Are You Reaching Your Audience? Exploring Item Exposure over Consumer Segments in Recommender Systems

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Title: Are You Reaching Your Audience? Exploring Item Exposure over Consumer Segments in Recommender Systems
Other Titles: How Diverse Is Your Audience? Exploring Consumer Diversity in Recommender Systems
Authors: Wasilewski, JacekHurley, Neil J.
Permanent link: http://hdl.handle.net/10197/9979
Date: 31-Aug-2017
Online since: 2019-04-16T10:28:05Z
Abstract: Many state-of-the-art recommender systems are known to suffer from popularity bias, which means that they have a tendency to recommend items that are already popular, making those items even more popular. This results in the item catalogue being not fully utilised, which is far from ideal from the business’ perspective. Issues of item exposure are actually more complex than simply overexposure of popular items. In this paper we look at the exposure of individual items to different groups of consumers, the item’s audience, and address the question of whether recommender systems reach each item’s potential audience. Thus, we go beyond state-of-the-art analyses that have simply addressed the extent to which items are recommended, regardless of whether they are reaching their target audience. We conduct an empirical study on the MovieLens 20M dataset showing that recommender systems do not fully utilise items’ audiences, and existing sales diversity optimisers do not improve their exposure.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2017 the Authors
Keywords: Recommender systemsDiversityConsumer diversityItem-centric evaluation
Other versions: https://recsys.acm.org/recsys17/
http://ceur-ws.org/Vol-1905/
Language: en
Status of Item: Peer reviewed
Conference Details: The 11th ACM Conference on Recommender Systems, Como, Italy, 27-31 August 2017
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Insight Research Collection

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