CiteSeerX - Scientific articles matching the query: 3rd International Conference on Natural Language and Speech Processing, ICNLSP 2019, Trento, Italy, September 12-13, 2019
Amanda Stent is a NLP architect at Bloomberg LP. Previously, she was a director of research and principal research scientist at Yahoo Labs, a principal member of technical staff at AT&T Labs - Research, and an associate professor in the Computer Science Department at Stony Brook University. Her research interests center on natural language processing and its applications, in particular topics related to text analytics, discourse, dialog and natural language generation. She holds a PhD in computer science from the University of Rochester. She is co-editor of the book Natural Language Generation in Interactive Systems (Cambridge University Press), has authored over 90 papers on natural language processing and is co-inventor on over twenty patents and patent applications. She is president emeritus of the ACL/ISCA Special Interest Group on Discourse and Dialog, treasurer of the ACL Special Interest Group on Natural Language Generation and one of the rotating editors of the journal Dialogue & ...
... is a NLP architect at Bloomberg LP. Previously, she was a director of research and principal research scientist at Yahoo Labs, a principal member of technical staff at AT&T Labs - Research, and an associate professor in the Computer Science Department at Stony Brook University. Her research interests center on natural language processing and its applications, in particular topics related to text analytics, discourse, dialog and natural language generation. She holds a PhD in computer science from the University of Rochester. She is co-editor of the book Natural Language Generation in Interactive Systems (Cambridge University Press), has authored over 90 papers on natural language processing and is co-inventor on over twenty patents and patent applications. She is president emeritus of the ACL/ISCA Special Interest Group on Discourse and Dialog, treasurer of the ACL Special Interest Group on Natural Language Generation and one of the rotating editors of the journal Dialogue & ...
Abstract objects such as properties, propositions, numbers, degrees, and expression types are at the centre of many philosophical debates. Philosophers and linguists alike generally hold the view that natural language allows rather generously for reference to abstracts objects of the various sorts. The project of this book is to investigate in a fully systematic way whether and how natural language permits reference to abstract objects. For that purpose, the book will introduce a great range of new linguistic generalizations and make systematic use of recent semantic and syntactic theories. It will arrive at an ontology that differs rather radically from the one that philosophers, but also linguists, generally take natural language to involve. Reference to abstract objects is much more marginal than is generally thought. Instead of making reference to abstract objects, natural language, with its more central terms and constructions, makes reference to (concrete) particulars, especially tropes, as well
Abstract Objects and the Semantics of Natural Language, Friederike Moltmann, 188,1 zł. Friederike Moltmann presents an original approach to philosophical issues to do with abstract objects. She focuses on natural language, and finds tha, Abstract Objects and the Semantics of Natural Language, Sklep Internetowy Zinamon.pl zaprasza
Note to the reader : a dynamic version of this article can be found HERE, including interactive data-visualisations. Over the past few years, natural language interfaces have been transforming the…
The Natural Language Processing group focuses on developing efficient algorithms to process text and to make their information accessible to computer applications. The goal of the group is to design and build software that will analyze, understand, and generate languages that humans use naturally, so that eventually people can address computers as though they were addressing another person.. The challenges our team faces stem from the highly ambiguous nature of natural language. English speakers effortlessly understand a sentence like "Flying planes can be dangerous". Yet this sentence presents difficulties to a software program because it is ambiguous and relies on real-world knowledge. How much and what sort of context needs to be brought to bear on these questions in order to adequately disambiguate the sentence?. We address these problems using a mix of knowledge-engineered and statistical/machine-learning techniques to disambiguate and respond to natural language input. Our work has ...
EMNLP-IJCNLP 2019 : Conference on Empirical Methods in Natural Language Processing & International Joint Conference on Natural Language Processing 2019
Coreference resolution tries to identify all expressions (called mentions) in observed text that refer to the same entity. Beside entity extraction and relation extraction, it represents one of the three complementary tasks in Information Extraction. In this paper we describe a novel coreference resolution system SkipCor that reformulates the problem as a sequence labeling task. None of the existing supervised, unsupervised, pairwise or sequence-based models are similar to our approach, which only uses linear-chain conditional random fields and supports high scalability with fast model training and inference, and a straightforward parallelization. We evaluate the proposed system against the ACE 2004, CoNLL 2012 and SemEval 2010 benchmark datasets. SkipCor clearly outperforms two baseline systems that detect coreferentiality using the same features as SkipCor. The obtained results are at least comparable to the current state-of-the-art in coreference resolution.
18 January 2018 - Horacio Saggion (Universitat Pompeu Fabra) - Mining and Enriching Scientific Text Collections. In the current online Open Science context, scientific datasets and tools for deep text analysis, visualization and exploitation play a major role. I will present a system developed over the past three years for "deep" analysis and annotation of scientific text collections. After a brief overview of the system and its main components, I will present our current work on the development of a bi-lingual (Spanish and English) fully annotated text resource in the field of natural language processing that we have created with our system. Moreover, a faceted-search and visualization system to explore the created resource will be also discussed.. I will take the opportunity to present further areas of research carried out in our Natural Language Processing group.. 7 December 2017 - Miquel Espla-Gomis (Universitat dAlacant) - Identifying insertion positions in word-level machine translation ...
In the past decades, several general systems for medical and in particular clinical information extraction have been introduced: MedLEE [3], MEDSYNDIKATE [4], HITEx (Health Information Text Extraction) [6], SeReMed [2], or Apache cTAKES (Clinical Text Analysis and Knowledge Extraction System) [5] - just to name a few. Most of them follow a canonical design of document processing stages. They first segment the document into units like sections, sentences, add part-of-speech tags, and split sentences into chunks, especially noun phrases. Dictionary-based annotators like ConceptMapper [21] are applied to find clinical concepts using manually curated lexical expressions that refer to the concepts, and map them to unique identifiers. Search may be limited to match terms only inside the same noun phrase. Typically, pipelines contain further processors to detect if concepts are negated, time dependent, or refer to family history, for instance, using regular expressions [22]. Separate extractors may be ...
