Session-Based Recommender System for Sustainable Digital Marketing

Hyunwoo Hwangbo and Yangsok Kim
Additional contact information
Hyunwoo Hwangbo: Graduate School of Information, Yonsei University, 50 Yonsei-ro, Seodaemun-Gu, Seoul 03722, Korea
Yangsok Kim: Department of Management Information Systems, KeiMyung University, 1095 Dalgubeol-daero, Dalseo-Gu, Daegu 42061, Korea

Sustainability, 2019, vol. 11, issue 12, 1-19

Abstract: Many companies operate e-commerce websites to sell fashion products. Some customers want to buy products with intention of sustainability and therefore the companies need to suggest appropriate fashion products to those customers. Recommender systems are key applications in these sustainable digital marketing strategies and high performance is the most necessary factor. This research aims to improve recommendation systems’ performance by considering item session and attribute session information. We suggest the Item Session-Based Recommender (ISBR) and the Attribute Session-Based Recommenders (ASBRs) that use item and attribute session data independently, and then we suggest the Feature-Weighted Session-Based Recommenders (FWSBRs) that combine multiple ASBRs with various feature weighting schemes. Our experimental results show that FWSBR with chi-square feature weighting scheme outperforms ISBR, ASBRs, and Collaborative Filtering Recommender (CFR). In addition, it is notable that FWSBRs overcome the cold-start item problem, one significant limitation of CFR and ISBR, without losing performance.

Keywords: sustainable digital marketing; sustainable fashion business; session-based recommender; sequential patterns; feature selection; feature weighting; cold-start problem (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/12/3336/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/12/3336/ (text/html)

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:gam:jsusta:v:11:y:2019:i:12:p:3336-:d:240384

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().