Open AccessProceedings Article
INQUERY does battle with TREC-6
James Allan,James P. Callan,W. Bruce Croft,Lisa Ballesteros,Donald Byrd,Russell Swan,Jinxi Xu +6 more
- Iss: 500240, pp 169-206
TLDR
Participation du CIIR (Center for Intelligent Information Retrieval) de l'Universite du Massachusetts au congres TREC 6Abstract:
Participation du CIIR (Center for Intelligent Information Retrieval) de l'Universite du Massachusetts au congres TREC 6read more
Citations
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Journal ArticleDOI
Improving the effectiveness of information retrieval with local context analysis
Jinxi Xu,W. Bruce Croft +1 more
TL;DR: A new technique is proposed, called local context analysis, which selects expansion terms based on cooccurrence with the query terms within the top-ranked documents.
Proceedings ArticleDOI
A hidden Markov model information retrieval system
TL;DR: A novel method for performing blind feedback in the HMM framework, a more complex HMM that models bigram production, and several other algorithmic re nements form a state-of-the-art retrieval system that ranked among the best on the TREC-7 ad hoc retrieval task.
Proceedings Article
The TREC spoken document retrieval track: a success story
TL;DR: The SDR Track can be declared a success in that it has provided objective, demonstrable proof that this technology can be successfully applied to realistic audio collections using a combination of existing technologies and that it can be objectively evaluated.
Journal ArticleDOI
Overview of the sixth text REtrieval conference (TREC-6)
Ellen M. Voorhees,Donna Harman +1 more
TL;DR: The Text REtrieval Conference is a workshop series designed to encourage research on text retrieval for realistic applications by providing large test collections, uniform scoring procedures and a forum for organizations interested in comparing results.
Journal ArticleDOI
Combining the language model and inference network approaches to retrieval
Donald Metzler,W. Bruce Croft +1 more
TL;DR: This paper combines the language modeling and inference network approaches into a single framework that allows structured queries to be evaluated using language modeling estimates and reaffirms that high quality structured queries outperform unstructured queries.
References
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Book ChapterDOI
The INQUERY Retrieval System
TL;DR: A retrieval system (INQUERY) that is based on a probabilistic retrieval model and provides support for sophisticated indexing and complex query formulation is described.
Proceedings ArticleDOI
Phrasal translation and query expansion techniques for cross-language information retrieval
Lisa Ballesteros,W. Bruce Croft +1 more
TL;DR: The role of phrases in query expansion via local context analysis and local feedback and how they can be used to significantly reduce the error associated with automatic dictionary translation are explored.
Proceedings ArticleDOI
Querying across languages: a dictionary-based approach to multilingual information retrieval
TL;DR: This paper found that correct identification and translation of multi-word terminology is the single most important source of error in the system, although amblguit y in translation also contributes to poor performance.
Proceedings ArticleDOI
Optimization of relevance feedback weights
Chris Buckley,Gerard Salton +1 more
TL;DR: The approach used here, Dynamic Feedback C)ptimization starts with a good weighting scheme based npoa Rocchi(r ferxlback) and improves those weights in a dynamic fashion by t,rw,iug possible changes of query weights on th~ learning set, documents, and the resulting optimized query performs 1o-1.5% better.
Proceedings ArticleDOI
Incremental relevance feedback
TL;DR: This paper focuses on a relevance feedback technique that allows easily understandable and manageable user interfaces, and at the same time provides high-quality retrieval results.