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We study the similarity search problem which aims to find the similar query results according to a set of given data and a query string. To balance the result number and result quality, we combine query result diversity with query…

Databases · Computer Science 2017-02-24 Ruoxi Shi , Hongzhi Wang , Tao Wang , Yutai Hou , Yiwen Tang

Collective behavior in online social media and networks is known to be capable of generating non-intuitive dynamics associated with crowd wisdom and herd behaviour. Even though these topics have been well-studied in social science, the…

Signal Processing · Electrical Eng. & Systems 2018-05-16 Fernando Rosas , Kwang-Cheng Chen , Deniz Gunduz

As artificial intelligence becomes more powerful and a ubiquitous presence in daily life, it is imperative to understand and manage the impact of AI systems on our lives and decisions. Modern ML systems often change user behavior (e.g.…

Artificial Intelligence · Computer Science 2022-03-31 Matija Franklin , Hal Ashton , Rebecca Gorman , Stuart Armstrong

Various theoretical and empirical studies have accounted for why humans cooperate in competitive environments. Although prior work has revealed that network structure and multiplex interactions can promote cooperation, most theory assumes…

Physics and Society · Physics 2026-01-05 Jnanajyoti Bhaumik , Naoki Masuda

Natural and human-made common goods present key challenges due to their susceptibility to degradation, overuse, or congestion. We explore the self-organisation of their usage when individuals have access to several available commons but…

Multiagent Systems · Computer Science 2025-04-11 Diogo L. Pires , Vincenzo Mancuso , Paolo Castagno , Marco Ajmone Marsan

With the rapid development of recommender systems, accuracy is no longer the only golden criterion for evaluating whether the recommendation results are satisfying or not. In recent years, diversity has gained tremendous attention in…

Information Retrieval · Computer Science 2019-05-17 Qiong Wu , Yong Liu , Chunyan Miao , Yin Zhao , Lu Guan , Haihong Tang

We study group decision making with changing preferences as a Markov Decision Process. We are motivated by the increasing prevalence of automated decision-making systems when making choices for groups of people over time. Our main…

Multiagent Systems · Computer Science 2020-11-06 Kshitij Kulkarni , Sven Neth

In search and recommendation, diversifying the multi-aspect search results could help with reducing redundancy, and promoting results that might not be shown otherwise. Many previous methods have been proposed for this task. However,…

Information Retrieval · Computer Science 2021-05-24 Jianghong Zhou , Eugene Agichtein , Surya Kallumadi

Suppose that we wish to estimate a user's preference vector $w$ from paired comparisons of the form "does user $w$ prefer item $p$ or item $q$?," where both the user and items are embedded in a low-dimensional Euclidean space with distances…

Machine Learning · Statistics 2019-05-27 Gregory H. Canal , Andrew K. Massimino , Mark A. Davenport , Christopher J. Rozell

The public goods game is a famous example illustrating the tragedy of the commons. In this game cooperating individuals contribute to a pool, which in turn is distributed to all members of the group, including defectors who reap the same…

Physics and Society · Physics 2020-04-24 Arend Hintze , Jochen Staudacher , Katja Gelhar , Alexander Pothmann , Juliana Rasch , Daniel Wildegger

Modern recommendation systems ought to benefit by probing for and learning from delayed feedback. Research has tended to focus on learning from a user's response to a single recommendation. Such work, which leverages methods of supervised…

Information Retrieval · Computer Science 2023-08-01 Zheqing Zhu , Benjamin Van Roy

We develop a model of social media in which users produce different types of content and choose whom to follow. Even when abstracting from algorithmic bias, linking costs shape networks and polarization. In the welfare-maximizing…

Theoretical Economics · Economics 2026-02-26 Patrick Allmis , Luca Paolo Merlino

It is common in recommendation systems that users both consume and produce information as they make strategic choices under uncertainty. While a social planner would balance "exploration" and "exploitation" using a multi-armed bandit…

Computer Science and Game Theory · Computer Science 2019-02-20 Nicole Immorlica , Jieming Mao , Aleksandrs Slivkins , Zhiwei Steven Wu

In recommendation literature, explainability and fairness are becoming two prominent perspectives to consider. However, prior works have mostly addressed them separately, for instance by explaining to consumers why a certain item was…

Information Retrieval · Computer Science 2023-08-24 Ludovico Boratto , Francesco Fabbri , Gianni Fenu , Mirko Marras , Giacomo Medda

Content creators compete for exposure on recommendation platforms, and such strategic behavior leads to a dynamic shift over the content distribution. However, how the creators' competition impacts user welfare and how the relevance-driven…

Computer Science and Game Theory · Computer Science 2023-05-04 Fan Yao , Chuanhao Li , Denis Nekipelov , Hongning Wang , Haifeng Xu

Recommender systems are promising ways to filter the overabundant information in modern society. Their algorithms help individuals to explore decent items, but it is unclear how they allocate popularity among items. In this paper, we…

Physics and Society · Physics 2015-05-28 An Zeng , Chi Ho Yeung , Mingsheng Shang , Yi-Cheng Zhang

We investigate market forces that would lead to the emergence of new classes of players in the sponsored search market. We report a 3-fold diversification triggered by two inherent features of the sponsored search market, namely, capacity…

Computer Science and Game Theory · Computer Science 2007-11-05 Sudhir Kumar Singh , Vwani P. Roychowdhury , Himawan Gunadhi , Behnam A. Rezaei

We study the power of item-pricing as a tool for approximately optimizing social welfare in a combinatorial market. We consider markets with $m$ indivisible items and $n$ buyers. The goal is to set prices to the items so that, when agents…

Computer Science and Game Theory · Computer Science 2015-11-10 Michal Feldman , Nick Gravin , Brendan Lucier

We examine the implications of consumer privacy when preferences today depend upon past consumption choices, and consumers shop from different sellers in each period. Although consumers are ex ante identical, their initial consumption…

Theoretical Economics · Economics 2024-09-17 V. Bhaskar , Nikita Roketskiy

An important benefit of multi-objective search is that it maintains a diverse population of candidates, which helps in deceptive problems in particular. Not all diversity is useful, however: candidates that optimize only one objective while…

Neural and Evolutionary Computing · Computer Science 2019-08-06 Hormoz Shahrzad , Babak Hodjat , Camille Dollé , Andrei Denissov , Simon Lau , Donn Goodhew , Justin Dyer , Risto Miikkulainen
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