, Latent Semantic Indexing (LSI) and TREC-2., in The Second Text REtrieval Conference (TREC2), D. Harman, ed., March 1994, pp. 105--116. National Institute of Standards and Technology Special Publication 500-215. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Computational Methods for Intelligent Information Access - Berry, Dumais, al. (1995) (13 citations) (Correct)
....used vectors derived from known relevant documents (like relevance feedback) combined with LSI matching. TREC Recently, LSI has been used for both information filtering and information retrieval in TREC (Text REtrieval Conference) a large scale retrieval conference conferencesponsored by NIST [8, 9]. The TREC collection contains more than 1; 000; 000 documents (representing more that 3 gigabytes of ASCII text) 200 queries, and relevance 28 judgements pooled from the return sets of more than 30 systems. The content of the collections varies widely ranging from news sources (AP News Wire, ....
....in Section 3.3. That is, the vector for a document is located at the weighted vector sum of its constituent term vectors. Although it is very difficult to compare across systems in any detail because of large pre processing, representation and matching differences, LSI performance was quite good [9]. For filtering tasks, using information about known relevant documents to create a vector for each query was beneficial. The retrieval advantage of 31 was somewhat smaller than that observed for other filtering tests and is attributable to the good initial queries in TREC. For retrieval tasks, ....
[Article contains additional citation context not shown here]
, Latent Semantic Indexing (LSI) and TREC-2., in The Second Text REtrieval Conference (TREC2), D. Harman, ed., March 1994, pp. 105--116. National Institute of Standards and Technology Special Publication 500-215.
Using Linear Algebra for Intelligent Information Retrieval - Berry, Dumais, O'Brien (1995) (183 citations) (Correct)
....used vectors derived from known relevant documents (like relevance feedback) combined with LSI matching. TREC. Recently, LSI has been used for both information filtering and information retrieval in TREC (Text REtrieval Conference) a large scale retrieval conference conference sponsored by NIST [7, 8]. The TREC collection contains more than 1; 000; 000 documents (representing more that 3 gigabytes of ASCII text) 200 queries, and relevance judgements pooled from the return sets of more than 30 systems. The content of the collections varies widely ranging from news sources (AP News Wire, Wall ....
....in Section 3.3. That is, the vector for a document is located at the weighted vector sum of its constituent term vectors. Although it is very difficult to compare across systems in any detail because of large pre processing, representation and matching differences, LSI performance was quite good [8]. For filtering tasks, using information about known relevant documents to create a vector for each query was beneficial. The retrieval advantage of 31 was somewhat smaller than that observed for other filtering tests and is attributable to the good initial queries in TREC. For retrieval tasks, ....
[Article contains additional citation context not shown here]
, Latent Semantic Indexing (LSI) and TREC-2., in The Second Text REtrieval Conference (TREC2), D. Harman, ed., March 1994, pp. 105--116. National Institute of Standards and Technology Special Publication 500-215.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC