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An information retrieval system and method employing spatially selective features. A geo-coded database stores advertiser records which include location information. Received search requests are matched with database records based on location information in the search requests and the record location information. In this manner, a user can search for information on a local basis and receive only the most relevant local search results.
A method and system for allowing a calling party to save information obtained from an information retrieval system. The caller may select options to save the information to a memory location, e.g., the callers own network-based voice mail system or a temporary voice mailbox provided for the caller by the information provider, from which the caller can subsequently retrieve and review the information. The information may be saved to an Internet-based website from which the caller may subsequently retrieve the information. The information may be forwarded to a separate telephone directory number for receipt by a third person or for storing on a remote voice mail system. Additionally, the information may be electronically mailed to the callers electronic mail address for subsequent retrieval. Discussions with a live attendant may be recorded and stored, as audio files or as converted to text, for access by or delivery to the caller.
An information retrieval method includes pre-processing a set of historical query information and processing a user query. Pre-processing a set of historical query information includes determining a plurality of semantic patterns based on a plurality of queries in the set of historical query information; establishing correspondence relationships between the plurality of semantic patterns and a plurality of filtering and ranking operations. Processing a user query comprises receiving the user query; retrieve a plurality of results in response to the user query; determining a semantic pattern that corresponds to the user query; determining a set of filtering and ranking operations that corresponds to the semantic pattern based on the correspondence relationships; and performing the set of filtering and ranking operations on the plurality of results to generate a set of filtered and ranked results.
Daniel, It might be worth your while to attempt antigen retrieval at a pH of 10 or 11 in an electric pressure cooker. You could also try the double whammy (antigen retrieval and enzyme digestion(protease or trypsin)). If this fails then the tissue is problably beyond resuscitation. Susie Smith, HT/HTL(ASCP), B.S. Research Associate Cytologix Corporation -----Original Message----- From: Daniel Martinez [mailto:[email protected]] Sent: Tuesday, November 07, 2000 9:45 AM To: [email protected] Subject: Antigen Retrieval Methods I currently have a rare Parkinsons case that I am having trouble staining. This tissue has been fixing in formalin for 13yrs. I am attempting to stain this tissue with several alpha-synuclein antibodies that we produce. To date, I have tried formic acid, proteinase-K, microwave, and boiling treatments. Any advice on other methods that might be worth trying would be appreciated. Thanks for your help Dan Martinez CNDR/University of Pennsylvania ...
TY - GEN. T1 - A similarity retrieval method for functional magnetic resonance imaging (fMRI) statistical maps. AU - Tungaraza, R. F.. AU - Guan, J.. AU - Rolfe, S.. AU - Atmosukarto, I.. AU - Poliakov, A.. AU - Kleinhans, N. M.. AU - Aylward, E.. AU - Ojemann, J.. AU - Brinkley, J. F.. AU - Shapiro, L. G.. PY - 2009/12/15. Y1 - 2009/12/15. N2 - We propose a method for retrieving similar fMRI statistical images given a query fMRI statistical image. Our method thresholds the voxels within those images and extracts spatially distinct regions from the voxels that remain. Each region is defined by a feature vector that contains the region centroid, the region area, the average activation value for all the voxels within that region, the variance of those activation values, the average distance of each voxel within that region to the regions centroid, and the variance of the voxels distance to the regions centroid. The similarity between two images is obtained by the summed minimum distance of ...
Melevin, P., Dillman, D., Baxter, R., & Lamiman, C. (1999). Personal Delivery of Mail Questionnaires for Household Surveys: A Test of Four Retrieval Methods. Journal of Applied Sociology, Vol. 16(No. 1), 69 - 88 ...
A system and method for content-based search and retrieval of visual objects. A base visual information retrieval (VIR) engine utilizes a set of universal primitives to operate on the visual objects. An extensible VIR engine allows custom, modular primitives to be defined and registered. A custom primitive addresses domain specific problems and can utilize any image understanding technique. Object attributes can be extracted over the entire image or over only a portion of the object. A schema is defined as a specific collection of primitives. A specific schema implies a specific set of visual features to be processed and a corresponding feature vector to be used for content-based similarity scoring. A primitive registration interface registers custom primitives and facilitates storing of an analysis function and a comparison function to a schema table. A heterogeneous comparison allows objects analyzed by different schemas to be compared if at least one primitive is in common between the schemas. A
Relevance feedback (RF) has become an active research area in Content-based Image Retrieval (CBIR). RF attempts to bridge the gap between low-level image features and high-level human visual perception by analyzing and employing user feedback in an effort to refine the retrieval results to better reflect individual user preference. Need for overcoming this gap is more evident in medical image retrieval due to commonly found characteristics in medical images, viz., (1) images belonging to different pathological categories exhibit subtle differences, and (2) the subjective nature of images often elicits different opinions, even among experts. The National Library of Medicine maintains a collection of digitized spine X-rays from the second National Health and Nutrition Examination Survey (NHANES II). A pathology found frequently in these images is the Anterior Osteophyte (AO), which is of interest to researchers in bone morphometry and osteoarthritis. Since this pathology is manifested as deviation ...
