Systems and Means of Informatics
2016, Volume 26, Issue 4, pp 4-18
METHOD OF INCREASING INFORMATION PERTINENCE FOR E-COMMERCE RECOMMENDER SYSTEMS BASED ON IMPLICIT DATA
- S. A. Philippov
- V. N. Zakharov
Abstract
The paper describes the method of increasing pertinence of information in e-commerce recommender systems based on implicit data, i.e., due to the processing of user activity associated with the decision-making process. The method works successfully in situations where information about user activity is absent or little informative. Practical application of this method in e-commerce systems can improve their efficiency through targeted supply of goods and services to consumers. The main feature of the proposed method is the combined use of Item-Item CF (collaborative filtering) and User-User CF methods taking into account the implicit data collected. The features of the proposed method are verified by a prototype software that is installed on the existing online store Thaisoap.
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[+] About this article
Title
METHOD OF INCREASING INFORMATION PERTINENCE FOR E-COMMERCE RECOMMENDER SYSTEMS BASED ON IMPLICIT DATA
Journal
Systems and Means of Informatics
Volume 26, Issue 4, pp 4-18
Cover Date
2016-11-30
DOI
10.14357/08696527160401
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
pertinence search; collaborative filtering; e-commerce recommender system; implicit data targeting
Authors
S. A. Philippov  and V. N. Zakharov
Author Affiliations
Institute of Informatics Problems, Federal Research Center "Computer Science
and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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