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TREC-4 Experiments using Drift
- In Proceedings of the Fourth Text Retrieval Conference (TREC-4
, 1996
"... Drift is a prototype, vector space based, information retrieval system in development at the University of Virginia. The system is designed to do experiments in distributed, dynamic information retrieval. We describe our first experiments using Drift on larger test collections, specifically the Cate ..."
Abstract
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Cited by 6 (4 self)
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the Category B subset of the TREC corpus. 1 Introduction The intelligent application of classic Information Retrieval (IR) methods in today's information environment is pivotal to enabling effective, efficient search of distributed document collections. Recent research results in the IR literature [1, 2
A Case Study with Topic 202 from TREC4
"... The sudden growth of the World Wide Web and its unprecedented popularity as a de facto global digital library exemplified both the strengths and weaknesses of the Information Retrieval techniques used by popular search engines. Most queries are short and incomplete attempts to describe or characteri ..."
Abstract
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for the exploration of the terminology of a corpus as well as for the automatic expansion of queries. The technique we use for the discovery of the associations is association rules mining
Automatic Word Similarity Detection for TREC 4 Query Expansion
- In 4th Text Retrieval Conf. (TREC-4), NIST #500-236
, 1995
"... Accessing online information remains an inexact science. While valuable information can be found, typically many irrelevant documents are also retrieved and many relevant ones are missed. Terminology mismatches between the user's query and document contents is a main cause of retrieval failures ..."
Abstract
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Cited by 3 (3 self)
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failures. Expanding a user's query with related words can improve search performance, but the problem of identifying related words remains. This research uses corpus linguistics techniques to automatically discover word similarities directly from the contents of the untagged TREC database
Automatic Word Similarity Detection for ABSTRACT TREC 4 Query Expansion
, 1995
"... Accessing online information remains an inexact science. While valuable information can be found, typically many irrelevant documents are also retrieved and many relevant ones are missed. Terminology mismatches between the user's query and document contents is a main cause of retrieval failures ..."
Abstract
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failures. Expanding a user's query with related words can improve search performance, but the problem of identifying related words remains. This research uses corpus linguistics techniques to automatically discover word similarities directly from the contents of the untagged TREC database
Information Retrieval Based on Context Distance and Morphology
- SIGIR '99
, 1999
"... We present an approach to information retrieval based on context distance and morphology. Context distance is a measure we use to assess the closeness of word meanings. This context distance model measures semantic distances between words using the local contexts of words within a single document as ..."
Abstract
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Cited by 22 (1 self)
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the proposed method on a subset of TREC-4 corpus (AP88 and AP90 collection, 158,240 documents, 49 queries). Results show that this method improves the 11-point average precision by 8.6%.
Summary Report on the TREC-4 Experiment: Combining Probabilistic and Vector-Space Schemes
"... This paper describes and evaluates a retrieval scheme combining the OKAPI probabilistic retrieval model with various vector-space schemes. In this study, each retrieval strategy represents both queries and documents using the same set of single terms; however they weight them differently. To combine ..."
Abstract
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with the relatively high retrieval effectiveness achieved by the OKAPI model, can various vector-space schemes further improve the retrieval performance of the OKAPI approach, and (3) can the learning results obtained with one tested collection (WSJ) be valid for another corpus (SJMN)?
Report on the TREC-4 Experiment: Combining Probabilistic and Vector-Space Schemes
, 1996
"... This paper describes and evaluates a retrieval scheme combining the OKAPI probabilistic retrieval model with various vector-space schemes. In this study, each retrieval strategy represents both queries and documents using the same set of single terms; however they weight them differently. To combine ..."
Abstract
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with the relatively high retrieval effectiveness achieved by the OKAPI model, can various vector-space schemes further improve the retrieval performance of the OKAPI approach, and (3) can the learning results obtained with one tested collection (WSJ) be valid for another corpus (SJMN)? Participation: Category: B
Abstract Information Retrieval Based on Context Distance and Morphology
"... We present an approach to information retrieval based on context distance and morphology. Context distance is a measure we use to assess the closeness of word meanings. This context distance model measures semantic distances between words using the local contexts of words within a single document as ..."
Abstract
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the proposed method on a subset of TREC-4 corpus (AP88 and AP90 collection, 158,240 documents, 49 queries). Results show that this method improves the 11-point average precision by 8.6%. 1
Evaluating Robustness Of A QA System Through A Corpus Of Real-Life Questions
"... This paper presents the sequential evaluation of the question answering system SQuaLIA. This system is based on the same sequential process as most statistical question answering systems, involving 4 main steps from question analysis to answer extraction.The evaluation is based on a corpus made from ..."
Abstract
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Cited by 1 (0 self)
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This paper presents the sequential evaluation of the question answering system SQuaLIA. This system is based on the same sequential process as most statistical question answering systems, involving 4 main steps from question analysis to answer extraction.The evaluation is based on a corpus made
ABSTRACT A Corpus Analysis Approach for Automatic Query Expansion and its Extension to Multiple Databases 1
, 1999
"... Searching online text collections can be both rewarding and frustrating. While valuable information can be found, typically many irrelevant documents are also retrieved and many relevant ones are missed. Terminology mismatches between the user's query and document contents are a main cause of r ..."
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of retrieval failures. Expanding a user's query with related words can improve search performance, but finding and using related words is an open problem. This research uses corpus analysis techniques to automatically discover similar words directly from the contents of the databases which are not tagged
Results 1 - 10
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29
