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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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Software systems that operate in an international environment often must support multilingual data models. For example, users of a procurement system must be able to describe the products they want to buy in many languages because they want to receive offers from suppliers that reside in different countries. Designing a system that can effectively display data in a given users language and also allow him to do full text searches is a challenge - many commonly used patterns will have a high performance penalty and slow down your system. In this first of a series of articles we will describe how Postgres supports full text search in general and what are the most common anti-patterns for multilingual SQL models.
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 textual data format is one in which the data is specified as a sequence of characters. HTML, Internet e-mail, and all XML-based formats are textual. In modern textual data formats, the characters are usually taken from the Unicode repertoire [UNICODE].. Binary data formats are those in which portions of the data are encoded for direct use by computer processors, for example thirty-two bit little-endian twos-complement and sixty-four bit IEEE double-precision floating-point. The portions of data so represented include numeric values, pointers, and compressed data of all sorts.. In principle, all data can be represented using textual formats.. The trade-offs between binary and textual data formats are complex and application-dependent. Binary formats can be substantially more compact, particularly for complex pointer-rich data structures. Also, they can be consumed more rapidly by agents in those cases where they can be loaded into memory and used with little or no conversion.. Textual formats ...
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 ...
T-sql (188) stored procedure (16) index (15) SSIS (13) USER DEFINE FUNCTION (9) c# (9) audit trail (7) encryption (7) trigger (7) asp.net (6) BCP (5) CREATE TRIGGER (5) Full Text Search (5) OUTPUT (5) UDF (5) decryption (5) experts-exchange.com (5) information_schema.columns (5) sp_MSforeachtable (5) ALTER TRIGGER (4) cte (4) cursor (4) linked server (4) xml (4) CROSS APPLY (3) Contains (3) DMK (3) Inner Join (3) PIVOT (3) XP_CMDSHELL (3) aggregate function (3) bcp.exe (3) bulk insert (3) coalesce (3) dateadd (3) dynamic pivot (3) error fix (3) identity (3) instead of trigger (3) subquery (3) t-sq (3) teched event in Ahmedabad (3) view (3) Asymmetric (2) DELETED (2) FreeText (2) HTTP Endpoint (2) INFORMATION_SCHEMA.tables (2) INSERTED (2) Microsoft.ACE.OLEDB.12.0 (2) OPENROWSET (2) OUTER APPLY (2) OUTPUT Parameter (2) PSEUDO TABLE (2) RANK() (2) Read Committed Isolation Level (2) Read UnCommitted Isolation Level (2) SMK (2) SNAPSHOT ISOLATION (2) SPLIT (2) Serializable Isolation Level (2) ...
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.
In this article, we will discuss the basic concepts of Information Retrieval along with some of the models used in Information Retrieval
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
A business needs to have a powerful business tool that helps to manage all the information from previous up to the present. In this way, it helps business to build a strong marketing strategy and even decision making. Yes, decision making plays an important role in a business. So, all of the mentioned above is very important when talking about business. It is true that a business is not easy to handle and manage. Either small or big businesses, both are hard to manage especially if not equipped with the said data warehouse application. Now, to understand more and learn about a data warehouse. Below information will serve as the hero to save a business from a failure to success. Does it make sense? A serious and dedicated business owner should apply this advanced tool.. What is data warehouse?. If you want to get all the information about the business, then you should apply several techniques of maintaining, designing, retrieving and building data. Now, data warehousing will be the ideal and wise ...
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...
Ranking attempts to measure how relevant documents are to a particular query, so that when there are many matches the most relevant ones can be shown first. Greenplum Database provides two predefined ranking functions, which take into account lexical, proximity, and structural information; that is, they consider how often the query terms appear in the document, how close together the terms are in the document, and how important is the part of the document where they occur. However, the concept of relevancy is vague and very application-specific. Different applications might require additional information for ranking, e.g., document modification time. The built-in ranking functions are only examples. You can write your own ranking functions and/or combine their results with additional factors to fit your specific needs.. The two ranking functions currently available are:. ...
The Nationwide Access Register provides access information (including wheelchair access) for disabled people and accessibility details for parents with pushchairs.
Datum: 19.05.2021 um 16:15 Uhr Ort: via ZOOM (for ZOOM access information, please contact Michael Haack: [email protected] ). ...
With the release of version 5.0, Alfresco officially stopped supporting the Lucene indexing subsystem, leaving Solr as Alfrescos lone indexing solution. A major benefit of leveraging Lucene was its in-transaction indexing, making content searchable as soon as it was created. Solr, however, utilizes asynchronous indexing which leads to eventual consistency, meaning newly created content is not searchable right away. This poses problems when building solutions for clients that need a high-velocity system capable of ingesting and then quickly presenting newly created content from Alfresco to end users. Luckily, Alfresco has a solution: Enter Transactional Metadata Query.. What is a Transactional Metadata Query?. With the release of version 4.2, Alfresco began supporting a system called Transactional Metadata Query. This system allows particular CMIS and FTS language queries to be run directly against database indexes instead of the Solr index. Having CMIS and FTS queries run directly against the ...
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
Metadata may be retrieved in JSON format using our REST API, or in XML format as documented below. Most DOI-to-metadata queries are done via HTTPS using synchronous HTTPS queries, but may also be submitted as asynchronous batch queries. Example HTTPS query https://doi.crossref.org/servlet/query?pid={[email protected]}&format=unixref&id=DOI OpenURL query We support DOI queries formatted as OpenURL version 0.1 requests. For complete metadata (UNIXREF) include the format=unixref parameter. https://www.crossref.org/openurl/?pid={[email protected]}&format=unixref&id=doi:10.1577/H02-043&noredirect=true Query results: xsd_xml format (default) |crossref_result version=2.0 xsi:schemaLocation=https://www.
