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User Profile Mining and Personalization of Web Services

by Preeti Khare, Vandan Tewari, Nirmal Dagdee
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 105 - Number 13
Year of Publication: 2014
Authors: Preeti Khare, Vandan Tewari, Nirmal Dagdee
10.5120/18436-9501

Preeti Khare, Vandan Tewari, Nirmal Dagdee . User Profile Mining and Personalization of Web Services. International Journal of Computer Applications. 105, 13 ( November 2014), 12-15. DOI=10.5120/18436-9501

@article{ 10.5120/18436-9501,
author = { Preeti Khare, Vandan Tewari, Nirmal Dagdee },
title = { User Profile Mining and Personalization of Web Services },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 105 },
number = { 13 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume105/number13/18436-9501/ },
doi = { 10.5120/18436-9501 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:37:37.072577+05:30
%A Preeti Khare
%A Vandan Tewari
%A Nirmal Dagdee
%T User Profile Mining and Personalization of Web Services
%J International Journal of Computer Applications
%@ 0975-8887
%V 105
%N 13
%P 12-15
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web Services are defined as software systems designed to support interoperable machine-to-machine interaction over a network using standardized XML messages. Since user's expectations and requirements constantly change, it is important to include their preferences in offering of web services. A user profile, used in web service personalization, is a structured construct containing information both directly and indirectly pertaining to a user's preferences, behavior and context. Effective personalization requires services to build and maintain accurate models of a customer's preferences, interests and background through a user profile. Building effective user profiles can benefit from different research contributions in different areas, including security, statistical prediction and mining etc. In this paper we focus on the dynamic evaluation of user profiles for personalization of web services based on service usage log.

References
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  5. Ming-Chuan Hung and Don-Lin Yang, "An Efficient Fuzzy C-Means Clustering Algorithm" Department of Information Engineering, Feng Chain University Taichung Taiwan.
  6. Keno Buss, "Literature Review on Preprocessing for Text Mining," STRL, De Montfort University.
  7. J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York 1981
  8. S. Akthar, Sk. Md. Rafiet, Improving the software architecture therough fuzzy clustering technique, Indian Journal of Computer Science and Engineering1(1), 54-57.
Index Terms

Computer Science
Information Sciences

Keywords

User Profile Web Services Personalization and Service Usage Log

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