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Data retrieval
Results: 1828

#	Item
381	eDiscovery Services Experience when and where it matters most The increasing complexity of global eDiscovery can challenge even the most sophisticated organizations. Beyond the explosion of electronically stored data, le Add to Reading List Source URL: www.consilio.com Language: English - Date: 2013-06-10 17:33:28 Workflow Information Science Information retrieval Concept Search Electronic discovery
382	Clustering Top-Ranking Sentences for Information Access Anastasios Tombros1 , Joemon M. Jose1 , and Ian Ruthven2 1 Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, U.K. Add to Reading List Source URL: www.dcs.gla.ac.uk Language: English - Date: 2008-01-06 06:19:52 Natural language processing Document clustering Relevance Full text search Data mining Cluster analysis Web query classification Information science Information retrieval Science
383	Gaining insights into the Global Financial Crisis using Saffron Georgeta Bordea Kartik Asooja Paul Buitelaar INSIGHT Centre for Data Analytics Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2014-06-19 09:18:54 Natural language processing Computational linguistics Relevance Text Retrieval Conference Information extraction Financial Crisis Inquiry Commission Late-2000s financial crisis Enterprise search Lucene Information science Information retrieval Science
384	The SDQL Manual for the NFL Updated for 2010 “Study the past, if you would divine the future.” Add to Reading List Source URL: killersports.com Language: English - Date: 2014-07-13 20:47:38 Information retrieval Database management systems Internet search Sports data Information science SQL
385	Personalized Concept-based Search and Exploration on the Web of Data using Results Categorization Melike Sah and Vincent Wade Centre for Next Generation Localisation, KDEG, Trinity College Dublin, Dublin, Ireland {Melike Add to Reading List Source URL: eswc-conferences.org Language: English - Date: 2015-05-13 12:33:38 Personalization Semantic search Query expansion Semantic similarity Relevance Linked data Google Search Information science Information retrieval Personalized search
386	Identifying Gene Function Descriptions by Probability-based Sentence Selection Kazuhiro Seki, Nihar Sheth, and Javed Mostafa Laboratory for Applied Informatics Research, Indiana University 1320 East Tenth Street, LI 011, Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2004-02-12 14:07:10 Computational linguistics Information retrieval Speech recognition Automatic summarization Data mining Stemming Language model Sentence Dice Linguistics Science Natural language processing
387	Collaborative Prediction and Ranking with Non-Random Missing Data Benjamin M. Marlin Richard S. Zemel Add to Reading List Source URL: people.cs.ubc.ca Language: English - Date: 2009-08-17 20:00:28 Estimation theory Statistical theory Statistical models Collaborative filtering Recommender system Regression analysis Mixture model Expectation–maximization algorithm Cross-validation Statistics Machine learning Information retrieval
388	Towards Scalable Real-Time Entity Resolution using a Similarity-Aware Inverted Index Approach Peter Christen1 Ross Gayler2 Add to Reading List Source URL: cs.anu.edu.au Language: English - Date: 2008-09-26 00:12:14 Data management Database management systems Information retrieval Search algorithms Searching Record linkage Database index Inverted index Extensible Storage Engine Information science Information Data
389	The JAVELIN Question-Answering System at TREC 2003: A Multi-Strategy Approach with Dynamic Planning E. Nyberg, T. Mitamura, J. Callan, J. Carbonell, R. Frederking, K. Collins-Thompson, L. Hiyakumoto, Y. Huang, C. Huttenh Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2004-06-09 16:11:08 Computational linguistics Natural language processing Linguistics Artificial intelligence applications Question answering Open domain question answering Data collection QA Question Information science Science Information retrieval
390	Measuring the Similarity between Implicit Semantic Relations using Web Search Engines Danushka Bollegala∗ The University of Tokyo Hongo 7-3-1, Tokyo, Japan Add to Reading List Source URL: www.wsdm2009.org Language: English - Date: 2009-04-14 09:41:39 Statistics Lexical semantics Semantics Information retrieval Data mining Semantic similarity Cluster analysis WordNet Analogy Linguistics Computational linguistics Science

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