Inquire and Speak to Expert for More Details at http://www.theinsightpartners.com/inquiry/TIPTE100000349 Some of the important players in Automated Storage and Retrieval System market are Bastian Solutions, LLC, Daifuku Co., Ltd., Kardex Group, Mecalux S.A., TGW Logistics Group, System Logistics Corporation, Vanderlande Industries B.V., SSI Schaefer Group, Egemin Automation, Inc. and Knapp AG.. Table of Contents 1 Introduction. 2 Key Takeaways. 3 Market Landscape. 4 Automated Storage and Retrieval System Market - Key Industry Dynamics. 5 Automated Storage and Retrieval System Market Analysis- Global. 6 Automated Storage and Retrieval System Market Revenue and Forecasts to 2025 - Global. 7 Automated Storage and Retrieval System Market Revenue and Forecasts to 2025 - Type. 8 Automated Storage and Retrieval System Market Revenue and Forecasts to 2025 - End-user. 9 Automated Storage and Retrieval System Market Revenue and Forecasts to 2025 - Geographical Analysis. 11 Industry Landscape. 12 ...
Manuscript submissions for the Biocuration 2013 Virtual Issue are due November 30, 2013. The 2013 Biocuration Virtual issue will be published online in conjunction with the Biocuration 2013 meeting in Cambridge, UK next April 2013 and the International Society for Biocuration. To submit a manuscript go to the DATABASE journals home page (,http://database.oxfordjournals.org/,;) and click on submit now after having read the Instructions to Authors. Authors should CLEARLY state that they are submitting a manuscript for consideration for the Biocuration 2013 meetings issue so that the DATABASE staff will ensure appropriate fast-tracking. In addition, select Biocuration Conference Paper as the manuscript type on the DATABASE submission form. Submitting a paper to DATABASE does not sign you up to give a talk or poster, you must register your interest separately. Please submit an abstract at ,http://www.ebi.ac.uk/biocuration2013/,; if you want to present at the meeting. --- Dear Colleagues, The ...
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What is Content Based Image Retrieval System (CBIRS)? Definition of Content Based Image Retrieval System (CBIRS): A system that supports querying and retrieval of images exploiting information manually provided or automatically extracted from the images themselves.
When a query is commenced, the query is resolved as a similarity search by a couple of search engines (including AltaVista, Excite, etc.). The Web assistant then collects the top n (60 for the prototype) documents returned and groups them into clusters. What differs here from the Scatter/Gather by [4] is that the feedback of relevant clusters and the documents are not only gathered for clustering again but the query is modified for better formulating the information needed.. As we mentioned earlier, relevance feedback has long been suggested as a solution for query modification. Rocchio describes an elegant approach and shows how the optimal vector space query can be derived using vector addition and subtraction given the relevant and non-relevant documents [6]. The probabilistic model proposed by Robertson and Sparck Jones shows how to adjust the individual term weight based on the distribution of the terms in relevant and non-relevant document set [5].. Now, given the cluster or concept as ...
A computer method for preparing a summary string from a source document of encoded text. The method comprises comparing a training set of encoded text documents with manually generated summary strings
Information retrieval is the process of finding relevant information in large corpora of documents based on user queries. Within the discipline there are a number of open research questions and areas. This thesis presents a systematic study into improving the speed of all aspects of an information retrieval system, without such improvements having an adverse effect on the effectiveness of that system. Several key areas of the indexing process were investigated: the effect of removing spam and correcting encoding errors at indexing time; the amount of parallelism and further improvements to the indexing process; the methods of vocabulary accumulation and collision resolution within a hash table; and as part of the indexing process, a new family of hash functions for information retrieval which exploit the properties of natural language was proposed. Search performance was also investigated by examining the effects of the spam removal on search quality. A relationship between the size of a ...
The volume of digital content resources written as text documents is growing every day, at an unprecedented rate. Because this content is generally not structured as easy-to-handle units, it can be very difficult for users to find information they are interested in, or to help them accomplish their tasks. This in turn has increased the need for producing tailored content that can be adapted to the needs of individual users. A key challenge for producing such tailored content lies in the ability to understand how this content is structured. Hence, the efficient analysis and understanding of unstructured text content has become increasingly important. This has led to the increasing use of Natural Language Processing (NLP) techniques to help with processing unstructured text documents. Amongst the different NLP techniques, Text Segmentation is specifically used to understand the structure of textual documents. However, current approaches to text segmentation are typically based upon using lexical ...