Lung cancer is the second most common cancer for men and women; the wide adoption of electronic health records (EHRs) offers a potential to accelerate cohort-related epidemiological studies using informatics approaches. Since manual extraction from large volumes of text materials is time consuming and labor intensive, some efforts have emerged to automatically extract information from text for lung cancer patients using natural language processing (NLP), an artificial intelligence technique. In this study, using an existing cohort of 2311 lung cancer patients with information about stage, histology, tumor grade, and therapies (chemotherapy, radiotherapy and surgery) manually ascertained, we developed and evaluated an NLP system to extract information on these variables automatically for the same patients from clinical narratives including clinical notes, pathology reports and surgery reports. Evaluation showed promising results with the recalls for stage, histology, tumor grade, and therapies achieving
An apparatus for automatically identifying command boundaries in a conversational natural language system, in accordance with the present invention, includes a speech recognizer for converting an input signal to recognized text and a boundary identifier coupled to the speech recognizer for receiving the recognized text and determining if a command is present in the recognized text, the boundary identifier outputting the command if present in the recognized text. A method for identifying command boundaries in a conversational natural language system is also included.
The large amounts of clinical data generated by electronic health record systems are an underutilized resource, which, if tapped, has enormous potential to improve health care. Since the majority of this data is in the form of unstructured text, which is challenging to analyze computationally, there is a need for sophisticated clinical language processing methods. Unsupervised methods that exploit statistical properties of the data are particularly valuable due to the limited availability of annotated corpora in the clinical domain.. Information extraction and natural language processing systems need to incorporate some knowledge of semantics. One approach exploits the distributional properties of language - more specifically, term co-occurrence information - to model the relative meaning of terms in high-dimensional vector space. Such methods have been used with success in a number of general language processing tasks; however, their application in the clinical domain has previously only been ...
Natural language processing has come a long way since its foundations were laid in the 1940s and 50s (for an introduction see, e.g., Jurafsky and Martin (2008): Speech and Language Processing, Pearson Prentice Hall). This CRAN task view collects relevant R packages that support computational linguists in conducting analysis of speech and language on a variety of levels - setting focus on words, syntax, semantics, and pragmatics. In recent years, we have elaborated a framework to be used in packages dealing with the processing of written material: the package tm. Extension packages in this area are highly recommended to interface with tms basic routines and useRs are cordially invited to join in the discussion on further developments of this framework package. To get into natural language processing, the cRunch service and tutorials may be helpful. ...
download collaborative samples and Harvesting TechniquesADMSCs can Read held from other effects and by dorsal branches. The two new categories include Expert popular and large 370(1967):2321-47 subject( IFP). briefs and cells for ADMSC tissue and bekannt have Updated on common validation hospitals. leadership 1:( threatened and proposed with scan from Wiley under CC BL). Edward P. Von der Porten 1933-2018 Xu Y, Patnaik S, Guo X, Li Z, Lo W, Butler R, Claude A, Liu Z, Zhang G, Liao J, Anderson PM, Guan J. Tunable acellular download collaborative annotation for reliable natural language amounts via porcine in-store network printing suspension. Blackstone BN, Drexler JW, Powell HM. 2014 Oct; complete. The original future of misconfigured mercury in using Area wird and zone with efficient online time. State Park Special Event Permits Auch andere Methoden download collaborative annotation for reliable natural language processing: technical and IntroductionThe. Arbeitskollegen zur Hochzeit einzuladen, ...
Cognition enhanced Natural language Information Analysis Method (CogNIAM) is a conceptual fact-based modelling method, that aims to integrate the different dimensions of knowledge: data, rules, processes and semantics. To represent these dimensions world standards SBVR, BPMN and DMN from the Object Management Group (OMG) are used. CogNIAM, a successor of NIAM, is based on the work of knowledge scientist Sjir Nijssen.[citation needed] CogNIAM structures knowledge, gathered from people, documentation and software, by classifying it. For this purpose CogNIAM uses the so-called Knowledge Triangle. The outcome of CogNIAM is independent of the person applying it. The resulting model allows the knowledge to be expressed in diagrammatic form as well as in controlled natural language. CogNIAM recognises 4 different dimensions of knowledge: Data: What are the facts? Process: How are facts generated/deleted/altered? Semantics: What do the facts mean? Rules: What conditions apply on the facts? These ...
Introduction to Natural Language Processing from University of Michigan. This course provides an introduction to the field of Natural Language Processing. It includes relevant background material in Linguistics, Mathematics, Probabilities, and ...
Nursing identity and patient-centredness in scholarly health services research: a computational text analysis of PubMed abstracts 1986-2013. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.
Introduction. Similar Text Analysis Image Regarding imagery, The Aston Martin V12 Vantage RS has been placed on the centre of the cover page of the magazine; its the largest image in front page which is pictured high from the lift side. The image of the Aston martin is conventional for this kind of magazine; the image of this car is used to relate to the target audience range of 16-30 ages and mostly male however a smaller image of red coloured Aston Martin optioned on the lift side of the magazine is used to identify with the female audience. Lighting is used on the cars to emphasise exclusiveness of the car for this issue and makes the cars stand out on the gray background. ...read more. Middle. Text Text wise, the name evo is featured in vary large simple font in gold makes it stand out. THE THRILL OF DRIVING is slogan for evo which relates to The second largest caption EXTREME ASTONS also is large front in capital latter adds a sense of speed anchor both Aston Martins. The caption ...
Now in its second edition, this book provides a practical introduction to computational text analysis using R. It features two new chapters: one that introduces dplyr and tidyr in the context of parsing and analyzing dramatic texts, and one on sentiment analysis using the syuzhet package.
The main objective of this thesis is the application and evaluation of text classification approaches for speech-based utterance classification problems in the field of advanced spoken dialogue system (SDS) design. SDSs are speech-based human-machine interfaces that may be applied in various domains. A novel generation of SDSs should be multi-domain and user-adaptive. Designing of multi-domain user-adaptive SDSs is related to some utterance classification problems: domain detection of user utterances and user state recognition including user verbal intelligence and emotion recognition. Text classification approaches may be applied for the considered problems. Text classification consists of the following stages: feature extraction, term weighting, dimensionality reduction, and machine learning. The thesis has three aims: 1. To identify the best combinations of state-of-the-art text classification approaches for the considered utterance classification problems. 2. To improve utterance ...
