NDLI: Bartering Books to Beers: A Recommender System for Exchange Platforms

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Bartering Books to Beers: A Recommender System for Exchange Platforms

Content Provider	ACM Digital Library
Author	Rappaz, Jérémie McAuley, Julian Vladarean, Maria-Luiza Catasta, Michele
Abstract	Bartering is a timeless practice that is becoming increasingly popular on the Web. Recommending trades for an online bartering platform shares many similarities with traditional approaches to recommendation, in particular the need to model the preferences of users and the properties of the items they consume. However, there are several aspects that make bartering problems interesting and challenging, specifically the fact that users are both suppliers and consumers, and that the trading environment is highly dynamic. Thus, a successful model of bartering requires us to understand not just users' preferences, but also the social dynamics of who trades with whom, and the temporal dynamics of when trades occur. We propose new models for bartering-based recommendation, for which we introduce three novel datasets from online bartering platforms. Surprisingly, we find that existing methods (based on matching algorithms) perform poorly on real-world platforms, as they rely on idealized assumptions that are not supported by real bartering data. We develop approaches based on Matrix Factorization in order to model the reciprocal interest between users and each other's items. We also find that the social ties between members have a strong influence, as does the time at which they trade, therefore we extend our model to be socially- and temporally-aware. We evaluate our approach on trades covering books, video games, and beers, where we obtain promising empirical performance compared to existing techniques.
Starting Page	505
Ending Page	514
Page Count	10
File Format	PDF
ISBN	9781450346757
DOI	10.1145/3018661.3018696
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-02-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Exchange Barter Temporal dynamics Collaborative filtering Swap Reciprocity Social dynamics Matrix factorization
Content Type	Text
Resource Type	Article

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