Multilayer SOM with tree-structured data for efficient document retrieval and plagiarism detection.

Full Abstract

This paper proposes a new document retrieval (DR) and plagiarism detection (PD) system using multilayer self-organizing map (MLSOM). A document is modeled by a rich tree-structured representation, and a SOM-based system is used as a computationally effective solution. Instead of relying on keywords/lines, the proposed scheme compares a full document as a query for performing retrieval and PD. The tree-structured representation hierarchically includes document features as document, pages, and paragraphs. Thus, it can reflect underlying context that is difficult to acquire from the currently used word-frequency information. We show that the tree-structured data is effective for DR and PD. To handle tree-structured representation in an efficient way, we use an MLSOM algorithm, which was previously developed by the authors for the application of image retrieval. In this study, it serves as an effective clustering algorithm. Using the MLSOM, local matching techniques are developed for comparing text documents. Two novel MLSOM-based PD methods are proposed. Detailed simulations are conducted and the experimental results corroborate that the proposed approach is computationally efficient and accurate for DR and PD.

Author information

Author/s: Chow, Tommy W S (TW); Rahman, M K M (MK);

Affiliation: Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong. eetchow(-atsign-)cityu.edu.hk

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council (IEEE Trans Neural Netw), published in United States. (Language: eng)

Reference: 2009-Sep; vol 20 (issue 9) : pp 1385-402

Dates: Created 2009/09/03; Completed 2009/11/04;

PMID: 19643706, status: MEDLINE (last retrieved date: 11/4/2009)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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