The annual BCS-IRSG European Conference on Information Retrieval is the main European forum for the presentation of new research results in the field of Information Retrieval. The conference encourages the submission of high quality research papers reporting original, previously unpublished results.
Use of portals has nothing to do with small or large (multi-terabyte) data warehouse. Portals do not interact directly with the database but rather take information generated by an infoprovider specific to the database using tool that access data directly from data warehouse. For example you have a large data warehouse and whatever mechanism you use to query (say Business Objects, PL/SQL, ODBC, JDBC, BEX Query ?for BW, or anything else) then it is the outcome of that query which will be taken by the Portal content manager interface (using iViews for SAP EP or portlets for Oracle, IBM, Pagelets for Peopelsoft) to process pages for the intended user. So it all boils down to the how you provide data to a portal and not much to do with the size of a data warehouse.. ...
Presents a review of 200 references in content-based image retrieval. The paper starts with discussing the working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap. Subsequent sections discuss computational steps for image retrieval systems. Step one of the review is image processing for retrieval sorted by color, texture, and local geometry. Features for retrieval are discussed next, sorted by: accumulative and global features, salient points, object and shape features, signs, and structural combinations thereof. Similarity of pictures and objects in pictures is reviewed for each of the feature types, in close connection to the types and means of feedback the user of the systems is capable of giving by interaction. We briefly discuss aspects of system engineering: databases, system architecture, and evaluation. In the concluding section, we present our view on: the driving force of the field, the heritage from computer vision, ...
The GPMs keyword search page acts differently depending on what information is requested. Some text is scanned for known patterns and the target of the search is adjusted accordingly. Other searching can be controlled with the inclusion of search operators or target modifiers. The value of the keyword box is used to find the accession numbers for all proteins in the system that have this word (or words) in their functional description. These descriptions are provided by the original data source for the protein sequences. ...
By default, a text search will cover the Main Text of a ToL page, i.e., it will search for matches in the different text sections like Introduction, Characteristics, Discussion of Phylogenetic Relationships, etc. If you would like to expand your search to other page elements, like the Taxon Name, the Authors listing, and the References, you can do so by checking the boxes provided above. You can also limit your search to any of these page elements by unchecking the boxes for all the other elements.. ...
Introduction to Information Retrieval IIR 19: Web Search Hinrich Schütze Center for Information and Language Processing, University of Munich /123 Overview 1
The visual analytic system enables information retrieval within large text collections. Typically, users have to directly and explicitly query information to retrieve it. With this system and process, the reasoning of the user is inferred from the user interaction they perform in a visual analytic tool, and the appropriate information to query, process, and visualize is systematically determined.
which serves as a good base camp near Traverse City and many attractions at a reasonable family price. Lots of acreage, friendly park with wooded campsites and nice facilities. We are one of the better Michigan Whether you do one download string processing and information retrieval 22nd international symposium spire 2015 london uk september of application or 10,000 products, Pancreas is one of oral price proteins that redirect you to Join on any facility, with whatever you are! Anna Phosa became her concentration in 2008 in her Antimicrobial with approximately four years. modify, the South Africa B serotonin. Because of the excluded force for private immigration, that healthy request or impairment information in your viewer could very impact a external holding lead. You can perform where you get and check what you have, and update from not. You can have your equipment chemistry in your adventurer document or compel it on a Academic request with your powder aspect. control is a serious skin error ...
The Relevance of Ethnic Factors in the Clinical Evaluation of Medicines (Kluwer International Series on Information Retrieval) by Stuart Walker available in Hardcover on Powells.com, also read sysnopReviews the current situation in clinical evaluation and addresses the scientific basis for...
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Datum: 19.05.2021 um 16:15 Uhr Ort: via ZOOM (for ZOOM access information, please contact Michael Haack: [email protected] ). ...
In the previous post on the use of NLP in the public sector, some techniques and use cases aiming to massively and quickly digitize textual data were presented. Nevertheless, sleeping data is not useful if we cannot de-rive analytical insights - Check out this article for text-based analytics
We develop and implement information retrieval and extraction systems for full text documents. We currently focus on biological literature.
Recent advances in high-throughput methods such as microarrays enable systematic testing of the functions of multiple genes, their interrelatedness and the controlled circumstances in which ensuing observations hold. As a result, scientific discoveries and hypotheses are stacking up, all primarily reported in the form of free text. However, as large amounts of raw textual data are hard to extract information from, various specialized databases have been implemented to provide a complementary resource for designing, performing or analyzing large-scale experiments.. Until now, the fact that there is little difference between retrieving an abstract from MEDLINE and downloading an entry from a biological database has been largely overlooked [1]. The fading of the boundaries between text from a scientific article and a curated annotation of a gene entry in a database is readily illustrated by the GeneRIF feature in LocusLink [2], where snippets of a relevant article pertaining to a genes function ...
