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Experiments were conducted to explore the impact of combining various components of eight leading information retrieval systems. Each system demonstrated improved effectiveness through the use of blind feedback , also known as pseudo-relevance feedback , a form of query expansion. Blind feedback use...

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Bibliographic Details
Published in:Information retrieval (Boston) 2009-12, Vol.12 (6), p.680-694
Main Authors: Clarke, Charles L. A., Cormack, Gordon V., Lynam, Thomas R., Buckley, Chris, Harman, Donna
Format: Article
Language:English
Subjects:
Access to information
Algorithms
Computer Science
Data Mining and Knowledge Discovery
Data Structures and Information Theory
Documents
Exact sciences and technology
Experiments
Feedback
Information and communication sciences
Information processing and retrieval
Information retrieval
Information retrieval. Man machine relationship
Information science. Documentation
Information Storage and Retrieval
Knowledge management
Natural Language Processing (NLP)
Pattern Recognition
Queries
Query expansion
R&D
Relevance feedback
Reliable Information Access Workshop
Research & development
Research process. Evaluation
Sciences and techniques of general use
Studies
System effectiveness
Systems development
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Summary:Experiments were conducted to explore the impact of combining various components of eight leading information retrieval systems. Each system demonstrated improved effectiveness through the use of blind feedback , also known as pseudo-relevance feedback , a form of query expansion. Blind feedback uses the results of a preliminary retrieval step to augment the efficacy of a secondary retrieval step. The hybrid combination of primary and secondary retrieval steps from different systems in a number of cases yielded better effectiveness than either of the constituent systems alone. This positive combining effect was observed when entire documents were passed between the two retrieval steps, but not when only the expansion terms were passed. Several combinations of primary and secondary retrieval steps were fused using the CombMNZ algorithm; all yielded significant effectiveness improvement over the individual systems, with the best yielding an improvement of 13% ( p  = 10 −6 ) over the best individual system and an improvement of 4% ( p  = 10 −5 ) over a simple fusion of the eight systems.
ISSN:1386-4564
1573-7659
DOI:10.1007/s10791-009-9105-0