Document (#34712)

Author
Kumar, C.A.
Radvansky, M.
Annapurna, J.
Title
Analysis of Vector Space Model, Latent Semantic Indexing and Formal Concept Analysis for information retrieval
Source
Cybernetics and information technologies. 12(2012) no.1, S.34-48
Year
2012
Abstract
Latent Semantic Indexing (LSI), a variant of classical Vector Space Model (VSM), is an Information Retrieval (IR) model that attempts to capture the latent semantic relationship between the data items. Mathematical lattices, under the framework of Formal Concept Analysis (FCA), represent conceptual hierarchies in data and retrieve the information. However both LSI and FCA uses the data represented in form of matrices. The objective of this paper is to systematically analyze VSM, LSI and FCA for the task of IR using the standard and real life datasets.
Theme
Formale Begriffsanalyse
Object
Latent semantic indexing

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  5. Li, D.; Kwong, C.-P.: Understanding latent semantic indexing : a topological structure analysis using Q-analysis (2010) 0.37
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