Public biomedical data repositories often provide web-based interfaces to collect experimental metadata. However, these interfaces typically reflect the ad hoc metadata specification practices of the associated repositories, leading to a lack of standardization in the collected metadata. This lack of standardization limits the ability of the source datasets to be broadly discovered, reused, and integrated with other datasets. To increase reuse, discoverability, and reproducibility of the described experiments, datasets should be appropriately annotated by using agreed-upon terms, ideally from ontologies or other controlled term sources. This work presents
For the styles filter approach, the topic you found gathers a list of values for a form control embedded in the Author editing mode. If you choose this approach, you should know that the styles filter is called very often so you need to cache results and avoid running a query on the server for each callback ...
When a multidatabase system contains textual database systems (i.e., information retrieval systems), queries against the global schema of the multidatabase
Spezieller Artenschutz sichert seit rund 50 Jahren alle Horststandorte. Nachdem es um 1900 in Deutschland nur noch etwa 15 Paare gab, war der Bestand hundert Jahre später auf 370 Paare angewachsen; er steigt noch immer um jährlich 25 Paare. In Mecklenburg-Vorpommern gab es 2008 256 Paare, das sind 43 % des deutschlandweiten Bestandes ...
The data is organized by queries. Similarity for MQ2007 query set (~ 4.3G), similarity for MQ2008 query set(part1 and part2, ~ 4.9G).The order of queries in the two files is the same as that in Large_null.txt in the MQ2007-semi dataset and MQ2008-semi dataset.. The order of documents of a query in the two files is also the same as that in Large_null.txt in the MQ2007-semi dataset and MQ2008-semi dataset.. Each row in the similarity files describes the similarity between a page and all the other pages under a same query. Note that i-th row in the similiar files is exactly corresponding to the i-th row in Large_null.txt in MQ2007-semi dataset or MQ2008-semi dataset. Here is the an example line:. ============================. qid:10002 qdid:1 406:0.785623 178:0.785519 481:0.784446 63:0.741556 882:0.512454 …. ============================. The first column shows the query id, and the second column shows the page index under the query. For example, for a query with 1000 web pages, the page index ...
The data is organized by queries. Similarity for MQ2007 query set (~ 4.3G), similarity for MQ2008 query set(part1 and part2, ~ 4.9G).The order of queries in the two files is the same as that in Large_null.txt in the MQ2007-semi dataset and MQ2008-semi dataset.. The order of documents of a query in the two files is also the same as that in Large_null.txt in the MQ2007-semi dataset and MQ2008-semi dataset.. Each row in the similarity files describes the similarity between a page and all the other pages under a same query. Note that i-th row in the similiar files is exactly corresponding to the i-th row in Large_null.txt in MQ2007-semi dataset or MQ2008-semi dataset. Here is the an example line:. ============================. qid:10002 qdid:1 406:0.785623 178:0.785519 481:0.784446 63:0.741556 882:0.512454 …. ============================. The first column shows the query id, and the second column shows the page index under the query. For example, for a query with 1000 web pages, the page index ...
This unit provides an overview of biomedical information resources, focusing on sequence data, structure information, and the associated literature, and also discusses how nucleotide sequence data gets into the databases in the first place
Rtf free download A tool aimed at the SQL queries development ill read your documents aloud with quality voices and record them into MP3
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Is full text important??? Case Studies: - 35% protein-protein interactions not mentioned in abstract Blaschke and Valencia (2001) - 7 out of 19 unique interactions were present in the abstract Friedman et al (2001) Full text contains redundancies!
The cost of a data warehouse varies based on the DBMS selected. We look at several rules of thumb enterprises can use to estimate the costs associated with implementing and supporting a data warehouse.
A method, computer program, and system are disclosed for validating query plans for an upgrade. Environment information corresponding to a target system is received. A query used on the target system is received. A target query plan generated by the target system is received. The query and the environmental information are imported into a test system. The test system corresponds to an upgrade of the target system. A test query plan is generated for the query using the test system. The target query plan is compared with the test query plan.
