Open AccessMultidimensional User Data Model for Web Personalization
Author(s) -
Nithin K. Anil,
Sharath Basil Kurian,
T Aby Abahai,
Surekha Mariam Varghese
Publication year - 2013
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/11896-7955
Subject(s) - computer science , personalization , personalized search , cluster analysis , profiling (computer programming) , information retrieval , ranking (information retrieval) , relevance (law) , data mining , world wide web , machine learning , political science , law , operating system
Personalization is being applied to great extend in many systems. This paperpresents a multi-dimensional user data model and its application in web search.Online and Offline activities of the user are tracked for creating the usermodel. The main phases are identification of relevant documents and therepresentation of relevance and similarity of the documents. The conceptsKeywords, Topics, URLs and clusters are used in the implementation. Thealgorithms for profiling, grading and clustering the concepts in the user modeland algorithm for determining the personalized search results by re-ranking theresults in a search bank are presented in this paper. Simple experiments forevaluation of the model and their results are described.Comment: 6 pages, 3 figures -"Published with International Journal of Computer Applications (IJCA)