A semidiscrete matrix decomposition for latent semantic indexing information retrieval
نویسندگان
چکیده
منابع مشابه
A Semi-Discrete Matrix Decomposition for Latent Semantic Indexing in Information Retrieval
The vast amount of textual information available today is useless unless it can be e ectively and e ciently searched. In information retrieval, we wish to match queries with relevant documents. Documents can be represented by the terms that appear within them, but literal matching of terms does not necessarily retrieve all relevant documents. Latent Semantic Indexing represents documents by app...
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The focus of this paper is exploring the use of Latent Semantic Indexing (LSI) and Semi-Discrete Matrix Decomposition (SDD) in Bahasa Indonesia Information Retrieval System. The method is to take advantage of implicit higher-order structure in association of terms with document (" semantic structure ") in order to improve the detection of relevant document on the basis of terms found in queries...
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With the electronic storage of documents comes the possibility of building search engines that can automatically choose documents relevant to a given set of topics. In information retrieval, we wish to match queries with relevant documents. Documents can be represented by the terms that appear within them, but literal matching of terms does not necessarily retrieve all relevant documents. There...
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Due to the growth of large data collections, information retrieval or database searching is of vital importance. Lexical matching techniques may retrieve irrelevant or inaccurate results because of synonyms and polysemous words, so effective concept-based techniques are needed. One such technique is latent semantic indexing (LSI) which uses a vector-space approach by identifying documents whose...
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Conventional vector-based Information Retrieval (IR) models: Vector Space Model (VSM) and Generalized Vector Space Model (GVSM) represents documents and queries as vectors in a multidimensional space. This high dimensional data places great demands on computing resources. To overcome these problems, Latent Semantic Indexing (LSI), a variant of VSM, projects the documents into a lower dimensiona...
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ژورنال
عنوان ژورنال: ACM Transactions on Information Systems
سال: 1998
ISSN: 1046-8188,1558-2868
DOI: 10.1145/291128.291131