Mitigating long tail effect in recommendations using few shot learning technique

Volume: 140, Pages: 112887 - 112887
Published: Feb 1, 2020
Abstract
Recommender system has been established as an effective tool for users in providing personalized suggestions in many domains, especially in e-commerce. In these domains, recommendations are provided based on the feedback (ratings) given by the users. However, recommendations provided by the traditional approaches are biased towards the popular items (items that receive more number of ratings). As a result, unpopular items are left out and these...
Paper Details
Title
Mitigating long tail effect in recommendations using few shot learning technique
Published Date
Feb 1, 2020
Volume
140
Pages
112887 - 112887
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