NDLI: Document Clustering Using Concept Space and Cosine Similarity Measurement

Content Provider	IEEE Xplore Digital Library
Author	Muflikhah, L. Baharudin, B.
Copyright Year	2009
Abstract	Document clustering is related to data clustering concept which is one of data mining tasks and unsupervised classification. It is often applied to the huge data in order to make a partition based on their similarity. Initially, it used for Information Retrieval in order to improve the precision and recall from query. It is very easy to cluster with small data attributes which contains of important items. Furthermore, document clustering is very useful in retrieve information application in order to reduce the consuming time and get high precision and recall. Therefore, we propose to integrate the information retrieval method and document clustering as concept space approach. The method is known as Latent Semantic Index (LSI) approach which used Singular Vector Decomposition (SVD) or Principle Component Analysis (PCA). The aim of this method is to reduce the matrix dimension by finding the pattern in document collection with refers to concurrent of the terms. Each method is implemented to weight of term-document in vector space model (VSM) for document clustering using fuzzy c-means algorithm. Besides reduction of term-document matrix, this research also uses the cosine similarity measurement as replacement of Euclidean distance to involve in fuzzy c-means. And as a result, the performance of the proposed method is better than the existing method with f-measure around 0.91 and entropy around 0.51.
Starting Page	58
Ending Page	62
File Size	747617
Page Count	5
File Format	PDF
ISBN	9780769538921
DOI	10.1109/ICCTD.2009.206
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-11-13
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cosine similarity LSI Clustering methods Extraterrestrial measurements Information retrieval Large scale integration Data mining Fuzzy c-means Information science Document clustering Space technology Clustering algorithms Euclidean distance Principal component analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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