An Improved Mechanism for User Profile Generation Using Case-Based Reasoning and Weighted Association Rule Mining
DOI:
https://doi.org/10.26438/ijcse/v6i12.803809Keywords:
Normal Recovery Collaborative Filtering, Case Based Reasoning (CBR), Weighted Association Rule Mining (WARM), Hypertext Induced Topic Search (HITS)Abstract
Web page recommender systems play a major role in web searches by retrieving most relevant results. The goal of personalized recommendation is to tailor the search results to a particular user based on his/her interest. Traditional retrieval systems are not adaptive enough to satisfy the user’s individual needs and interests. A collaborative filtering approach, called Normal Recovery Collaborative Filtering (NRCF) is used to increase the accuracy of webpage recommendation. As an enhancement, this work applies Case Based Reasoning (CBR) in web searches to optimize the retrieval strategy and Weighted Association Rule Mining (WARM) algorithm to predict more accurate webpages using association rules generated specifically for individual user profiles. For any active user, the system retrieves most similar user profiles matching the current user. Weighted rules are generated based on the frequency of visit and duration spent on the page. WARM is based on the profile similarity between the active user and the computed weighted rules. Based on these rules, new pages that visited by similar users are recommended to the active user. Experiment results show that the proposed algorithm combining CBR and WARM outperforms well with more accuracy by providing more efficient and appropriate recommendation.
References
[1] Shashichhikara and Purushottam Sharma , “Weighted Association Rule Mining: A Survey’, International Journal of Research in Applied Science and Engineering Technology”, Vol. 2, pp. 84-88,2014.
[2] Wesley Chu and Tsau Young Lin, “Foundations and Advances in Data Mining (Studies in Fuzziness and Soft Computing”, Springer Verlag, Vol. 180, 2005.
[3] Şule Gunduz-Oguducu,“Web Page Recommendation Models: Theory and Algorithms”, Synthesis Lectures on Data Management, Vol. 2, pp. 1-85, 2010.
[4] Zibin Zheng, Hao Ma, Michael Lyu, R. and Irwin King, “Wsrec: A Collaborative Filtering Based Web Service Recommender System”, IEEE International Conference on Web Services, pp. 437 – 444, 2009
[5] Zibin Zheng, Hao Ma, Michael Lyu, R. and Irwin Kin, “QoS-aware Web Service Recommendation by Collaborative Filtering”, IEEE Transactions on Services Computing, Vol. 4, pp. 140-152, 2012.
[6] Huifeng Sun, Zibin Zheng, Junliang Chen and Michael Lyu, R., “Personalized Web Service Recommendation via Normal Recovery Collaborative Filtering”, IEEE Transactions on Services Computing, Vol. 6, pp. 573 – 579, 2012.
[7] Yong-Bin Kang, Shonali Krishnaswamy and Arkady Zaslavsky, “A Retrieval Strategy for Case-Based Reasoning Using Similarity and Association Knowledge”, IEEE Transactions on Cybernetics, Vol. 44, pp. 473 – 487, 2014.
[8] Liang Yan and Chunping Li, “Incorporating Page View Weight into an Association-Rule-Based Web Recommendation System”, In proceedings of 19th Australian Conference on Advances in Artificial Intelligence, pp. 577-586, 2006
[9] Barry Smyth, “The Adaptive Web”, Springer Berlin Heidelberg, LNCS.4321, 2007.
[10] Pooja Devi, Ashlesha Gupta and Ashutosh Dixit, “Comparative Study of HITS and PageRank Link Based Ranking Algorithms”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 3, pp. 5749-5754, 2014.
[11] Bhavithra Janakiraman, Saradha Arumugam, Aiswarya Jayaprakash, “An Improved Mechanism For User Profiling And Recommendation Using Case-Based Reasoning”, Emerging trends in Computer Engineering and Research (ECER),Vol 8, no.2, pp.319-327, 2017
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
