NDLI: Rough set based clustering in dense web domain

Content Provider	IEEE Xplore Digital Library
Author	Mishra, R. Kumar, P. Bhasker, B.
Copyright Year	2012
Description	Author affiliation: Indian Institute of Management IT & Systems Department, Lucknow, India (Mishra, R.; Kumar, P.; Bhasker, B.)
Abstract	Clustering is a widely used technique in data mining applications. It groups the objects on the basis of similarity among them. Web has evolved enormously in past few years which resulted in sharp augmentation in number of web users and web pages. Web personalization has become a challenging task for e-Commerce based companies due to the information overload on web and increase of web users. Web users are matched with the available information in order to make personalization effective. Web usage data, coming from a single domain happens to be dense in nature as plenty of web users are fetching the pages from the same domain/ application area. This scenario is prevalent in case of e-Commerce websites. Rough set is a soft computing technique which is efficient in dealing with ambiguities present in data. In this paper we have utilized rough set based clustering using similarity upper approximation for deriving the clusters. The clusters evolve in steps and finally converge in to a well defined clustering scheme. Developers are trying to customize web sites as per the needs of specific users with the help of knowledge acquired from users' navigational behaviour. Since user page visits are intrinsically sequential in nature, efficient clustering algorithms with suitable distance/similarity measure for sequential data is needed. In the current paper, we demonstrate the clustering task for sequence data (web page visits) in three ways namely, capturing content information, sequence information and combination of both. Experimental results suggest that the measure which captures both content and sequence forms compact clusters, thus putting the web users of similar interests in one group.
Starting Page	521
Ending Page	526
File Size	740363
Page Count	6
File Format	PDF
ISBN	9781467351171
ISSN	21647143
e-ISBN	9781467351195
DOI	10.1109/ISDA.2012.6416592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-27
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decision support systems Rough Sets Helium Clustering Intelligent systems Web data Manganese
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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