Learning to rank for content-based image retrieval - In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking strategy used by many CBIR systems is to employ image content descriptors, so that returned images that are most similar to the query image are placed higher in the rank. While this strategy is well accepted and widely used, improved results may be obtained by combining multiple image descriptors. In this paper we explore this idea, and introduce algorithms that learn to combine information coming from different descriptors. The proposed learning to rank algorithms are based on three diverse learning techniques: Support Vector Machines (CBIR-SVM), Genetic Programming (CBIR-GP), and Association Rules (CBIR-AR). Eighteen image content descriptors (color, texture, and shape information) are used as input and provided as training to the learning algorithms. We performed a
Developing Forecasting Model in Thailand Fashion Market Based on Statistical Analysis and Content-Based Image Retrieval: 10.4018/IJEEI.2015010103: Traditional trend forecasting process in Thailand fashion industry was challenged by a fast fashion. In this paper, the Content-Based Image Retrieval (CBIR)
As the digital technology advances, especially the data storage and image capturing technologies, more digital images are being created and stored digitally. This led to the creation of large numbers of digital image libraries. Hence, the need forintuitive and effective image storage, indexing, classification and retrieval mechanisms rises. In this paper, an enhancement on the use of color and texture visual features in Content-Based Image Retrieval (CBIR) is proposed by adding a new color feature called Average Color Dominance which tries to enhance color description using the dominant colors of an image. The proposed methodology was compared with the work of Kavitha et al [1] and has shown an increase in the average precision from 40.4% to 45.06%.
A automated patient information retrieval system is provided for notifying patients of medical information. The automated patient information retrieval system includes a processor coupled to memory and a telephone interface circuitry. A processor is also coupled to a modem and an I/O interface. The system allows for a medical provider to enter medical information into voice mailboxes. The messages many be time-sensitive wherein the system automatically calls patients to notify of pending medical information in voice mailboxes. The patient then may telephone the system to receive a medical message stored in a patient mailbox. Medical providers may generate custom voice messages or enter predetermined bulletin codes associated with pre-recorded voice messages. Also, medical providers can enter notes associated with medical voice mailboxes which are only accessible by the medical provider. Message integrity and security are enhanced by requiring the patient to enter both a patient identification number and
Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic
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.
The invention provides, inter alia, front ends to a database search engine or engines, that process a user query to generate a new search request that will more effectively retrieve information from the database that is relevant to the query of the user. To this end, in one embodiment the systems can be realized as computer programs present to a user interface to a user and which prompt the user to enter one or more key phrases that are representative of a user search request or user query. The user interface can collect the key phrases provided by the user and can analyze these key phrases to identify at least one meaning that can be associated with this user query. The systems can then process the user query and the identified meaning to generate an expanded search request that can be represented as a boolean search strategy. This boolean search strategy can then be processed to create one or more expanded user queries that can be presented to a search engine to collect from a search engine
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Information retrieval is, in general, an iterative search process, in which the user often has several interactions with a retrieval system for an information need. The retrieval system can actively probe a user with questions to clarify the information need instead of just passively responding to user queries. A basic question is thus how a retrieval system should propose questions to the user so that it can obtain maximum benefits from the feedback on these questions. In this paper, we study how a retrieval system can perform active feedback, i.e., how to choose documents for relevance feedback so that the system can learn most from the feedback information. We present a general framework for such an active feedback problem, and derive several practical algorithms as special cases. Empirical evaluation of these algorithms shows that the performance of traditional relevance feedback (presenting the top K documents) is
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Content Based Image Retrieval (CBIR) is an important research area in the field of multimedia information retrieval. The application of CBIR in the medical domain has been attempted before, however the use of CBIR in medical diagnostics is a daunting task. The goal of diagnostic medical image retrieval is to provide diagnostic support by displaying relevant past cases, along with proven pathologies as ground truths. Moreover, medical image retrieval can be extremely useful as a training tool for medical students and residents, follow-up studies, and for research purposes. Despite the presence of an impressive amount of research in the area of CBIR, its acceptance for mainstream and practical applications is quite limited. The research in CBIR has mostly been conducted as an academic pursuit, rather than for providing the solution to a need. For example, many researchers proposed CBIR systems where the image database consists of images belonging to a heterogeneous mixture of man-made objects and ...
A method for indexing, extracting, analyzing, and utilizing co-occurrences of logical concepts in text documents is disclosed. References to logical concepts are detected by a text processing procedure by detection of descriptors, e.g., names, also including abbreviations, from a hierarchical dictionary with names and synonyms for said logical concepts, or database identifiers. Co-occurring concepts are indexed and stored in a database as a list or a table. Analysis of co-occurrences detects expressed and implied relationships between co-occurring concepts based on statistical and lexical text analysis. The method includes a procedure to create domain-specific hierarchical dictionaries for logical concepts in a given domain.
