research-article

Fair and balanced: learning to present news stories

Authors:

S.V.N. Vishwanathan,

Alex SmolaAuthors Info & Claims

WSDM '12: Proceedings of the fifth ACM international conference on Web search and data mining

Pages 333 - 342

https://doi.org/10.1145/2124295.2124337

Published: 08 February 2012 Publication History

Abstract

Relevance, diversity and personalization are key issues when presenting content which is apt to pique a user's interest. This is particularly true when presenting an engaging set of news stories. In this paper we propose an efficient algorithm for selecting a small subset of relevant articles from a streaming news corpus. It offers three key pieces of improvement over past work: 1) It is based on a detailed model of a user's viewing behavior which does not require explicit feedback. 2) We use the notion of submodularity to estimate the propensity of interacting with content. This improves over the classical context independent relevance ranking algorithms. Unlike existing methods, we learn the submodular function from the data. 3) We present an efficient online algorithm which can be adapted for personalization, story adaptation, and factorization models. Experiments show that our system yields a significant improvement over a retrieval system deployed in production.

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Cited By

Liu JLiu CBelkin N(2020)Personalization in text information retrievalJournal of the Association for Information Science and Technology10.1002/asi.2423471:3(349-369)Online publication date: 28-Jan-2020
https://dl.acm.org/doi/10.1002/asi.24234
Veloso BAssunção RFerreira AZiviani N(2019)In Search of a Stochastic Model for the E-News ReaderACM Transactions on Knowledge Discovery from Data10.1145/336269513:6(1-27)Online publication date: 13-Nov-2019
https://dl.acm.org/doi/10.1145/3362695
Chen CChou STai CKu L(2019)Phrase-guided attention web article recommendation for next clicks and viewsProceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1145/3341161.3342869(315-324)Online publication date: 27-Aug-2019
https://dl.acm.org/doi/10.1145/3341161.3342869
Show More Cited By

Index Terms

Fair and balanced: learning to present news stories
1. Computing methodologies
  1. Machine learning

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cover image ACM Conferences

WSDM '12: Proceedings of the fifth ACM international conference on Web search and data mining

February 2012

792 pages

ISBN:9781450307475

DOI:10.1145/2124295

General Chairs:
Eytan Adar
University of Michigan, USA
,
Jaime Teevan
Microsoft Research, USA
,
Program Chairs:
Eugene Agichtein
Emory University, USA
,
Yoelle Maarek
Yahoo! Research, Israel

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 February 2012

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WSDM'12: Fifth ACM International Conference on Web Search and Data Mining

February 8 - 12, 2012

Washington, Seattle, USA

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Cited By

Liu JLiu CBelkin N(2020)Personalization in text information retrievalJournal of the Association for Information Science and Technology10.1002/asi.2423471:3(349-369)Online publication date: 28-Jan-2020
https://dl.acm.org/doi/10.1002/asi.24234
Veloso BAssunção RFerreira AZiviani N(2019)In Search of a Stochastic Model for the E-News ReaderACM Transactions on Knowledge Discovery from Data10.1145/336269513:6(1-27)Online publication date: 13-Nov-2019
https://dl.acm.org/doi/10.1145/3362695
Chen CChou STai CKu L(2019)Phrase-guided attention web article recommendation for next clicks and viewsProceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1145/3341161.3342869(315-324)Online publication date: 27-Aug-2019
https://dl.acm.org/doi/10.1145/3341161.3342869
Ding WGovindaraj DVishwanathan STeredesai AKumar VLi YRosales RTerzi EKarypis G(2019)Whole Page Optimization with Global ConstraintsProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330675(3153-3161)Online publication date: 25-Jul-2019
https://dl.acm.org/doi/10.1145/3292500.3330675
Ji QShi XShang M(2019)A Deep Temporal Collaborative Filtering Recommendation Framework via Joint Learning from Long and Short-Term Effects2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00139(959-966)Online publication date: Dec-2019
https://doi.org/10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00139
Veloso B(2019)Stochastic Models to Improve E-News Recommender SystemsAdvances in Conceptual Modeling10.1007/978-3-030-34146-6_24(255-262)Online publication date: 27-Oct-2019
https://doi.org/10.1007/978-3-030-34146-6_24
Chen LZhang GZhou H(2018)Fast greedy MAP inference for determinantal point process to improve recommendation diversityProceedings of the 32nd International Conference on Neural Information Processing Systems10.5555/3327345.3327465(5627-5638)Online publication date: 3-Dec-2018
https://dl.acm.org/doi/10.5555/3327345.3327465
Al-Ghossein MMurena PAbdessalem TBarré ACornuéjols APera SEkstrand MAmatriain XO'Donovan J(2018)Adaptive collaborative topic modeling for online recommendationProceedings of the 12th ACM Conference on Recommender Systems10.1145/3240323.3240363(338-346)Online publication date: 27-Sep-2018
https://dl.acm.org/doi/10.1145/3240323.3240363
Zhang LLiu PGulla JLee DSastry NWeber I(2018)A Deep Joint Network for Session-based News Recommendations with Contextual AugmentationProceedings of the 29th on Hypertext and Social Media10.1145/3209542.3209557(201-209)Online publication date: 3-Jul-2018
https://dl.acm.org/doi/10.1145/3209542.3209557
Epure EKille BIngvaldsen JDeneckere RSalinesi CAlbayrak SCremonesi PRicci FBerkovsky STuzhilin A(2017)Recommending Personalized News in Short User SessionsProceedings of the Eleventh ACM Conference on Recommender Systems10.1145/3109859.3109894(121-129)Online publication date: 27-Aug-2017
https://dl.acm.org/doi/10.1145/3109859.3109894
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