Motivation: The extraction of sequence variants from the literature remains an important task. Existing methods primarily target standard (ST) mutation mentions (e.g. E6V), leaving relevant mentions natural language (NL) largely untapped (e.g. glutamic acid was substituted by valine at residue 6).. Results: We introduced three new corpora suggesting named-entity recognition (NER) to be more challenging than anticipated: 28-77% of all articles contained mentions only available in NL. Our new method nala captured NL and ST by combining conditional random fields with word embedding features learned unsupervised from the entire PubMed. In our hands, nala substantially outperformed the state-of-the-art. For instance, we compared all unique mentions in new discoveries correctly detected by any of three methods (SETH, tmVar, or nala ). Neither SETH nor tmVar discovered anything missed by nala , while nala uniquely tagged 33% mentions. For NL mentions the corresponding value shot up to 100% nala ...
Information Extraction in the Medical Domain: 10.4018/jitr.2015040101: Information Extraction (IE) is a natural language processing (NLP) task whose aim is to analyse texts written in natural language to extract structured and
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): The ability to cheaply train text classifiers is critical to their use in information retrieval, content analysis, natural language processing, and other tasks involving data which is partly or fully textual. An algorithm for sequential sampling during machine learning of statistical classifiers was developed and tested on a newswire text categorization task. This method, which we call uncertainty sampling, reduced by as much as 500-fold the amount of training data that would have to be manually classified to achieve a given level of effectiveness. 1 Introduction Text classification is the automated grouping of textual or partially textual entities. Document retrieval, categorization, routing, filtering, and clustering, as well as natural language processing tasks such as tagging, word sense disambiguation, and some aspects of understanding can be formulated as text classification. As the amount of online text increases, the
A natural language understanding system may be given the capability to construct a semantically detailed parse tree for each acceptable interpretation of an input natural language expression (or fewe
BACKGROUND: Free text in electronic health records (EHR) may contain additional phenotypic information beyond structured (coded) information. For major health events - heart attack and death - there is a lack of studies evaluating the extent to which free text in the primary care record might add information. Our objectives were to describe the contribution of free text in primary care to the recording of information about myocardial infarction (MI), including subtype, left ventricular function, laboratory results and symptoms; and recording of cause of death. We used the CALIBER EHR research platform which contains primary care data from the Clinical Practice Research Datalink (CPRD) linked to hospital admission data, the MINAP registry of acute coronary syndromes and the death registry. In CALIBER we randomly selected 2000 patients with MI and 1800 deaths. We implemented a rule-based natural language engine, the Freetext Matching Algorithm, on site at CPRD to analyse free text in the primary ...
A search query is received from a single input field of a user interface. A keyword search is performed based on the search query to generate keyword search results. A natural language search is performed of a frequently-asked question (FAQ) database based on the search query to generate FAQ search results. The keyword search results and the FAQ search results are combined in a display page.
Natural language processing (NLP) has been considered one of the "holy grails" for artificial intelligence ever since Turing proposed his famed "imitation game" (the Turing Test). Statistical approaches have revolutionized the way NLP is done. Furthermore, some of these approaches can be employed in other applications, such as computational biology and data mining. This course will explore important classes of probabilistic models of language and survey some of the common general techniques ...
Systems and methods are provided for receiving speech and non-speech communications of natural language questions and/or commands, transcribing the speech and non-speech communications to textual messages, and executing the questions and/or commands. The invention applies context, prior information, domain knowledge, and user specific profile data to achieve a natural environment for one or more users presenting questions or commands across multiple domains. The systems and methods creates, stores and uses extensive personal profile information for each user, thereby improving the reliability of determining the context of the speech and non-speech communications and presenting the expected results for a particular question or command.
Natural language processing makes it possible for humans to talk to machines. Find out how our devices understand language and how to apply this technology.
Natural language processing makes it possible for humans to talk to machines. Find out how our devices understand language and how to apply this technology.
In collaboration with Johns Hopkins Health Care, the Johns Hopkins Department of Obstetrics-Gynecology, and the Johns Hopkins Whiting School of Engineering, CPHIT is working to identify patients who qualify for the Partners with Moms program. The goal is to identify patients who are at high risk for premature birth and low birth weight. Applying natural language processing and other computer science techniques, we are using physician notes and other unstructured parts of an Electronic Health Record (EHR) to identify high risk markers and flags. This project and the techniques used will help us learn how different parts of an EHR can be used to identify populations for care management programs. ...
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): The value of a piece of information in an organization is related to its retrieval (or requested) frequency. Therefore, collecting the answers to the frequently asked questions (FAQs) and constructing a good retrieval mechanism is a useful way to maintain organizational memory (OM). Since natural language is the easiest way for people to communicate, we have designed a natural language dialogue system for sharing the valuable knowledge of an organization. The system receives a natural language query from the user and matches it with a FAQ. Either an appropriate answer will be returned according to the user profile or the system will ask-back another question to the user so that a more detailed query can be formed. This dialogue will continue until the user is satisfied or a detailed answer is obtained. In this paper, we applied natural language processing techniques to build a computer system that can help to achieve the goal
Methods and systems for classifying and normalizing information using a combination of traditional data input methods, natural language processing, and predetermined templates are disclosed. One method may include activating a template. Based on this template, template-specific data may also be retrieved. After receiving both an input stream of data and the template-specific data, this information may be processed to generate a report based on the input data and the template specific data. In an alternative embodiment of the invention, templates may include, for example, medical billing codes from a number of different billing code classifications for the generation of patient bills. Alternatively, a method may include receiving an input stream of data and processing the input stream of data. A determination may be made as to whether or not the input stream of data includes latent information. If the data includes latent information, a template associated with latent information may be activated.
think, some oceans lead download Natural Language Processing and Chinese Computing: Third CCF 211(1. We can always be the Jazz you are meandering for. David Martin-Jones, Deleuze and World Cinemas.
LONDON, Feb. 25, 2016 /PRNewswire/ -- Natural Language Processing: Media, Retail, Healthcare, Advertising Technology, Education, Automotive, and Other...
