Buyagain Grocery Recommender Algorithm for Online Shopping of Grocery and Gourmet Foods

Sharon J. Moses and L.D. Dhinesh Babu
Additional contact information
Sharon J. Moses: VIT University, Vellore, India
L.D. Dhinesh Babu: VIT University, Vellore, India

International Journal of Web Services Research (IJWSR), 2018, vol. 15, issue 3, 1-17

Abstract: Online shopping of grocery and gourmet products differ from other shopping activities due to its routine nature of buy-consume-buy. The existing recommendation algorithms of ecommerce websites are suitable only to render recommendation for products of one time purchase. So, in order to identify and recommend the products that users are likely to buy again and again, a novel recommender algorithm is proposed based on linguistic decision analysis model. The proposed buyagain recommender algorithm finds the semantic value of the user comments and computes the semantic value along with the user rating to render recommendation to the user. The efficiency of the buyagain recommender algorithm is evaluated using the grocery and gourmet dataset of amazon ecommerce websites. The end result proves that the algorithm accurately recommends the product that the user likes to purchase once again.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJWSR.2018070101 (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:jwsr00:v:15:y:2018:i:3:p:1-17

Access Statistics for this article

International Journal of Web Services Research (IJWSR) is currently edited by Liang-Jie Zhang

More articles in International Journal of Web Services Research (IJWSR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().