'Relevance ranking' diaporamas de présentation

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Unbundling the ILS @ NCSU: implementation of an e-commerce search solution

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Relevance Ranking in the Scholarly Domain

Relevance Ranking in the Scholarly Domain. Dr. Tamar Sadeh LIBER Conference Tartu, Estonia, June 2012. The top three keys for success. 1. 2. 3. Content. 1. Speed. 2. Relevance Ranking. 3.

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Implementing a Faceted Search Framework

Implementing a Faceted Search Framework. Emily Lynema & Andrew K. Pace NC State University Libraries ASIS&T Seminar April 9, 2007. Agenda. The Context: Problem & motivation Local Implementation What and How? Challenges Encountered Outcomes Usage Statistics Future Opportunities.

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White list Black list

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What difference a good tool? using Endeca for a faceted catalog

What difference a good tool? using Endeca for a faceted catalog. Emily Lynema NCSU Libraries ACRL Delaware Valley Chapter Fall Program November 3, 2006. Agenda. The Context: Next Gen Search Tools vs. OPAC Problems Local Implementation Why, What and How? Assessment Usage Statistics

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What difference a good tool? using Endeca for a faceted catalog

What difference a good tool? using Endeca for a faceted catalog. Emily Lynema NCSU Libraries ACRL Delaware Valley Chapter Fall Program November 3, 2006. Agenda. The Context: Next Gen Search Tools vs. OPAC Problems Local Implementation Why, What and How? Assessment Usage Statistics

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Geographical Web Search Engines and Geographical Information Retrieval (GIR)

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Towards Practical Relevance Ranking for 10 Million Books

Towards Practical Relevance Ranking for 10 Million Books. w www.hathitrust.org ww.hathitrust.org. Tom Burton-West Information Retrieval Programmer Digital Library Production Service University of Michigan Library www.hathitrust.org/blogs/large-scale-search Code4lib February 12, 2013.

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IS530 Lesson 12 Boolean vs. Statistical Retrieval Systems

IS530 Lesson 12 Boolean vs. Statistical Retrieval Systems. Boolean or Statistical?. Most web search engines default to statistical, use Boolean for advanced Most proprietary online systems default to Boolean, use statistical for alternative

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Alternative & Customized Search Engines

Alternative & Customized Search Engines. Mary Ellen Bates Bates Information Services mbates@BatesInfo.com. What we'll cover:. Beyond the Big 3.5 Specialized search tools DIY search engines. Beyond the Big 3.5. Exalead. Great advanced search tools Excellent tool for complex searching

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History of Internet Searching

History of Internet Searching. The Internet. Built in 1969. Funded by the DoD for scientific research, built by BBN Technologies. Originally called ARPANET A dvanced R esearch P rojects A gency First nodes (connections) were at universities (UCLA, UCSB, Stanford, Univ. of Utah).

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A Generation Model to Unify Topic Relevance and Lexicon-based Sentiment for Opinion Retrieval

A Generation Model to Unify Topic Relevance and Lexicon-based Sentiment for Opinion Retrieval. Min Zhang, Xinyao Ye Tsinghua University SIGIR 2008 2009. 01. 14. Summarized & presented by Jung-Yeon Yang IDS Lab. Introduction.

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Session 7: Early Case Assessment

Session 7: Early Case Assessment. LBSC 708X/INFM 718X Seminar on E-Discovery Jason R. Baron Adjunct Faculty University of Maryland March 8, 2012. How much does counsel know?. About the nature and scope of the relevant evidence existing in custody and control of the opposing party?

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XQuery Processing with Relevance Ranking

Leonidas Fegaras University of Texas at Arlington fegaras@cse.uta.edu http://lambda.uta.edu/. XQuery Processing with Relevance Ranking. Motivation. Many IR techniques for approximate matching over text-rich documents keyword search queries over flat documents only ranked results

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Relevance Ranking and Clustering

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Collection Fusion

Collection Fusion. -Parallel Retrieval on Different Information Sources (e.g. Different Search Engines, or different collections) -Merger of results. MetaCrawler - University of Washington (Selberg + Etzioni,1995) Towell + Vorhees. Collection Fusion.

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IDS Search

Mike Curtis Systems Librarian Broome Community College curtis_m@sunybroome.edu 607-778-5609. IDS Search. IDS Search. Situation/Problem/Opportunity:

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State of the Art: Federated Search Engines

State of the Art: Federated Search Engines. ICOLC April 13, 2005. Federated Search hype, circa 2003. The correct solution for unifying access to a variety of information resources. - Roy Tennant, Library Journal, 6/15/2003

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BAH DAML Tools

BAH DAML Tools. XML To DAML Query Relevance Assessor DAML XSLT Adapter. XML To DAML. The high level tasks in order are XML Schema to DAML - current task XML DTD to DAML - via XML Spy as a preprocessor XML Content to DAML - dependent on the language map XML Schema to DAML Accomplishments

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