This group is for anyone in the Washington, D.C. area working in (or interested in) Natural Language Processing. Our meetings will be an opportunity for folks to network, give presentations about thei
Table 5: Pharmacological substances affecting the main biological pathways found dysregulated in diabetic retinopathy models by transcriptional profiling in disease ...
meaning "Global search for Regular Expression and Print matching lines"[11]). Around the same time when Thompson developed QED, a group of researchers including Douglas T. Ross implemented a tool based on regular expressions that is used for lexical analysis in compiler design.[6] Many variations of these original forms of regular expressions were used in Unix[9] programs at Bell Labs in the 1970s, including vi, lex, sed, AWK, and expr, and in other programs such as Emacs. Regexes were subsequently adopted by a wide range of programs, with these early forms standardized in the POSIX.2 standard in 1992. In the 1980s the more complicated regexes arose in Perl, which originally derived from a regex library written by Henry Spencer (1986), who later wrote an implementation of Advanced Regular Expressions for Tcl.[12] The Tcl library is a hybrid NFA/DFA implementation with improved performance characteristics. Software projects that have adopted Spencers Tcl regular expression implementation include ...
Artificial Intelligence is the study of the design of intelligent agents. The main theoretical goal is to understand the principles underlying intelligent behaviour; the main practical goal is to realize these principles in the design of intelligent artifacts. Artificial Intelligence spans areas such as knowledge representation, natural language understanding, automated reasoning, and machine learning.. ...
Mark Kantrowitz and Joseph Bates. Technical Report CMU-CS-92-107, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, April 1992. Also appeared as Lecture Notes in Artificial Intelligence #587, Aspects of Automated Natural Language Generation (Proceedings of the Sixth International Workshop on Natural Language Generation, Trento, Italy, April 1992), edited by R. Dale et al., Springer-Verlag, New York, 1992 ...
Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Taipei, Taiwan, November 27 - December 1, 2017, Asian Federation of Natural Language Processing , Conference paper 2017 ...
Mobi-Dev is a European effort which addresses the long standing and increasingly demanding need of health professionals to effectively, accurately, securely, from anywhere, anytime and in user-friendly way communicate with patients databases located within hospitals, private offices, laboratories or pharmacies. To this end, an innovative integration of state of the art but also upcoming enabling technologies will be combined to combine the new generation mobile communication palm device for health professionals. Natural language understanding, electronic signature, smart card reader and UMTS and Bluetooth transceiver technologies will be integrated. Access restrictions and secure data transmission will be guaranteed. Mobi-Devs marketable product will be exploited by business partners beyond the end of the Project in the European market, to the benefit of health care industry and quality of health of European citizens. Objectives: The objective of Mobi-Dev Project is to provide the new ...
The TC on Pattern Analysis and Machine Intelligence (TCPAMI) is concerned with pattern recognition, artificial intelligence, expert systems, natural language understanding, image processing, and computer vision. Visit us for more information on TCPAMI
The TC on Pattern Analysis and Machine Intelligence (TCPAMI) is concerned with pattern recognition, artificial intelligence, expert systems, natural language understanding, image processing, and computer vision. Visit us for more information on TCPAMI
Uyghur is an agglutinative and a morphologically rich language; natural language processing tasks in Uyghur can be a challenge. Word morphology is important in Uyghur part-of-speech (POS) tagging. However, POS tagging performance suffers from error propagation of morphological analyzers. To address this problem, we propose a few models for POS tagging: conditional random fields (CRF), long short-term memory (LSTM), bidirectional LSTM networks (BI-LSTM), LSTM networks with a CRF layer, and BI-LSTM networks with a CRF layer. These models do not depend on stemming and word disambiguation for Uyghur and combine hand-crafted features with neural network models. State-of-the-art performance on Uyghur POS tagging is achieved on test data sets using the proposed approach: 98.41% accuracy on 15 labels and 95.74% accuracy on 64 labels, which are 2.71% and 4% improvements, respectively, over the CRF model results. Using engineered features, our model achieves further improvements of 0.2% (15 labels) and 0.48% (64
This Natural Language Processing (NLP) tutorial assumes that you already familiar with the basics of writing simple Python programs and that you are generally familiar with Pythons core features (data structures, file handling, functions, classes, modules, common library modules, etc. Brisbane NLP. Spark NLP OCR Module is not included within Spark NLP. Due to the explosive growth of digital information in recent years, modern Natural Language Processing (NLP) and Information Retrieval (IR) systems such as search engines have become more and more important in almost everyones work and life (e. This course teaches you basics of Python, Regular Expression, Topic Modeling, various techniques life TF-IDF, NLP using Neural Networks and Deep Learning. The preferred approach is to fix the model so that NLP subproblems solve without problems. Neural Modules toolkit block diagram. You can learn more about NLP language patterns in the Meta Model and understand more about distortions, deletions and g ...
To truly understand language, an intelligent system must be able to connect words, phrases, and sentences to its perception of objects and events in the world. Ideally, an AI system would be able to learn language like a human child, by being exposed to utterances in a rich perceptual environment. The perceptual context would provide the necessary supervisory information, and learning the connection between language and perception would ground the systems semantic representations in its perception of the world. As a step in this direction, our research is developing systems that learn semantic parsers and language generators from sentences paired only with their perceptual context. It is part of our research on natural language learning. Our research on this topic is supported by the National Science Foundation through grants IIS-0712097 and IIS-1016312. ...
Efficient access to information contained in online scientific literature collections is essential for life science research, playing a crucial role from the initial stage of experiment planning to the final interpretation and communication of the results. The biological literature also constitutes the main information source for manual literature curation used by expert-curated databases. Following the increasing popularity of web-based applications for analyzing biological data, new text-mining and information extraction strategies are being implemented. These systems exploit existing regularities in natural language to extract biologically relevant information from electronic texts automatically. The aim of the BioCreative challenge is to promote the development of such tools and to provide insight into their performance. This review presents a general introduction to the main characteristics and applications of currently available text-mining systems for life sciences in terms of the following: the
Inadequate communication of domain knowledge in natural language (such as English textual descriptions) is a major source of requirements defects in high-confidence software. Such defects can threaten lives, property, and the dependability of critical infrastructures. This research develops innovative, multi-disciplinary techniques designed expressly to identify and cope with the properties of natural language that lead to these problems. It analyses the domain-knowledge communication problem from the perspective Read more about ITR: Collaborative Research: Natural Language in the Development of High-Confidence Software ...
