A new document representation using term frequency and vectorized graph connectionists with application to document retrieval

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

31 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)12023-12035
Journal / PublicationExpert Systems with Applications
Volume36
Issue number10
Publication statusPublished - Dec 2009

Abstract

This paper presents a new document representation with vectorized multiple features including term frequency and term-connection-frequency. A document is represented by undirected and directed graph, respectively. Then terms and vectorized graph connectionists are extracted from the graphs by employing several feature extraction methods. This hybrid document feature representation more accurately reflects the underlying semantics that are difficult to achieve from the currently used term histograms, and it facilitates the matching of complex graph. In application level, we develop a document retrieval system based on self-organizing map (SOM) to speed up the retrieval process. We perform extensive experimental verification, and the results suggest that the proposed method is computationally efficient and accurate for document retrieval. © 2009 Elsevier Ltd. All rights reserved.

Research Area(s)

  • Document retrieval, Graph representation, Multiple features, Self-organizing map

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