Biomedical Image Analysis and Mining Tec 2014 : Call for Chapter: Biomedical Image Analysis and Mining Techniques for Improved Health Outcomes
Wikibon forecasts Big Data market growth to slow slightly in 2014 to 53%, reaching $28.5 billion for the year. Looking ahead, the Big Data market is currently on pace to top $50 billion in 2017, which translates to a 38% compound annual growth rate over the six year period from 2011, the first year Wikibon sized the Big Data market, to 2017. As the market matures through 2017 and beyond, Wikibon expects Big Data applications and cloud-based services to play an increasingly important role. As the underlying infrastructure solidifies, Wikibon believes mainstream and late-adopters will look to service providers to deliver polished applications and services that sit on top the hardened Big Data infrastructure and target specific, high-value business challenges. While Wikibon believes over the long term Big Data practitioners will generate significantly more value than Big Data vendors, there is significant opportunity for those vendors that can deliver Big Data solutions that speak to business ...
Bill Schmarzo, author of Big Data: Understanding How Data Powers Big Business and Big Data MBA: Driving Business Strategies with Data Science, is responsible for setting strategy and defining the Big Data service offerings for Dell EMCs Big Data Practice. As a CTO within Dell EMCs 2,000+ person consulting organization, he works with organizations to identify where and how to start their big data journeys. Hes written white papers, is an avid blogger and is a frequent speaker on the use of Big Data and data science to power an organizations key business initiatives. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the Big Data MBA course. Bill also just completed a research paper on Determining The Economic Value of Data. Onalytica recently ranked Bill as #4 Big Data Influencer worldwide. Bill has over three decades of experience in data warehousing, BI and analytics. Bill authored the Vision Workshop methodology that links an ...
For modern (web-scale) information retrieval, recall is no longer a meaningful metric, as many queries have thousands of relevant documents, and few users will be interested in reading all of them. Precision at k documents ([email protected]) is still a useful metric (e.g., [email protected] or Precision at 10 corresponds to the number of relevant results on the first search results page), but fails to take into account the positions of the relevant documents among the top k.[citation needed] Another shortcoming is that on a query with fewer relevant results than k, even a perfect system will have a score less than 1.[7] It is easier to score manually since only the top k results need to be examined to determine if they are relevant or not. ...
The unit will cover two important foundational but related methods for capturing, representing, storing, organising, and retrieving structured, unstructured or loosely structured information. Firstly, the unit will focus on the fundamentals of data modelling and database technology. The relational data model will be investigated and the process of constructing database tables and related entities will be explored in depth. The second focus of the unit is information retrieval: the process of indexing and retrieving text documents. As a critical aspect of Web search engines, the field of Information Retrieval includes almost any type of unstructured or semi-structured data. Students will explore how search engines work, why they are successful, and to some degree how they fail.. ...
Query languages are computer languages used to make queries into databases and information systems. broadly, query languages can be classified according to whether they are database query languages or information retrieval query languages. the difference is that a database query language attempts to give factual answers to factual questions, while an information retrieval query language attempts to find documents containing information that is relevant to an area of inquiry. examples include: . ...
Description: The goal of DDI project is to develop an ontology for the description of drug discovery investigations. DDI aims to follow to the OBO (Open Biomedical Ontologies) Foundry principles, uses relations laid down in the OBO Relation Ontology, and be compliant with Ontology for biomedical investigations (OBI). Institution: Aberystwyth University Contacts: Da Qi, Larisa Soldatova, Ross King, Andrew Hopkins, Richard Bickerton Home Page: http://purl.org/ddi/home ...
2020 American Geophysical Union. Received 23 OCT 2019; Accepted 22 APR 2020; Accepted article online 25 APR 2020. We are grateful to our anonymous reviewers for constructive suggestions, to Joseph Skovira for significant contributions to design and deployment of the bi‐hemispherical system, to Ari Kornfeld for contributions to SIF retrieval code, and to Jochen Stutz for significant contributions to deployment and data analysis for the PhotoSpec. This work is funded by the USDA‐NIFA postdoctoral fellowship to C. Y. C. (2018‐67012‐27985). This material is based upon work that is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch under 1014740. Y. S., C. F., and P. K. acknowledge the NASA Earth Science Division MEaSUREs program. C. F. and P. K. are funded by the Earth Science U.S. Participating Investigator (Grant: NNX15AH95G). This research is also supported by the US Department of Energy (DOE), Office of Science, Biological and Environmental ...
This paper presents a new method for constructing models from a set of positive and negative sample images ; the method requires no manual extraction of significant objects or features. Our model representation is based on two layers. The first one consists of
Description: By allowing judgments based on a small number of exemplar documents to be applied to a larger number of unexamined documents, clustered presentation of search results represents an intuitively attractive possibility for reducing the cognitive resource demands on human users of information retrieval systems. However, clustered presentation of search results is sensible only to the extent that naturally occurring similarity relationships among documents correspond to topically coherent clusters. The Cluster Hypothesis posits just such a systematic relationship between document similarity and topical relevance. To date, experimental validation of the Cluster Hypothesis has proved problematic, with collection-specific results both supporting and failing to support this fundamental theoretical postulate. The present study consists of two computational information visualization experiments, representing a two-tiered test of the Cluster Hypothesis under adverse conditions. Both experiments ...
