A Meta-Heuristic Algorithm Approximating Optimized Recommendations for E-Commerce Business Promotions

Shalini Gupta and Veer Sain Dixit
Additional contact information
Shalini Gupta: Department of Computer Science, Atma Ram Sanatan Dharma College, University of Delhi, Delhi, India
Veer Sain Dixit: Department of Computer Science, Atma Ram Sanatan Dharma College, University of Delhi, Delhi, India

International Journal of Information Technology Project Management (IJITPM), 2020, vol. 11, issue 2, 23-49

Abstract: To provide personalized services such as online-product recommendations, it is usually necessary to model clickstream behavior of users if implicit preferences are taken into account. To accomplish this, web log mining is a promising approach that mines clickstream sessions and depicts frequent sequential paths that a customer follows while browsing e-commerce websites. Strong attributes are identified from the navigation behavior of users. These attributes reflect absolute preference (AP) of the customer towards a product viewed. The preferences are obtained only for the products clicked. These preferences are further refined by calculating the sequential preference (SP) of the user for the products. This paper proposes an intelligent recommender system known as SAPRS (sequential absolute preference-based recommender system) that embed these two approaches that are integrated to improve the quality of recommendation. The performance is evaluated using information retrieval methods. Extensive experiments were carried out to evaluate the proposed approach against state-of-the-art methods.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJITPM.2020040103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jitpm0:v:11:y:2020:i:2:p:23-49

Access Statistics for this article

International Journal of Information Technology Project Management (IJITPM) is currently edited by John Wang

More articles in International Journal of Information Technology Project Management (IJITPM) from IGI Global
Bibliographic data for series maintained by Journal Editor ().