JOURNAL ARTICLE

General query expansion techniques for spoken document retrieval

Pierre JourlinSE JohnsonKaren Spärck JonesPC Woodland

Year: 1999 Journal:   The American Journal of Medicine Vol: 100 (4)Pages: 383-5   Publisher: Elsevier BV

Abstract

This paper presents some developments in query expansion and document representation of our Spoken Document Retrieval (SDR) system since the 1998 Text REtrieval Conference (TREC-7). We have shown that a modification of the document representation combining several techniques for query expansion can improve Average Precision by 17 % relative to a system similar to that which we presented at TREC-7 [1]. These new experiments have also confirmed that the degradation of Average Precision due to a Word Error Rate (WER) of 25 % is relatively small (around 2 % relative). We hope to repeat these experiments when larger document collections become available to evaluate the scalability of these techniques.

Keywords:
Query expansion Computer science Document retrieval Information retrieval Scalability Representation (politics) Query optimization Natural language processing Database

Metrics

24
Cited By
4.01
FWCI (Field Weighted Citation Impact)
12
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Algorithms and Data Compression
Physical Sciences →  Computer Science →  Artificial Intelligence
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