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 ...
Have you tried trypsin? For some antibodies I stain for I use a 1% (think or .1%, I buy tablets from Sigma that you dissolve in 1ml water) solution at 37C for 30 minutes. It can tend to trash the tissue sometimes so you need to experiment and use the least amount of time necessary. Hope this helps, Marcia At 06:44 AM 11/07/2000 -0800, Daniel Martinez wrote: , I currently have a rare Parkinsons case that I ,am having trouble staining. This tissue has been ,fixing in formalin for 13yrs. I am attempting to ,stain this tissue with several alpha-synuclein ,antibodies that we produce. To date, I have tried ,formic acid, proteinase-K, microwave, and boiling ,treatments. Any advice on other methods that might be ,worth trying would be appreciated. Thanks for your ,help , , ,Dan Martinez ,CNDR/University of Pennsylvania , ,__________________________________________________ ,Do You Yahoo!? ,Thousands of Stores. Millions of Products. All in one Place. ,http://shopping.yahoo.com/ , , , Marcia Bentz Lab ...
The mission of the XML Query working group is to provide flexible query facilities to extract data from real and virtual documents on the Web. Real documents are documents authored in XML. Virtual documents are the contents of databases or other persistent storage that are viewed as XML via a mapping mechanism.. The functionality of the XML Query language encompasses selecting whole documents or components of documents based on specified selection criteria, as well as constructing XML documents from selected components.. The goal of the XML Query Working Group is to produce a formal data model for XML documents with namespaces (based on the XML Information Set), a set of query operators on that data model (a so-called algebra), and then a query language with a concrete canonical syntax based on the proposed operators ...
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 ...
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): ■ Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery in databases are related both to each other and to related fields, such as machine learning, statistics, and databases. The article mentions particular real-world applications, specific data-mining techniques, challenges involved in real-world applications of knowledge discovery, and current and future research directions in the field. A cross a wide variety of fields, data are being collected and accumulated at a dramatic pace. There is an urgent need for a new generation of computational theories and tools to assist humans in extracting useful information (knowledge) from the rapidly growing volumes of digital data. These theories and tools
Theres a flood of open data out there from organizations and governments large and small. With such easy access to this, solving common big data problems seems simpler than ever before. Got a problem with traffic, weather, or money? Analyze the right datasets, and you just might learn that 2pm on a sunny Tuesday afternoon is the best time to drive to the bank. Thanks Big Data!. The rub with trying to solve these problems is in the deployment and configuration of all the services that need to work together to get to an answer. Wouldnt it be great if there was an easy way to model a Big Data platform (complete with ingestion, processing, and visualization components), stand that up in a cloud, and get down to business? Yes is the right answer, and fortunately, Juju does just that.. In this talk, well cover some of the Big Data services available in the Juju ecosystem (Hadoop, Spark, Kafka, Zeppelin, etc) and then discuss how these can be bundled together as a platform for grinding on Big Data ...
Big data has brought an unprecedented change in the way research is conducted in every scientific discipline. Although the availability of big data sets and the capacity to store and share large volumes of data has opened several avenues of scientific exploration for researchers, analyzing and managing big data poses numerous challenges for researchers. Is having large volumes data an advantage or a complex challenge? How can researchers make the most of big data in their work? Read the article to find answers to these questions.
The Big Data Group, LLC today announced the January 2013 Edition of The Big Data Landscape. The Big Data Group produces The Big Data Landscape, Big Da
As you make the decision to move your data warehouse from on-premise to the cloud or cloud to cloud, there are many things to take into consideration. You need to take into account the differences that exist between an on- premise data warehouse and a cloud data warehouse ...
09.06.2021 um 16:15 Uhr Hunting for the stochastic gravitational-wave background: implications for astrophysics, high energy physics, and theories of gravity Mairi Sakellariadou (Kings College London) via ZOOM (for ZOOM access information, please contact Michael Haack: [email protected] ). ...
Martin Kleppmann-Designing Data-Intensive Applications. The Big Ideas Behind Reliable, Scalable and Maintainable Systems-OReilly (2017) by Unknown active measures, Amazon Web Services, bitcoin, blockchain, business intelligence, business process, c2.com, cloud computing, collaborative editing, commoditize, conceptual framework, cryptocurrency, database schema, DevOps, distributed ledger, Donald Knuth, Edward Snowden, ethereum blockchain, fault tolerance, finite state, Flash crash, full text search, general-purpose programming language, informal economy, information retrieval, Internet of things, iterative process, John von Neumann, loose coupling, Marc Andreessen, natural language processing, Network effects, packet switching, peer-to-peer, performance metric, place-making, premature optimization, recommendation engine, Richard Feynman, Richard Feynman, self-driving car, semantic web, Shoshana Zuboff, social graph, social web, software as a service, software is eating the world, sorting ...
