NIST

Results: 18894



#Item
881Learning to rank / Query expansion / Text Retrieval Conference / Google Search / Document retrieval / Discounted cumulative gain / N-gram / Language model / Relevance feedback / Information science / Information retrieval / Science

The University of Amsterdam at the TREC 2011 Session Track Bouke Huurnink Richard Berendsen Edgar Meij

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Source URL: trec.nist.gov

Language: English - Date: 2012-02-03 09:41:34
882Computational linguistics / Natural language processing / Internet search engines / Text messaging / Twitter / Query expansion / Text Retrieval Conference / WordNet / Google Search / Information science / Science / Information retrieval

10 Weeks to TREC: STIRS Sienaʼs Twitter Information Retrieval System Sharon Gower Small, Darren Lim, Karl Appel, Denis Kalic, Matthew Kemmer, David Purcell, Carl Tompkins, Chan Tran The Siena College Institute for Artif

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Source URL: trec.nist.gov

Language: English - Date: 2012-02-03 09:41:52
883Natural language processing / Computational linguistics / Information / Question answering / Text Retrieval Conference / Precision and recall / Question / Science / Information science / Information retrieval

Answering multiple questions on a topic from heterogeneous resources Boris Katz, Matthew Bilotti, Sue Felshin, Aaron Fernandes, Wesley Hildebrandt, Roni Katzir, Jimmy Lin, Daniel Loreto, Gregory Marton, Federico Mora, Oz

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Source URL: trec.nist.gov

Language: English - Date: 2005-02-10 13:20:37
884Electronics / Varistor / Transient voltage suppressor / Surge protector / Voltage spike / Resistor / MOV / Voltage regulator / Capacitor / Electrical components / Electrical engineering / Electromagnetism

Metal-oxide varistor: a new way to suppress transients by J. D. Harnden Jr. and F.D. Martzloff Corporate Research and Development, General Electric Co and W . G. Morris and F. B. Golden Semiconductor Products Department,

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Source URL: pml.nist.gov

Language: English - Date: 2006-05-25 13:19:00
885Relevance feedback / Text Retrieval Conference / Precision and recall / Relevance / Query expansion / Document retrieval / Concept Search / RetrievalWare / Information science / Information retrieval / Science

IIT at TREC-8: Improving Baseline Precision M. Catherine McCabe Advanced Analytic Tools Washington, DC

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Source URL: trec.nist.gov

Language: English - Date: 2000-02-08 12:59:48
886Tf*idf / Document retrieval / Information science / Information retrieval / Query expansion

Retrieval of Biomedical Documents by Prioritizing Key Phrases Kevin Hsin-Yih Lin, Wen-Juan Hou and Hsin-Hsi Chen Department of Computer Science and Information Engineering, National Taiwan University Taipei, Taiwan, 106

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Source URL: trec.nist.gov

Language: English - Date: 2006-02-21 09:28:39
887Query expansion / Google Search / Full text search / Document retrieval / Text Retrieval Conference / Precision and recall / Search engine indexing / Relevance / Tf*idf / Information science / Information retrieval / Science

Juru at TREC 2006: TAAT versus DAAT in the Terabyte Track David Carmel, Einat Amitay IBM Haifa Research Lab Haifa 31905, Israel

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Source URL: trec.nist.gov

Language: English - Date: 2007-02-16 13:07:42
888Knowledge / Natural language processing / Bibliographic databases / National Institutes of Health / TREC Genomics / Relevance / Precision and recall / MEDLINE / Text mining / Science / Information science / Information retrieval

Microsoft Word - TREC 2005 Genomics Track 2-24.doc

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Source URL: trec.nist.gov

Language: English - Date: 2006-02-28 07:12:17
889Science / Natural language processing / Computational linguistics / Model selection / Statistical classification / Support vector machine / Vector space model / Latent semantic indexing / N-gram / Statistics / Information science / Information retrieval

TREC 2005 Enterprise Track Results from Drexel Weizhong Zhu1, Min Song2, and Robert B. Allen1 1 College of Information Science

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Source URL: trec.nist.gov

Language: English - Date: 2006-02-21 09:28:35
890Computational linguistics / Information retrieval / Linguistics / Text Retrieval Conference / Open domain question answering / Question answering / N-gram / Language model / Question / Science / Information science / Natural language processing

The Alyssa System at TREC 2006: A Statistically-Inspired Question Answering System Dan Shen Jochen L. Leidner Andreas Merkel Dietrich Klakow Spoken Language Systems Saarland University DSaarbr¨ucken, Germany

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Source URL: trec.nist.gov

Language: English - Date: 2007-02-16 13:07:46
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