Distributed EDLSI, BM25, and Power Norm at TREC 2008

This paper describes our participation in the TREC Legal competition in 2008. Our first set of experiments involved the use of Latent Semantic Indexing (LSI) with a small number of dimensions, a technique we refer to as Essential Dimensions of Latent Semantic Indexing (EDLSI). Because the experimental dataset is large, we designed a distributed version of EDLSI to use for our submitted runs. We submitted two runs using distributed EDLSI, one with k = 10 and another with k = 41, where k is the dimensionality reduction parameter for LSI. We also submitted a traditional vector space baseline for comparison with the EDLSI results. This article describes our experimental design and the results of these experiments. We find that EDLSI clearly outperforms traditional vector space retrieval using a variety of TREC reporting metrics. We also describe experiments that were designed as a followup to our TREC Legal 2007 submission. These experiments test weighting and normalization schemes as well...

• Type: Conference
• Year: 2008
• Where: TREC
• Authors: April Kontostathis, Andrew Lilly, Raymond J. Spiteri
• Keywords: Information Technology, Latent Semantic Indexing, Traditional Vector Space, TREC 2008, TREC Legal Competition