Alphabetical Index of TREC-9 Papers by Task/Track

Index of TREC-9 Papers by Task/Track
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Cross-Language [Filtering] [Interactive] [Query] [Question Answering] [Spoken Document Retrieval] [Web] BBN Technologies TREC-9 Cross Lingual Retrieval at BBN, page 106 Chinese University at Hong Kong TREC-9 CLIR at CUHK Disambiguation by Similarity Values Between Adjacent Words, page 151 Fudan University FDU at TREC-9: CLIR, Filtering and QA Tasks, page 189 IBM T.J. Watson Research Center English-Chinese Informatin Retrieval at IBM, page 223 Johns Hopkins University, APL The HAIRCUT System at TREC-9, page 273 Korea Advanced Institute of Science and Technology TREC-9 Experiments at KAIST: QA, CLIR and Batch Filtering, page 303 Microsoft Research China, Tsinghua University China, and the Université de Montréal TREC-9 CLIR Experiments at MSRCN, page 343 MNIS-TextWise Labs CINDOR Trec-9 English-Chinese Evaluation, page 379 National Taiwan University Description of NTU QA and CLIR Systems in TREC-9, page 389 Queens College, CUNY TREC-9 Cross Language, Web and Question-Answering Track Experiments using PIRCS, page 419 RMIT University Melbourne TREC-9 Experiments, page 437 University of California at Berkeley TREC-9 Cross-Language Information Retrieval (English-Chinese) Overview, page 15 English-Chinese Cross-Language IR Using Bilingual Dictionaries, page 517 University of Maryland TREC-9 Experiments at Maryland: Interactive CLIR, page 543 University of Massachusetts INQUERY and TREC-9, page 551
Filtering [Cross-Language] [Interactive] [Query] [Question Answering] [Spoken Document Retrieval] [Web] Carnegie Mellon University kNN at TREC-9, page 127 YFilter at TREC-9, page 135 Fudan University FDU at TREC-9: CLIR, Filtering and QA Tasks, page 189 Informatique-CDC, ESPCI Training Context-Sensitive Neural Networks with Few Relevant Examples for the TREC-9 Routing, page 257 IRIT-SIG Mercure at trec9: Web and Filtering tasks, page 263 KDD R&D Laboratories, Inc., Waseda University Experiments on the TREC-9 Filtering Track, page 295 Korea Advanced Institute of Science and Technology TREC-9 Experiments at KAIST: QA, CLIR and Batch Filtering, page 303 Microsoft Research, WhizzBang Labs The TREC-9 Filtering Track Final Report, page 25 Microsoft Research Ltd., UK Microsoft Cambridge at TREC-9: Filtering Track, page 361 Queens College, CUNY TREC-9 Cross Language, Web and Question-Answering Track Experiments using PIRCS, page 419 Rutgers University Logical Analysis of Data in the TREC-9 Filtering Track, page 453 Université de Montréal The System RELIEFS: A New Approach for Information Filtering, page 573 University of Iowa Filters and Answers: The University of Iowa TREC-9 Results, page 533 University of Nijmegen Incrementality, Half-life, and Threshold Optimization for Adaptive Document Filtering, page 589
Interactive [Filtering] [Cross-Language] [Query] [Question Answering] [Spoken Document Retrieval] [Web] Chapman University Passive Feedback Collection--An Attempt to Debunk the Myth of Clickthroughs, page 141 National Institute of Standards and Technology and the Oregon Health Sciences University TREC-9 Interactive Track Report, page 41 Oregon Health Sciences University Further Analysis of Whether Batch and User Evaluations Give the Same Results with a Question-Answering Task, page 407 RMIT University Melbourne TREC-9 Experiments, page 437 Rutgers University Support for Question-Answering in Interactive Information Retrieval: Rutgers' TREC-9 Interactive Track Experience, page 463 University of Glasgow Question Answering, Relevance Feedback and Summarisation: Trec-9 Interactive Track Report, page 523 University of Sheffield Sheffield Interactive Experiment at TREC-9, page 645
Query [Cross-Language] [Filtering] [Interactive] [Question Answering] [Spoken Document Retrieval] [Web] Hummingbird Hummingbird's Fulcrum SearchServer at TREC-9, page 211 Microsoft Research Ltd., UK Microsoft Cambridge at TREC-9: Filtering Track, page 361 National Institute of Standards and Technology Query Expansion Seen Through Return Order of Relevant Documents, page 51 SabIR Research, Inc. Query Expansion Seen Through Return Order of Relevant Documents, page 51 The TREC-9 Query Track, page 81 Sun Microsystems Laboratories Halfway to Question Answering, page 489 University of Massachusetts INQUERY and TREC-9, page 551