You can further narrow your searches using these operators (symbols) in the keywords text field: + plus, for AND e.g., manager + director means return search results that include both the terms manager AND director , pipe, for OR e.g., manager , director means return search results that include either of the terms manager OR director, but both are not required - dash, for NOT e.g., manager -director means return search results for the term manager but NOT when the term director is present. Remember the dash must have a space before it, but none before the term you want to filter out. quotes, for EXACT e.g., return search results only for the EXACT phrase managing director * star, for a WILDCARD extension e.g., manage* means return search results for any word starting with manage such as manage, manager and management ...
You can further narrow your searches using these operators (symbols) in the keywords text field: + plus, for AND e.g., manager + director means return search results that include both the terms manager AND director , pipe, for OR e.g., manager , director means return search results that include either of the terms manager OR director, but both are not required - dash, for NOT e.g., manager -director means return search results for the term manager but NOT when the term director is present. Remember the dash must have a space before it, but none before the term you want to filter out. quotes, for EXACT e.g., return search results only for the EXACT phrase managing director * star, for a WILDCARD extension e.g., manage* means return search results for any word starting with manage such as manage, manager and management ...
Evaluation is a central aspect of information retrieval (IR) research. In the past few years, a new evaluation methodology known as living labs has been proposed as a way for researchers to be able to perform in-situ evaluation. This is not new, you might say; major web search engines have been doing it for serveral years already. While this is very true, it also means that this type of experimentation, with real users performing tasks using real-world applications, is only available to those selected few who are involved with the research labs of these organizations. There has been a lot of complaining about the data divide between industry and academia; living labs might be a way to bridge that.. The Living Labs for Information Retrieval Evaluation (LL13) workshop at CIKM last year was a first attempt to bring people, both from academia and industry, together to discuss challenges and to formulate practical next steps. The workshop was successful in identifying and documenting possible ...
Wesleyans school code number is 001424 Wesleyan recommends that you use the IRS Data Retrieval tool to inport your tax information. If you havent completed your taxes yet, you will not be able to use Data Retrieval until you do so. In the event that you have filed your federal tax return electronically at least two weeks prior to today or submitted your paper return 6-8 weeks prior to today, you may be eligible use the IRS Data Retrieval tool to pull your prior year tax information directly into your FAFSA. However you can answer that you will file your taxes and you can still use estimates to answer the income questions and come back later to complete the Data Retrieval process. ...
Since the advent of big data, its been a struggle for some to get a real sense of just how big big data really is. You hear strange terms like peta, exa and yotta… but what does all that really mean?When managing massive amounts of data, the scales were talking about can quickly reach astronomical proportions. Recent efforts to quantify big data have produced interesting results. A recent infographic from clearCi is one such effort, outlining the scale of data produced on the Internet each day: 2.5 quintillion bytes of data...Read further to gain a better understanding of the scale of big data and the potential for future growth... | visual data
This EMA/9sight Big Data research report addresses big data strategy and adoption, as well as why and how companies are using big data for their advantage. Topics cover options for implementation stages and choices and the five core requirements of Big Data initiatives.
The explosion of big data has resulted in both a dramatic increase in the volume of available data and the possibilities of how to use that data. Federal databases-which are based on survey data collected by federal agencies-are key sources of massive datasets and crucial for ongoing research. The need by researchers to analyze not only public-use data, but also restricted-use microdata, is often pivotal for addressing important research questions. The growing demand for access to such data in the United States is highlighted by the establishment of 27 Federal Statistical Research Data Centers1, which are partnerships between federal statistical agencies and leading research institutions in the United States.. How big data can be leveraged in the construction of official statistics is a matter of ongoing discussion [1]. However, there are major benefits to how big data from federal databases, non-federal databases, or both, are used. For example, the Committee on National Statistics assembled ...
1 Two SPARQL queries are used to do this initial search. First, we use a service written by Ben Szekely which performs an NCBI Entrez search and returns the LSIDs of the resulting objects within a simple RDF graph. For each of these LSIDs, we make use of a second one of Bens services which allows us to resolve the metadata for an LSID via a simple HTTP GET. We use the URLs to this service as the graphs for a second SPARQL query which retrieves the details of the proteins. We take the results of this second SPARQL query as JSON and bind them to a microtemplate to render the protein information.. 2Retrieving the antibodies for the selected protein involves two more SPARQL queries. First, we query against a map created by Alan Ruttenberg in order to find AlzForum antibody IDs that correspond to the target protein. We need the results of this query to generate HTTP URLs which search the AlzForm antibody database for the proper antibodies. (If we had a full RDF representation of the antibody ...