Anirban Mondal, Raghav Mittal, Vrinda Khandelwal, Parul Chaudhary, P. Reddy
{"title":"PEAR:产品到期意识和收益意识的项目集放置方案","authors":"Anirban Mondal, Raghav Mittal, Vrinda Khandelwal, Parul Chaudhary, P. Reddy","doi":"10.1109/DSAA53316.2021.9564189","DOIUrl":null,"url":null,"abstract":"Placement of items on the shelf space of retail stores significantly impacts the revenue of the retailer. Since customers typically tend to buy sets of items (i.e., itemsets) together, several research efforts have been undertaken towards facilitating itemset placement in retail stores for improving retailer revenue. However, they fail to consider that the time-period of expiry can vary across items i.e., some items expire sooner than others. This leads to loss of opportunity towards improving retailer revenue. Hence, we propose PEAR, which is a Product Expiry-Aware and Revenue-conscious itemset placement scheme for improving retailer revenue. Our key contributions are three-fold. First, we introduce the problem of addressing retail itemset placement when the items can be associated with different time-periods of expiry. Second, we propose the expiry-aware PEAR scheme for efficiently identifying and placing high-revenue itemsets for improving retailer revenue. Third, we conduct a performance study with two real datasets to demonstrate that PEAR is indeed effective in improving retailer revenue w.r.t. a reference scheme.","PeriodicalId":129612,"journal":{"name":"2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"PEAR: A Product Expiry-Aware and Revenue-Conscious Itemset Placement Scheme\",\"authors\":\"Anirban Mondal, Raghav Mittal, Vrinda Khandelwal, Parul Chaudhary, P. Reddy\",\"doi\":\"10.1109/DSAA53316.2021.9564189\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Placement of items on the shelf space of retail stores significantly impacts the revenue of the retailer. Since customers typically tend to buy sets of items (i.e., itemsets) together, several research efforts have been undertaken towards facilitating itemset placement in retail stores for improving retailer revenue. However, they fail to consider that the time-period of expiry can vary across items i.e., some items expire sooner than others. This leads to loss of opportunity towards improving retailer revenue. Hence, we propose PEAR, which is a Product Expiry-Aware and Revenue-conscious itemset placement scheme for improving retailer revenue. Our key contributions are three-fold. First, we introduce the problem of addressing retail itemset placement when the items can be associated with different time-periods of expiry. Second, we propose the expiry-aware PEAR scheme for efficiently identifying and placing high-revenue itemsets for improving retailer revenue. Third, we conduct a performance study with two real datasets to demonstrate that PEAR is indeed effective in improving retailer revenue w.r.t. a reference scheme.\",\"PeriodicalId\":129612,\"journal\":{\"name\":\"2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DSAA53316.2021.9564189\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSAA53316.2021.9564189","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PEAR: A Product Expiry-Aware and Revenue-Conscious Itemset Placement Scheme
Placement of items on the shelf space of retail stores significantly impacts the revenue of the retailer. Since customers typically tend to buy sets of items (i.e., itemsets) together, several research efforts have been undertaken towards facilitating itemset placement in retail stores for improving retailer revenue. However, they fail to consider that the time-period of expiry can vary across items i.e., some items expire sooner than others. This leads to loss of opportunity towards improving retailer revenue. Hence, we propose PEAR, which is a Product Expiry-Aware and Revenue-conscious itemset placement scheme for improving retailer revenue. Our key contributions are three-fold. First, we introduce the problem of addressing retail itemset placement when the items can be associated with different time-periods of expiry. Second, we propose the expiry-aware PEAR scheme for efficiently identifying and placing high-revenue itemsets for improving retailer revenue. Third, we conduct a performance study with two real datasets to demonstrate that PEAR is indeed effective in improving retailer revenue w.r.t. a reference scheme.