Psychology-informed Recommender Systems

IF 8.3 2区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Foundations and Trends in Information Retrieval Pub Date : 2021-12-06 DOI:10.1561/1500000090

E. Lex, Dominik Kowald, Paul Seitlinger, Thi Ngoc Trang Tran, A. Felfernig, M. Schedl

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引用次数: 32

Abstract

Personalized recommender systems have become indispensable in today’s online world. Most of today’s recommendation algorithms are data-driven and based on behavioral data. While such systems can produce useful recommendations, they are often uninterpretable, black-box models, which do not incorporate the underlying cognitive reasons for user behavior in the algorithms’ design. The aim of this survey is to present a thorough review of the state of the art of recommender systems that leverage psychological constructs and theories to model and predict user behavior and improve the recommendation process. We call such systems psychology-informed recommender systems. The survey identifies three categories of psychology-informed recommender systems: cognition-inspired, personality-aware, and affectaware recommender systems. Moreover, for each category, Elisabeth Lex, Dominik Kowald, Paul Seitlinger, Thi Ngoc Trang Tran, Alexander Felfernig and Markus Schedl (2021), “Psychology-informed Recommender Systems”, Foundations and Trends® in Information Retrieval: Vol. 15, No. 2, pp 134–242. DOI: 10.1561/1500000090. Full text available at: http://dx.doi.org/10.1561/1500000090

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基于心理学的推荐系统

个性化推荐系统在当今的网络世界中已经不可或缺。今天的大多数推荐算法都是数据驱动的，基于行为数据。虽然这样的系统可以产生有用的建议，但它们通常是不可解释的黑箱模型，没有在算法设计中纳入用户行为的潜在认知原因。本调查的目的是对推荐系统的现状进行全面的回顾，这些系统利用心理学结构和理论来建模和预测用户行为，并改进推荐过程。我们称这种系统为基于心理的推荐系统。该调查确定了三类基于心理学的推荐系统:认知启发型、个性感知型和情感感知型推荐系统。此外，对于每个类别，Elisabeth Lex, Dominik Kowald, Paul Seitlinger, Thi Ngoc Trang Tran, Alexander felferning和Markus Schedl(2021)，“心理通知推荐系统”，信息检索的基础和趋势®:第15卷，第2期，第134-242页。DOI: 10.1561 / 1500000090。全文可在:http://dx.doi.org/10.1561/1500000090

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来源期刊

Foundations and Trends in Information Retrieval COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

39.10

自引率

0.00%

发文量

期刊介绍： The surge in research across all domains in the past decade has resulted in a plethora of new publications, causing an exponential growth in published research. Navigating through this extensive literature and staying current has become a time-consuming challenge. While electronic publishing provides instant access to more articles than ever, discerning the essential ones for a comprehensive understanding of any topic remains an issue. To tackle this, Foundations and Trends® in Information Retrieval - FnTIR - addresses the problem by publishing high-quality survey and tutorial monographs in the field. Each issue of Foundations and Trends® in Information Retrieval - FnT IR features a 50-100 page monograph authored by research leaders, covering tutorial subjects, research retrospectives, and survey papers that provide state-of-the-art reviews within the scope of the journal.