Question Answering [Cross-Language] [Filtering] [Interactive] [Query] [Spoken Document Retrieval] [Web] CL Research Syntactic Clues and Lexical Resources in Question-Answering, page 157 Fudan University FDU at TREC-9: CLIR, Filtering and QA Tasks, page 189 IBM T.J. Watson Research Center One Search Engine or Two for Question-Answering, page 235 IBM's Statistical Question Answering System, page 231 Imperial College of Science, Technology and Medicine A Simple Question Answering System, page 251 Korea Advanced Institute of Science and Technology TREC-9 Experiments at KAIST: QA, CLIR and Batch Filtering, page 303 Korea University Question Answering Considering Semantic Categories and Co-Occurence Density, page 317 LIMSI-CNRS QALC--The Question-Answering System of LIMSI-CNRS, page 325 Microsoft Research Ltd. Question Answering Using a Large NLP System, page 355 The MITRE Corporation Another Sys Called Qanda, page 369 National Institute of Standards and Technology Overview of the TREC-9 Question Answering Track, page 71 National Taiwan University Description of NTU QA and CLIR Systems in TREC-9, page 389 NTT Data Corporation NTT DATA TREC-9 Question Answering Track Report, page 399 Queens College, CUNY TREC-9 Cross Language, Web and Question-Answering Track Experiments using PIRCS, page 419 Southern Methodist University FALCON: Boosting Knowledge for Answer Engines, page 479 Sun Microsystems Laboratories Halfway to Question Answering, page 489 Syracuse University Question Answering: CNLP at the TREC-9 Question Answering Track, page 501 Universidad de Alicante A Semantic Approach to Question Answering Systems, page 511 Universitá di Pisa - Italy The PISAB Question Answering System, page 621 Université de Montréal Goal-Driven Answer Extraction, page 563 University of Iowa Filters and Answers: The University of Iowa TREC-9 Results, page 533 University of Massachusetts INQUERY and TREC-9, page 551 University of Sheffield University of Sheffield TREC-9 QA System, page 635 University of Southern California Question Answering in Webclopedia, page 655 University of Waterloo, CTIT Question Answering by Passage Selection (MultiText Experiments for TREC-9), page 673
Spoken Document Retrieval [Cross-Language] [Filtering] [Interactive] [Query] [Question Answering] [Web] Cambridge University Spoken Document Retrieval for TREC-9 at Cambridge University, page 117 LIMSI The LIMSI SDR System for TREC-9, page 335 National Institute of Standards and Technology Spoken Document Retrieval Track Slides University of Sheffield The Thisl SDR System at TREC-9, page 627
Web [Cross-Language] [Filtering] [Interactive] [Query] [Question Answering] [Spoken Document Retrieval] AT&T Labs-Research AT&T Labs at TREC-9, page 103 CSIRO Mathematics and Information Sciences ACSys/CSIRO TREC-9 Experiments, page 167 Melbourne TREC-9 Experiments, page 437 Overview of the TREC-9 Web Track, page 87 CWI, Amsterdam The Mirror DBMS at TREC-9, page 171 Dublin City University Dublin City University Experiments in Connectivity Analysis for TREC-9, page 179 Fujitsu Laboratories, Ltd. Fujitsu Laboratories TREC-9 Report, page 203 Hummingbird Hummingbird's Fulcrum SearchServer at TREC-9, page 211 Illinois Institute of Technology IIT TREC-9-Entity Based Feedback with Fusion, page 241 IRIT-SIG Mercure at trec9: Web and Filtering tasks, page 263 Johns Hopkins University, APL The HAIRCUT System at TREC-9, page 273 Justsystem Corporation Reflections on "Aboutness" TREC-9 Evaluation Experiments at Justsystem, page 281 Queens College, CUNY TREC-9 Cross Language, Web and Question-Answering Track Experiments using PIRCS, page 419 RICOH Co., Ltd. Structuring and Expanding Queries in the Probablistic Model, page 427 RMIT University Melbourne TREC-9 Experiments, page 437 SabIR Research, Inc. SabIR Research at TREC-9, page 475 TNO-TPD and Univ. of Twente TNO-UT at TREC-9: How Different are Web Documents?, page 665 University of Bangkok, Thailand Kasetsart University TREC-9 Experiments, page 289 Université de Neuchâtel Report on the TREC-9 Experiment: Link-based Retrieval an Distributed Collections, page 579 University of North Carolina, Chapel Hill Information Space Based on HTML Structure, page 601 University of Padova, Italy Web Document Retrieval Using Passage Retrieval, Connectivity Information, and Automatic Link Weighting--TREC-9 Report, page 611 University of Waterloo, CTIT Question Answering by Passage Selection (MultiText Experiments for TREC-9), page 673
Last updated: Friday, 05-Oct-2001 13:17:36 UTC Date created: Wednesday, 01-Aug-17 trec@nist.gov