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Categorization of Malay documents using latent semantic indexing

Ab Samat, Nordianah and Azmi Murad, Masrah Azrifah and Atan, Rodziah and Abdullah, Muhammad Taufik (2008) Categorization of Malay documents using latent semantic indexing. In: Knowledge Management International Conference 2008 (KMICe2008), 10-12 June 2008, Langkawi, Malaysia.

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Document categorization is a widely researched area of information retrieval.A popular approach to categorize documents is the Vector Space Model(VSM), which represents texts with feature vectors.The categorizing based on the VSM suffers from noise caused by synonymy and polysemy.Thus, an approach for the clustering of Malay documents based on semantic relations between words is proposed in this paper.The method is based on the model first formulated in the context o f information retrieval, called Latent Semantic Indexing (LSI).This model leads to a vector representation of each document using Singular Value Decomposition(SVD),where familiar clustering techniques can be applied in this space.LSI produced good document clustering by obtaining relevant subjects appearing in a cluster.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN 978-983-3827-73-2 Organized by: College of Arts and Sciences, Universiti Utara Malaysia
Uncontrolled Keywords: Latent Semantic Indexing, Document Clustering, K-means, Malay Language
Subjects: P Language and Literature > PL Languages and literatures of Eastern Asia, Africa, Oceania
Q Science > QA Mathematics > QA76 Computer software
Divisions: College of Arts and Sciences
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 05 Jun 2014 02:32
Last Modified: 05 Jun 2014 02:32

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