Improving the Effectiveness of Information Retrieval with Clustering and Fusion

Jian Zhang ； Jian-Feng Gao ； Ming Zhou ； Jia-Xing Wang

《中文計算語言學期刊》 6卷1期 (2001/02) Pp. 109-125

https://doi.org/10.30019/IJCLCLP.200102.0005

並列摘要

Fusion and clustering are two approaches to improving the effectiveness of information retrieval. In fusion, ranked lists are combined together by various means. The motivation is that different JR systems will complement each other, because they usually emphasize different query features when determining relevance and retrieve different sets of documents. In clustering, documents are clustered either before or after retrieval. The motivation is that similar documents tend to be relevant to the same query so that this approach is likely to retrieve more relevant documents by identifying clusters of similar documents. In this paper, we present a novel fusion technique that can be combined with clustering to achieve consistent improvements over conventional approaches. Our method involves three steps: (1) clustering similar documents, (2) re-ranking retrieval results, and (3) combining retrieval results.

參考文獻

Allan, J.,Leuski, A.(2000).Proceedings of RIAO (Recherche d'Informations Assistee par Ordinateur.

CIIR Technical Report IR-172

Bartell, B. T.,Belew, R. K.,Cottrell, G. W.(1994).Proceedings of the 17th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval.

Cottrell, G.,Bartell, B. T.,Belew, R. K.,Vogt, C.(1997).Proceedings of the 5th Text Retrieval Conference (TREC 5), NIST Special Publication 500-238.

Cottrell, G.,Vogt, C.(1999).Fusion Via a Linear Combination of Scores.Information Retrieval.1(2)/1(3),151-173.