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Authors: Yonggong Ren 1 and Alma Leora Culén 2

Affiliations: 1 Liaoning Normal University, China ; 2 University of Oslo, Norway

Keyword(s): Web Data Mining, Inter-transaction Association Rules, Dual-strategy Database, Dual Strategy Users Interest Prediction Model.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Soft Computing ; Symbolic Systems ; Web Mining

Abstract: The 2nd Markov Model and inter-transaction association rules are both known as key technologies for building user interest prediction models. The use of these technologies potentially improves the users surfing experience. The use of the 2nd Markov Model increases the accuracy of predictions, but it does not cover all the data. Therefore, in this paper we propose a dual strategy for a user interest prediction model that includes the entire data set and improves the accuracy of inter-transaction association rules. The foundation of our dual strategy is a new method of building a database based on the degree of user interest. Secondly, we integrate the 2nd Markov Model and inter-transaction association rules for predicting future browsing patterns of users. Experimental results show that this method provides more accurate prediction results than previous similar research.

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Paper citation in several formats:
Ren, Y. and Culén, A. (2011). USERS INTEREST PREDICTION MODEL - Based on 2nd Markov Model and Inter-transaction Association Rules. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2011) - KDIR; ISBN 978-989-8425-79-9; ISSN 2184-3228, SciTePress, pages 236-241. DOI: 10.5220/0003659502440249

@conference{kdir11,
author={Yonggong Ren. and Alma Leora Culén.},
title={USERS INTEREST PREDICTION MODEL - Based on 2nd Markov Model and Inter-transaction Association Rules},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2011) - KDIR},
year={2011},
pages={236-241},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003659502440249},
isbn={978-989-8425-79-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2011) - KDIR
TI - USERS INTEREST PREDICTION MODEL - Based on 2nd Markov Model and Inter-transaction Association Rules
SN - 978-989-8425-79-9
IS - 2184-3228
AU - Ren, Y.
AU - Culén, A.
PY - 2011
SP - 236
EP - 241
DO - 10.5220/0003659502440249
PB - SciTePress