Profit Estimation Error Analysis in Recommender Systems based on Association Rules

dc.contributor.authorGurdal Ertek
dc.contributor.authorXu Chi
dc.contributor.authorGabriel Yee
dc.contributor.authorOng Boon Yong
dc.contributor.authorByung-Geun Choi
dc.date.accessioned2018-04-01T09:12:01Z
dc.date.accessioned2023-08-20T11:00:17Z
dc.date.available2018-04-01T09:12:01Z
dc.date.available2023-08-20T11:00:17Z
dc.date.issued2015-10
dc.descriptionErtek, G., Chi, X., Yee, G., Yong, O. B., & Choi, B. G. (2015, October). Profit estimation error analysis in recommender systems based on association rules. In Big Data (Big Data), 2015 IEEE International Conference on (pp. 2138-2142). IEEE.en_US
dc.description.abstractIt is a challenge to estimate expected benefits from recommender systems based on association rule mining. This paper aims to address this challenge and presents a study of buying preferences of a sample of retail customers. It reveals a monotonic, non-linear relationship between the expected profits (as a function of information loss) and minimum support thresh- old levels, when considering transactions for a recommender system based on association rules. This finding is significant for recommender systems that utilize potential profits as a decision- making criterion.en_US
dc.identifier.citationErtek, G., Chi, X., Yee, G., Yong, O. B., & Choi, B. G. (2015, October). Profit estimation error analysis in recommender systems based on association rules. In 2015 IEEE International Conference on Big Data (Big Data) (pp. 2138-2142). IEEE.en
dc.identifier.doihttps://doi.org/10.1109/BigData.2015.7363998
dc.identifier.urihttps://edms.wexl.in/handle/1/940
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.subjectRecommender Systemsen_US
dc.subjectAssociation Miningen_US
dc.subjectAssociation Ruleen_US
dc.subjectProfitabilityen_US
dc.subjectRetail Industryen_US
dc.titleProfit Estimation Error Analysis in Recommender Systems based on Association Rulesen_US
dc.typeConference Paperen

Files