<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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 use the data represented in the form of matrices. The objective of this paper is to systematically analyze VSM, LSI and FCA for the task of IR using standard and real life datasets.</p></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 use the data represented in the form of matrices. The objective of this paper is to systematically analyze VSM, LSI and FCA for the task of IR using standard and real life datasets.

Analysis of a Vector Space Model, Latent Semantic Indexing and Formal Concept Analysis for Information Retrieval

School of Information Technology and Engineering, VIT University, Vellore, India

VSB Technical University of Ostrava, Ostrava, Czech Republic

School of Computing Science and Engineering, VIT University, Vellore, India

Cybernetics and Information Technologies

Latent Semantic Indexing (LSI), a variant of classical Vector Space Model (VSM), is an Information Retrieval (IR) model that attempts to capture the latent...

Analysis of a Vector Space Model, Latent Semantic Indexing and Formal Concept Analysis for Information Retrieval

Online veröffentlicht: 13. März 2013

Seitenbereich: 34 - 48

DOI: https://doi.org/10.2478/cait-2012-0003

Schlüsselwörter
Formal concept analysis, Information Retrieval, latent semantic indexing, vector space model

This content is open access.

Analysis of a Vector Space Model, Latent Semantic Indexing and Formal Concept Analysis for Information Retrieval

Online veröffentlicht: 13. März 2013

Seitenbereich: 34 - 48

DOI: https://doi.org/10.2478/cait-2012-0003

SchlüsselwörterFormal concept analysis, Information Retrieval, latent semantic indexing, vector space model

This content is open access.

Schlüsselwörter
Formal concept analysis, Information Retrieval, latent semantic indexing, vector space model