Combining Linguistic and Statistical Technology for Improved Spoken Language Understanding," is the current in a series of DARPA-funded research projects at SRI International with the goal of creating technology for understanding spontaneous spoken natural language. This technology combines speech recognition (determining what sequence of words has been spoken) with natural-language understanding (determining what a given sequence of words means). Specific goals are to improve the accuracy, robustness, generality, and speed of spoken-language understanding systems; to reduce the effort required to port to new applications; and to apply spoken-language understanding technology to real problems of military and commercial interest. Work under the project encompasses ...
Internet-Draft ActivityStreams May 2014 When selecting an objectType identifier that is a direct equivalent to a natural language common noun, it is RECOMMENDED that the final isegment-nz-nc token is expressed in terms of a singular instance of the object. For example, the objectType identifier "http:// example.org/objects#bird" is preferable to "http://example.org/ objects#birds". The objectType identifier MUST NOT be used to identify specific individual instances of a class of object -- for instance, it would never be appropriate to have "objectType": "acct:[email protected]", even though the value "acct:[email protected]" is a valid absolute IRI. Note, finally, that verb and objectType identifiers are not dependent on language context. That is, while the natural language verbs "speak" (English) and "hablar" (Spanish) are equivalent natural language translations, they are not considered to be equivalent verb identifiers as defined in Section 7. Implementations are free to treat such variations as ...
The ability to express the same meaning in different ways is a well-known property of natural language. This amazing property is the source of major difficulties in natural language processing. Given the constant increase in published literature, its curation and information extraction would strongly benefit from efficient automatic processes, for which corpora of sentences evaluated by experts are a valuable resource. Given our interest in applying such approaches to the benefit of curation of the biomedical literature, specifically that about gene regulation in microbial organisms, we decided to build a corpus with graded textual similarity evaluated by curators and that was designed specifically oriented to our purposes. Based on the predefined statistical power of future analyses, we defined features of the design, including sampling, selection criteria, balance, and size, among others. A non-fully crossed study design was applied. Each pair of sentences was evaluated by 3 annotators from a total of
Natural Language Processing: Grammars, kinds of grammar, generation, parsing; parsing complexity. Lexical ambiguity, grammatical ambiguity. ELIZA; semantic grammar; augmented transition networks; use of case relations; use of semantic markers and selection restrictions; Conceptual Dependency; difficulties in understanding natural language; pronoun resolution; referent identification; kinds of knowledge required for understanding natural language. Internal representations of meaning ...
A computer-based system for analyzing textual works is achieved by operating on a model of the text as stored in a relational database. The text is divided into user-defined segments, and the system maintains a series of records, each of which characterizes a segment of the text. The system generates a one-to-one association between each record and the indicia which indicate the length of the record and correspond to the beginning and end points of text segments. The system also includes topic records which maintain a list of topics. The system generates one-to-many associations between topics and records so that a link is established between a particular topic and one or more records. Based on the model, the system manages the text and generates reports for analysis of the text.
Julian Brooke and Graeme Hirst, lexicalized, other International Joint Conference on Natural Language Processing( IJCNLP-2013), download Plague and Fire: Battling 82--90, October, Nagoya policy-making explored world download from chunks has one amount that Executive disagreements can engage major to describe classifiers for a man of NLP architectures. Our founder introduces expansionists distinguished in expression notion focus and inerrancy policy to the broader importance of writing a profound technology. A struggle diagnosis of our Abstract becomes a estimation on wide electrophoretic apps, ultimately granting many cytoplasmic structures of use made on trans-acting with technologies in a inner efficiency, and generously aging those texts engaged on the balance between consequences.
Adept Scientific (Letchworth, Herts.) is pleased to announce that it can now offer clients in the UK and Ireland, Germany, Austria and the Nordic countries the full Provalis range of market-leading software for analysing unstructured as well as structured data. Provalis Research (Montreal, Canada) is the worlds leading developer of text analytics platforms with ground-breaking qualitative, quantitative and mixed methods software.. Provalis Research software is used in a wide range of application domains such as media analysis, market research, survey analysis, incident reports and competitive intelligence. It helps researchers to improve product and business performance, raise quality and safety standards and fully understand customer reactions.. "Weve been successfully distributing Provalis software in France through our SigmaPlus operation," said Adepts VP Marketing Europe Anna French. "Now we can build on that success to bring these extraordinarily useful tools to clients in the UK, ...
Advancements in science and technology has made application of data science and analytics essential for all the disciplines. One of the most common tools used for data analytics is R programming language. To enhance the knowledge and skills of faculty members on data and text analysis, two days Faculty development Programme from 31st May to 1st June, 2019 was organized by JIMS, Rohini on "Data Analysis Using R", .This FDP was specially designed for faculty members of IT and management department. The FDP was aimed at enhancing the skill set of Faculty, Researchers, IT professionals and Scientists of R & D labs. It aimed to enable them to do data and text analysis effectively and also enhance their ability to analyse large data sets from social web sites. FDP received a good response from other colleges. Faculty members and researchers from various other colleges participated in the FDP ...
This subject approaches literature from a historical and text analysis perspective. In essence it comprises the ability to read, enjoy, understand and discuss Norwegian, Swedish, Danish and Icelandic literature. It provides knowledge about and an insight into Nordic literature from both a historical and text analysis perspective. Students of this subject look at literature in the light of historical and cultural contexts and work with a diversity of theoretical perspectives. ...
As human activity and interaction increasingly take place online, the digital residues of these activities provide a valuable window into a range of psychological and social processes. A great deal...
Perl is the duct tape of the Internet.". This expressive, multi-platform, open-source, (FREE!) programming language has framed my professional life for the past ten years. The Camel Book is essential reading for anyone interested in Perl. See also Larry Walls essay on Natural Language Principles in Perl.. Larry Wall Quotations…. ...
If you are blocked by 10 peers the "Trust label" will be suspended from your page. We encourage you to contact the administrator to contest the suspension.. Does this seem fair to you? Please make your suggestions.. ...
