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Adaptive, Personalized Diversity for Visual Discovery

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S.V.N. VishwanathanAuthors Info & Claims

RecSys '16: Proceedings of the 10th ACM Conference on Recommender Systems

Pages 35 - 38

https://doi.org/10.1145/2959100.2959171

Published: 07 September 2016 Publication History

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Abstract

Search queries are appropriate when users have explicit intent, but they perform poorly when the intent is difficult to express or if the user is simply looking to be inspired. Visual browsing systems allow e-commerce platforms to address these scenarios while offering the user an engaging shopping experience. Here we explore extensions in the direction of adaptive personalization and item diversification within Stream, a new form of visual browsing and discovery by Amazon. Our system presents the user with a diverse set of interesting items while adapting to user interactions. Our solution consists of three components (1) a Bayesian regression model for scoring the relevance of items while leveraging uncertainty, (2) a submodular diversification framework that re-ranks the top scoring items based on category, and (3) personalized category preferences learned from the user's behavior. When tested on live traffic, our algorithms show a strong lift in click-through-rate and session duration.

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Chen SWang YWen ZLi ZZhang CZhang XLin QZhu CXu JSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)Controllable Multi-Objective Re-ranking with Policy HypernetworksProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599796(3855-3864)Online publication date: 6-Aug-2023
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Mahajan KPalnitkar ARaul ASchumitsch B(2023)CAViaR: Context Aware Video RecommendationsCompanion Proceedings of the ACM Web Conference 202310.1145/3543873.3584658(518-522)Online publication date: 30-Apr-2023
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Index Terms

Adaptive, Personalized Diversity for Visual Discovery
1. Information systems
  1. World Wide Web
    1. Web searching and information discovery
      1. Personalization

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Published In

RecSys '16: Proceedings of the 10th ACM Conference on Recommender Systems

September 2016

490 pages

ISBN:9781450340359

DOI:10.1145/2959100

General Chairs:
Shilad Sen
Macalester College, USA
,
Werner Geyer
IBM Research Cambridge, USA
,
Program Chairs:
Jill Freyne
CSIRO, Australia
,
Pablo Castells
Universidad Autónoma de Madrid, Spain

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 07 September 2016

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SIGCHI

RecSys '16: Tenth ACM Conference on Recommender Systems

September 15 - 19, 2016

Massachusetts, Boston, USA

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RecSys '16 Paper Acceptance Rate 29 of 159 submissions, 18%;

Overall Acceptance Rate 254 of 1,295 submissions, 20%

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Cited By

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Pandey SDas SGanu HSingh SBalsamo SKnottenbelt WAbad CShang W(2024)Rethinking 'Complement' Recommendations at Scale with SIMDProceedings of the 15th ACM/SPEC International Conference on Performance Engineering10.1145/3629526.3645041(25-36)Online publication date: 7-May-2024
https://dl.acm.org/doi/10.1145/3629526.3645041
Chen SWang YWen ZLi ZZhang CZhang XLin QZhu CXu JSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)Controllable Multi-Objective Re-ranking with Policy HypernetworksProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599796(3855-3864)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599796
Mahajan KPalnitkar ARaul ASchumitsch B(2023)CAViaR: Context Aware Video RecommendationsCompanion Proceedings of the ACM Web Conference 202310.1145/3543873.3584658(518-522)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543873.3584658
Yang LWang STao YSun JLiu XYu PWang TChua TLauw HSi LTerzi ETsaparas P(2023)DGRec: Graph Neural Network for Recommendation with Diversified Embedding GenerationProceedings of the Sixteenth ACM International Conference on Web Search and Data Mining10.1145/3539597.3570472(661-669)Online publication date: 27-Feb-2023
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Hansen CMehrotra RHansen CBrost BMaystre LLalmas MLewin-Eytan LCarmel DYom-Tov EAgichtein EGabrilovich E(2021)Shifting Consumption towards Diverse Content on Music Streaming PlatformsProceedings of the 14th ACM International Conference on Web Search and Data Mining10.1145/3437963.3441775(238-246)Online publication date: 8-Mar-2021
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Abdool MHaldar MRamanathan PSax TZhang LManaswala AYang LTurnbull BZhang QLegrand TGupta RLiu YShah MRajan STang JPrakash B(2020)Managing Diversity in Airbnb SearchProceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3394486.3403345(2952-2960)Online publication date: 23-Aug-2020
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Zhao YZhou YOu MXu HLi NGupta RLiu YShah MRajan STang JPrakash B(2020)Maximizing Cumulative User Engagement in Sequential RecommendationProceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3394486.3403329(2784-2792)Online publication date: 23-Aug-2020
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