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
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To calculate the final video similarity, we apply the hard tanh activation function on the values of the network output, which clips values within range [-1, 1]. Finally, we apply Chamfer Similarity to derive a single value, which is considered as the final similarity between the two videos.. Experimental results. For the evaluation of the proposed approach, we employ two datasets compiled for fine-grained incident and near-duplicate video retrieval, i.e., FIVR-200K and SVD. We have manually annotated the videos in the dataset according to their audio duplicity with the set of query videos. Also, we evaluate the robustness of our approach to audio speed transformations by artificially generating audio duplicates.. In the following table, we compare the retrieval performance of AuSiL against Dejavu, a publicly available Shazam-like system. The performance is measured based on mean Average Precision (mAP) on the two annotated datasets with two different settings, i.e., the original version and the ...
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
This area of the site gives access to a range of online information resources for HSE employees and other healthcare workers. Choose from the options on the left of this page to read more.. ...
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 ...
The Big Data Challenge and Opportunity. The challenge for businesses trying to manage and analyze Big Data is that traditional data management tools do not work well with Big Data.. In general, the traditional way of handling data is with a relational database for on-line transaction processing, and a separate data warehouse and business intelligence tools for analytics, which provides processing relief from the main database. Large relational databases tend to be expensive propositions, as the costs of the processing units and the disks are very high.. Relational databases are based on whats called early structure binding. What this means is that you have to know what questions are going to be asked to the database so that you can design the schema, tables and relations. With big data, this assumption is often not correct.. Types of Big Data. Unlike transactional data, the analysis of big data is much less predictable. Big data is often either (1) various types of online data (text, images, ...
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. ...
SOUTH BEND, Ind., Sept. 13, 2021 - Aunalytics, a leading data platform company delivering Insights-as-a-Service for enterprise businesses, will present a new paper to be showcased at the ECML-PKDD 2021 Virtual Event, taking place online, September 13-17. During the event, David Cieslak, Chief Data Scientist for Aunalytics, will discuss the use of natural language interface synthesis of SQL database queries leveraging the companys new NL2SQL System.. Natural language interface integration with database environments is a growing field that enables end users to interact with relational databases without technical database skills. These interfaces solve the problem of synthesizing SQL queries based on natural language input from the user. There are considerable research interests around the topic but there are few systems to date that are deployed on top of active enterprise data marts.. At ECML-PKDD 2021, Aunalytics will introduce the NL2SQL system and present on data simulations that provide ...
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: . ...
Information retrieval and access have become central technologies for managing and leveraging the ongoing explosion of digital content. While effective, current techniques for designing retrieval models are limited by two issues. First, they have restricted representational power, and generally deal with simple settings that estimate the quality of individual results independently of other results. Second, existing methodologies for designing retrieval functions are labor intensive and cannot be efficiently applied to accommodate a growing variety of retrieval domains.. In this talk, I will describe two learning approaches for designing new retrieval models. The first is a structured prediction approach, which considers inter-dependencies between results in order to optimize for more sophisticated objectives such as information diversity. The second is an interactive learning approach, which reduces the efficiency bottleneck of relying on human experts by leveraging data gathered from online ...
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 ...
Unstructured Data, on the other hand, is much harder to … comes from: ITPUB. ... We find that a big data solution is a technology and that data warehousing is an architecture. Since Big Data, AI, and ML are already impacting the Defense industrys future, the potential for delivering true All Source intelligence in a timely manner is within grasp. Big Data technologies can be used for creating a staging area or landing zone for new data before identifying what data should be moved to the data warehouse. A few years ago, Apache Hadoop was the popular technology used to handle big data. Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. It has been designed to ...
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 ...
Find helpful learner reviews, feedback, and ratings for Big Data Integration and Processing from Universidade da Califórnia, San Diego. Read stories and highlights from Coursera learners who completed Big Data Integration and Processing and wanted to share their experience. Hello Gentlemen,\n\nThis course was very helpful foe me. It enhanced my knowledge about Big Data Int...
The Office of the City Clerk keeps the records of the City Council and makes them available to the public. We also receive and maintain many different types of documents that must, by law or as a result of legislation, be filed with us. The databases contain full text or scanned copies of many of these documents, and descriptions of others along with information about how to get copies.
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.
DATA WAREHOUSES OFFER AN EXCELLENT WAY TO CLEAN UP AND STORE YOUR DATA IN A WAY THAT CAN BE EASILY SEARCHED AND ORGANIZED. THATS WHAT THEY ARE FOR.. The important thing to understand, though, is that this is all they are for. They dont have any analytical function, so you need that on top. The fact that data warehouses are so good at tidying up your data can also be a drawback. This is because they are relational databases, which makes them highly restrictive in terms of the kind of data you can store and how you store it.. You only have a certain number of columns and ways to sort and identify each item, so anything that doesnt fit neatly into this poses a challenge-for example, photo or video content, language analysis, and so on. It also means that data warehouses only store past/historical data, also referred to as analytical data. You cant store current real-time (i.e. transactional) data.. This limits the kind of insights you can get out of the data stored in your warehouse, even with ...
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 ...
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Information Retrieval (cs.IR); Machine Learning (cs.LG ...
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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 ...