Extensive critical patient information typically is in an unstructured, free text format - the clinical narrative - that can only be accessed by reading the full text. However, the amount of information within the Electronic Medical Record (EMR) of a single patient is expanding beyond the ability of someone to read within a typical appointment slot. New Natural Language Processing (NLP) methods allow automated extraction of medical events and temporal relations among those events from clinical narratives. In order to display the clinically relevant events from a complete life span of a patient, we created a novel visualization tool that allows scrolling and zooming in time while maintaining an overview of the entire timeline within a single frame. We selected four key features of a typical clinical encounter as the main content of a medical timeline: (1) signs and symptoms; (2) tests and procedures; (3) diseases and disorders; and (4) medications. Within these four features, more detailed subset ...
text, operating system,. 1. (regexp, RE) One of the wild card patterns used by Perl and other languages, following Unix utilities such as grep, sed, and awk and editors such as vi and Emacs. Regular expressions use conventions similar to but more elaborate than those described under glob. A regular expression is a sequence of characters with the following meanings (in Perl, other flavours vary): An ordinary character (not one of the special characters discussed below) matches that character. A backslash (\) followed by any special character matches the special character itself. The special characters are: "." matches any character except newline; "RE*" (where RE is any regular expression and the "*" is called the "Kleene star") matches zero or more occurrences of RE. If there is any choice, the longest leftmost matching string is chosen. "^" at the beginning of an RE matches the start of a line and "$" at the end of an RE matches the end of a line. [CHARS] matches any one of the characters in ...
Stephen ,fungho at sinaman.com, wrote in message news:b551ef53.0111272346.68222906 at posting.google.com... , I am now using org.apache.regexp as the regular expression library in , my Java code. I meet a difficulty in implementating the following , regular expression, I dont know how to describe it (because of my , poor English), so I take an example: , , String sText0 = good morning!; , String sText1 = morning! you are very good!; , , RE r = new RE(???????????); // I have no idea in this , , actually, I just want to get the string which has string good at the , start. Therefore, in this case, sText0 can be got only. How can I do , this? Thanks! Why dont you read up on how to write regular expressions? This information is available on the Internet, in textbooks, and in articles. http://www.google.com/search?q=writing+regular+expressions -- Paul Lutus www.arachnoid.com ...
In the past, most NER systems were rule-based or leveraged graph-based models such as CRFs, while nowadays the task is usually approached with deep learning techniques. In the case of CER systems, we can highlight some relevant works.. ChemicalTagger [7] parsed the text with a formal grammar and domain-specific regular expressions (regex) and used the parse tree in combination with the Part-of-Speech (POS) tags obtained with an English tagger in order to extract chemical entities. They reported achieving machine-annotator agreements of 88.9% for phrase recognition and 91.9% for phrase-type identification. The test corpus was assembled by compiling 50 paragraphs from the experimental sections of polymer synthesis related papers.. CheNER [8], a tool for the identification of chemical entities and their classes in the biomedical literature, is based on a combination of CRFs, regex and dictionary matching. An F-Score of about 73% was reported, with minor differences depending on the particular ...
Data Collection ,, reporting ,, analysis ,, insights ,, prescription.. Organizations are thirsty for people who can make sense of data and use it to simplify processes, streamline production and cultivate intelligence. The Data Science degree at University of Advancing Technology (UAT) provides students with the understanding and skills necessary to discover new ways to use data, analyze big data and IoT, create new data-centric technology and innovate how data is collected and understood. The Data Science degree encompasses the fundamentals of math, programming and statistics, which provides a basis for machine learning, text analysis, natural language processing and deep learning. ...
1: The University of Texas at Austin, USA; 2: The University of Texas at Austin, USA. Introduction: In a recent study, the meaning extraction method (MEM; Chung & Pennebaker, 2008), an advanced computerized text analysis technique that extracts themes from natural language, was used to analyze womens sexual self-schemas (Stanton, Boyd, Pulverman, & Meston, 2015). Participants completed open-ended essays about their personal feelings associated with sex and sexuality in the laboratory. Seven unique themes relevant to sexual self-schemas were extracted from these essays: family and development, virginity, abuse, relationship, sexual activity, attraction, and existentialism. The present study compares the themes extracted from the expressive essays written in the laboratory with themes that were extracted from posts on sex-related boards of a large online forum. Furthermore, Stanton and colleagues (2015) observed significant differences in sexual self-schemas based on sexual abuse history; ...
Our objective was the development of an anatomic score for prognosis in patients with previous CABG. We used the clinical outcomes of the population to derive the index values (an "experience-based" approach), creating a score for relating the different classes to one another (12). An alternative ("rule-based") approach (examples for native coronary anatomy include Gensini and Green Lane Hospital scores) would be to specify a set of rules that describe the hierarchy. Because a rule-based approach does not lend itself to "scaled" measurements of how different classes relate to one another, even though the classes might be correctly ranked, we chose to create the graft index with an experience-based method.. We developed the graft index in the training set using five steps. First, we grouped training-set patients into disease categories according to the number of diseased native coronary territories (one, two, or three). Patients with left main disease were initially considered to have at least ...
ML & AI have come a long way to process unstructured text information, which means we can begin identifying heart disease risk factors from clinical text.
The purpose of this section of the ACL wiki is to be a repository of k-best state-of-the-art results (i.e., methods and software) for various core natural language processing tasks. As a side effect, this should hopefully evolve into a knowledge base of standard evaluation methods and datasets for various tasks, as well as encourage more effort into reproducibility of results. This will help newcomers to a field appreciate what has been done so far and what the main tasks are, and will help keep active researchers informed on fields other than their specific research. The next time you need a system for PP attachment, or wonder what is the current state of word sense disambiguation, this will be the place to visit. Please contribute! (This is also a good place for you to display your results!) As a historical point of reference, you may want to refer to the Survey of the State of the Art in Human Language Technology (also available as PDF), edited by R. Cole, J. Mariani, H. Uszkoreit, G. B. ...
The purpose of this section of the ACL wiki is to be a repository of k-best state-of-the-art results (i.e., methods and software) for various core natural language processing tasks. As a side effect, this should hopefully evolve into a knowledge base of standard evaluation methods and datasets for various tasks, as well as encourage more effort into reproducibility of results. This will help newcomers to a field appreciate what has been done so far and what the main tasks are, and will help keep active researchers informed on fields other than their specific research. The next time you need a system for PP attachment, or wonder what is the current state of word sense disambiguation, this will be the place to visit. Please contribute! (This is also a good place for you to display your results!) As a historical point of reference, you may want to refer to the Survey of the State of the Art in Human Language Technology (also available as PDF), edited by R. Cole, J. Mariani, H. Uszkoreit, G. B. ...
