Concept-Based user Profiles for Effective Search

Concept-Based user Profiles for Effective Search
Authors : D. Pavithra
Publication Date: 22-06-2015


Author(s):  D. Pavithra

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Volume. 4 - Issue. 06 , June - 2015

e-ISSN:   2278-0181

 DOI:  http://dx.doi.org/10.17577/IJERTV4IS060446


The objective of this project is to create a concept–based user profile using SpyNB-C algorithm. The relationship between the users are mined from the concept-based user profiles to perform collaborative filtering which allow the users with the same interest to share their profiles. The concept-based user profile is integrated into ranking algorithm so that the results are ranked according to the individual user’s interest. Concept-based methods automatically derive users’ topical interest by exploring the contents of the users’ browsed documents and search histories. The user profile is represented as a set of categories, and for each category, a set of keywords with weights. The SpyNB-C identifies the user preference pairs generated from clickthrough data based on the concept. The SpyNB-C algorithm treats clicked pages as positive samples and unclicked pages as unlabeled samples in the training process. Collaborative filtering (CF) is the process of filtering information for a user, based on a collection of user profiles. Users having similar profiles may share similar interests. For a user, information can be filtered in/out regarding to the behaviors of his or her similar users. Ranking is used to display the web results such that the most relevant or authoritative pages are displayed first.


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