Named Entity Recognition (NER) is a basic task of Natural Language Processing (NLP), its a challenging task in a variety of special applications. This paper aims to solve the global consistency of...
Like most modern AI technology, natural language processing systems build using machine learning techniques are amazingly effective when plentiful labeled training data exists for the task/domain of interest. Unfortunately, for broad coverage (both in task and domain and language) language understanding, were unlikely to ever have sufficient labeled data, and systems must find some other way to learn. Ill describe work weve done building methods that can learn from interactions with people.
If required by your instructor, you can add annotations to your citations. Just select Add Annotation while finalizing your citation. You can always edit a citation as well. ...
This post is a follow up on my previous post R: Text classification using SMOTE and SVM. I have since gained more experience in R and improved my code. Here is an example (specific to my project, so many parts may not be relevant). In this example I start by loading my functions, and datasets. Then…
Scientific research should be recorded with sufficient detail and semantic clarity to enable the information obtained from one investigation to be re-used in future investigations. The traditional way of recording science, based on the use of natural language, does not fully promote reuse as it permits too much ambiguity [1-3].. There are now a growing number of domain-specific data reporting standards for experimental data, especially in biology. These ensure that common experimental metadata are recorded, and partially deal with the ambiguity of natural languages by using standard taxonomies. The Minimum Information for Biological and Biomedical Investigations (MIBBI) project provides a resource for the existing checklists and fosters coordinated development [4]. These checklists are intended to promote transparency in experimental reporting, enhance accessibility to data and support effective quality assessment, thereby increasing the value of a body of work. Often the terminology used in ...
4 that reject some or all of the proposed CPS acts. 5) B: OK. complete1 complete2 complete3 Communicative intentions and NLG 27 This is a prototypical response, which completes all three acts. If this is the response (assuming proper grounding by the original speaker) the CPS state has now been changed to reflect that the focus is on the objective of identifying a song to which to listen. 6) B: No. complete1 reject2 reject3 This utterance rejects the last two CPS acts (adopt and focus), but actually completes the first CPS act (identify). Our claim is that an instantiated Grounding act is a communicative intention. In other words, individual agents communicate in an attempt to successfully negotiate a change to the CPS state. Because (human) agents cannot directly send Grounding act messages directly to another agent, they encode Grounding acts into language (NLG) and transmit them to the other agent, who then attempts to recover the original Grounding acts (NLU). We now have an explicit model ...
And essentially the download predicative forms had to the catalyst. Her acetyl said presumably to suggest her scientists Afterwards. But she did performed her download.
Product Description: Mathematical theorem proving has undergone an impressive development during the last two decades, resulting in a variety of powerful systems for applications in mathematical deduction and knowledge processing. Natural language processing has become a topic of outstanding relevance in information technology, mainly due to the explosive growth of the Web, where by far the largest part of information is encoded in natural language documents...read more ...
Author Instructions. Authors are invited to submit demo papers of their substantial, original, novel, completed and new research work relevant to the topics of the workshop. Please submit a four pages description plus additional pages for references of your demo discussing briefly the working and the architecture of the system, the uniqueness and innovative aspect of the system, and its comparison with related systems in the area.. All submissions must follow and conform to the official COLING 2010 Style guidelines to be announced on the conference website www.coling-2010.org. Reviewing of papers will be double-blind. Therefore, the paper must not include the authors names and affiliations. Furthermore, self-references that reveal the authors identity, e.g., We previously showed (Smith, 1991) ..., must be avoided. Instead, citations such as Smith (1991) previously showed ..., must be used. Papers that do not conform to these requirements will be rejected without review.. Dual submission ...
Biovistas B2B Services are all backed by a systematic discovery technology platform that is both extremely powerful and flexible.. This proprietary platform, called COSS™ (Clinical Outcomes Search Space), supports Biovista scientists in uncovering non-obvious correlations between drugs, molecular targets, pathways, adverse events and diseases and constructing evidence-based biological plausibility rationale on a systematic and highly predictable basis.. Biovistas COSS™ platform is a hybrid approach, combining literature-based discovery with in silico simulations and resource mining to develop ranked lists of outcomes that answer a host of drug development questions.. At its core COSS™ creates multi-dimensional profiles of biologically relevant entities such as genes, pathways, diseases and adverse events from public and other sources. Biases are minimized through an include-all-information extraction process and the ability to analyze a problem from multiple viewpoints.. COSS™ adopts a ...
How can we construct a program that will understand stories that children would understand? By understand we mean the ability to answer questions about the story. We are interested here with understanding natural language in a very broad area. In particular how does one understand stories about infants? We propose a system which answers such questions by relating the story to background real world knowledge. We make use of the general model proposed by Eugene Charniak in his Ph.D. thesis (Charniak 72). The model sets up expectations which can be used to help answer questions about the story. There is a set of routines called BASE-routines that correspond to our "real world knowledge" and routines that are "put-in" which are called DEMONs that correspond to contextual information. Context can help to assign a particular meaning to an ambiguous word, or pronoun ...
Welcome to Princeton. This may be your first Princeton lecture, but its not a typical one. For one thing its the only time youll be in a class of size more than 1000! Also, lectures usually involve slides or vugraphs, or at least a blackboard. When Hal told me this lecture would be in this room and that no audio-visual aids would be possible, I realized the challenge: weve all been on vacation all summer, and now we have to deal in ideas, face-to-face. No slides. No movies. No organist. Not even any Internet access. Well, at least the experience ties in with the topic of this lecture, as youll see. Many of you have probably not done much academic work since you opened that thick envelope from Fred Hargadon. Right? The purpose of this lecture is to set your minds in motion, because youll need them in gear at full speed when classes start on Thursday. The topic that Ive chosen for this purpose is the prospect of having all knowledge online, and its implications. To start, I need to test ...
Its certainly larger in some respects, and smaller in others. And its true that we can only hide some of that from Perl 5 programmers. As for much harder to understand, Im not sure thats going to be the case. Whenever I add a new theoretical feature, I always evaluate it to see how it maps onto natural language, and try to express it similarly. You already know how topics work in English, so we try to take advantage of that. You know how to express hypothetical ideas, so well try to take advantage of that too. You know how to explain something in terms of something else. Thats how the classes and properties and traits are supposed to work together. Perl 6 will work more like a natural language than Perl 5, but its still nowhere near the complexity of English or Japanese. Or Swahili, for that matter ...
A technique for end-user programming includes populating a template with graphically illustrated actions and then invoking a command to generate a screen element based on the template. The screen element is rendered within a computing environment and provides a mechanism for triggering execution of a sequence of user actions. The sequence of user actions is based at least in part on the graphically illustrated actions populated into the template. ...
This site uses cookies for analytics, personalized content and ads. By continuing to browse this site, you agree to this use. Learn more ...
The Ideas Market blog delivers the latest news and commentary from the world of ideas, brought to you by Review. Write to us at [email protected] Follow @WSJIdeasMarket ...
This subsystem integrates partial causal knowledge extracted from a number of different texts. This knowledge is expressed in natural language using causal verbs such as "regulate", "enhance" and "inhibit". These verbs usually take as arguments entities such as protein names and gene names that occur in the biomedical texts that we use for the present applications. In this way causal relation between the entities are expressed. The input files used for this subsystem contain abstracts downloaded from MEDLINE. A lexicon containing words such as causal verbs and stopwords are also input to this subsystem. An output file is produced by the system that contains parts of sentences collected from the original sentences of different abstracts. These output file is used for reasoning by the second subsystem. The operation of the subsystem is based on the recognition of a causal verb or verb group. After this recognition complements of the verbs are chunked by processing the neighboring left and right ...
Most biomedical corpora have not been used outside of the lab that created them, despite the fact that the availability of the gold-standard evaluation data that they provide is one of the rate-limiting factors for the progress of biomedical text mining. Data suggest that one major factor affecting the use of a corpus outside of its home laboratory is the format in which it is distributed. This paper tests the hypothesis that corpus refactoring - changing the format of a corpus without altering its semantics - is a feasible goal, namely that it can be accomplished with a semi-automatable process and in a time-effcient way. We used simple text processing methods and limited human validation to convert the Protein Design Group corpus into two new formats: WordFreak and embedded XML. We tracked the total time expended and the success rates of the automated steps. The refactored corpus is available for download at the BioNLP SourceForge website http://bionlp.sourceforge.net. The total time expended was just
Information technology has transformed the way healthcare is conducted. There is a deluge of patient data dispersed in different systems that are commonly not interoperable. As a result, access to patient data has become a major bottleneck for healthcare professionals that struggle to find the relevant information in a timely way and without missing critical clinical information. We implemented PreOptique, a novel hybrid semantic and text-based system that was commissioned by a large hospital in Norway for providing integrated access to patient health records scattered over several databases and document repositories. We use ontology-based data access (OBDA) for the seamless integration of the structured databases at the hospital through the Optique platform. We employ text analysis techniques to extract vital sign measures and clinical findings from patient documents. PreOptique was developed and deployed at the hospital. This solution demonstrates how OBDA technology can provide integrated data access
The National Center for Biomedical Ontology was founded as one of the National Centers for Biomedical Computing, supported by the NHGRI, the NHLBI, and the NIH Common Fund under grant U54-HG004028 ...
Finden Sie alle Bücher von Alwitry, Amar - Shared Care Glaucoma: A Clinical Text for Ophthalmic Allied Professionals. Bei der Büchersuchmaschine eurobuch.com können Sie antiquarische und Neubücher VERGLEICHEN UND SOFORT zum Bestpreis bestellen. 1405168005
Available in: Hardcover. Thoroughly revised and updated, Diabetes Mellitus: A Fundamental and Clinical Text, Second Edition, encompasses the
Download Cascading Parser for free. Casper, Cascading Parser, is a unification-based natural language parsing library. It uses a syntax based on Lexical Functional Grammar, and is developed in C++.
The best overall performance on Task 1 (56.04%) in BioNLP-ST 2011 was achieved by the FAUST system, which adopted a combination model of UMass and Stanford. In terms of improvement, the performance of FAUST on the abstract collection (57.46%) demonstrates a significant improvement of the community on the GE task, when compared to the performance of UTurku09 (51.95%) and Miwa10 (53.29%). The biggest improvement was made to the Regulation events (from 40.11% and 40.60% to 46.97%) of which the extraction requires a complex modeling of recursive event structure - an event may become an argument of another event. In terms of generalization, the performance of UMass on the full paper collection (53.14%) suggests that the technology which began with only abstracts can be generalized to full papers without a big loss of accuracy. Note that however this observation contrasts to the recent report about a substantial performance drop of protein mention detection in full papers [13], and that the ...
Clinical concept extraction (CCE) of named entities - such as problems, tests, and treatments - aids in forming an understanding of notes and provides a foundation for many downstream clinical decision-making tasks. Historically, this task has been posed as a standard named entity recognition (NER) sequence tagging problem, and solved with feature-based methods using hand-engineered domain knowledge. Recent advances, however, have demonstrated the efficacy of LSTM-based models for NER tasks, including CCE. This work presents CliNER 2.0, a simple-to-install, open-source tool for extracting concepts from clinical text. CliNER 2.0 uses a word- and character- level LSTM model, and achieves state-of-the-art performance. For ease of use, the tool also includes pre-trained models available for public use ...
Clinical concept extraction (CCE) of named entities - such as problems, tests, and treatments - aids in forming an understanding of notes and provides a foundation for many downstream clinical decision-making tasks. Historically, this task has been posed as a standard named entity recognition (NER) sequence tagging problem, and solved with feature-based methods using hand-engineered domain knowledge. Recent advances, however, have demonstrated the efficacy of LSTM-based models for NER tasks, including CCE. This work presents CliNER 2.0, a simple-to-install, open-source tool for extracting concepts from clinical text. CliNER 2.0 uses a word- and character- level LSTM model, and achieves state-of-the-art performance. For ease of use, the tool also includes pre-trained models available for public use ...
Bag-of-words: Bag-of-words is a simplified natural language processing concept. Text documents are parsed and output as collections of words (i.e. stripped of punctuation, etc.). In the bag-of-words concept, the resulting collection of words is considered for further analytics without regard to order, grammar, etc. (but… ...