research-article

Context-Aware Recommendation Using Role-Based Trust Network

Authors:

Jilei TianAuthors Info & Claims

ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 10, Issue 2

Article No.: 13, Pages 1 - 25

https://doi.org/10.1145/2751562

Published: 12 October 2015 Publication History

Abstract

Recommender systems have been studied comprehensively in both academic and industrial fields over the past decade. As user interests can be affected by context at any time and any place in mobile scenarios, rich context information becomes more and more important for personalized context-aware recommendations. Although existing context-aware recommender systems can make context-aware recommendations to some extent, they suffer several inherent weaknesses: (1) Users’ context-aware interests are not modeled realistically, which reduces the recommendation quality; (2) Current context-aware recommender systems ignore trust relations among users. Trust relations are actually context-aware and associated with certain aspects (i.e., categories of items) in mobile scenarios. In this article, we define a term role to model common context-aware interests among a group of users. We propose an efficient role mining algorithm to mine roles from a “user-context-behavior” matrix, and a role-based trust model to calculate context-aware trust value between two users. During online recommendation, given a user u in a context c, an efficient weighted set similarity query (WSSQ) algorithm is designed to build u’s role-based trust network in context c. Finally, we make recommendations to u based on u’s role-based trust network by considering both context-aware roles and trust relations. Extensive experiments demonstrate that our recommendation approach outperforms the state-of-the-art methods in both effectiveness and efficiency.

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Cited By

Lakehal AAlti ARoose P(2022)Novel Semantic-Based Probabilistic Context Aware Approach for Situations Enrichment and AdaptationApplied Sciences10.3390/app1202073212:2(732)Online publication date: 12-Jan-2022
https://doi.org/10.3390/app12020732
Fu ZYu LNiu X(2022)TRACE: Travel Reinforcement Recommendation Based on Location-Aware Context ExtractionACM Transactions on Knowledge Discovery from Data10.1145/348704716:4(1-22)Online publication date: 8-Jan-2022
https://dl.acm.org/doi/10.1145/3487047
Arour KDridi R(2022)Contextual Recommender Systems in Business from Models to ExperimentsMachine Learning and Data Analytics for Solving Business Problems10.1007/978-3-031-18483-3_7(115-140)Online publication date: 23-Sep-2022
https://doi.org/10.1007/978-3-031-18483-3_7
Show More Cited By

Index Terms

Context-Aware Recommendation Using Role-Based Trust Network
1. Information systems
  1. Information systems applications
    1. Data mining

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Published In

cover image ACM Transactions on Knowledge Discovery from Data

ACM Transactions on Knowledge Discovery from Data Volume 10, Issue 2

October 2015

291 pages

ISSN:1556-4681

EISSN:1556-472X

DOI:10.1145/2835206

Editor:
Philip S. Yu
University of Illinois at Chicago, USA

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Copyright © 2015 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 October 2015

Accepted: 01 March 2015

Revised: 01 January 2015

Received: 01 April 2013

Published in TKDD Volume 10, Issue 2

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National High-tech R&D Program
Shenzhen development Foundation
National Natural Science Foundation of China

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Cited By

Lakehal AAlti ARoose P(2022)Novel Semantic-Based Probabilistic Context Aware Approach for Situations Enrichment and AdaptationApplied Sciences10.3390/app1202073212:2(732)Online publication date: 12-Jan-2022
https://doi.org/10.3390/app12020732
Fu ZYu LNiu X(2022)TRACE: Travel Reinforcement Recommendation Based on Location-Aware Context ExtractionACM Transactions on Knowledge Discovery from Data10.1145/348704716:4(1-22)Online publication date: 8-Jan-2022
https://dl.acm.org/doi/10.1145/3487047
Arour KDridi R(2022)Contextual Recommender Systems in Business from Models to ExperimentsMachine Learning and Data Analytics for Solving Business Problems10.1007/978-3-031-18483-3_7(115-140)Online publication date: 23-Sep-2022
https://doi.org/10.1007/978-3-031-18483-3_7
Li LChu YLiu GWu X(2019)Multi-Objective Optimization-Based Networked Multi-Label Active LearningJournal of Database Management10.4018/JDM.201904010130:2(1-26)Online publication date: 1-Apr-2019
https://doi.org/10.4018/JDM.2019040101
Wang JZhu ZLiu JWang CXu Y(2019)An Approach of Role Updating in Context-Aware Role MiningSecuring the Internet of Things10.4018/978-1-5225-9866-4.ch066(1443-1464)Online publication date: 6-Sep-2019
https://doi.org/10.4018/978-1-5225-9866-4.ch066
Liu SChen ZLi X(2019)Time-Semantic-Aware Poisson Tensor Factorization Approach for Scalable Hotel RecommendationInformation Sciences10.1016/j.ins.2019.07.068Online publication date: Jul-2019
https://doi.org/10.1016/j.ins.2019.07.068
Chen GZhu FHeng P(2018)Large-Scale Bayesian Probabilistic Matrix Factorization with Memo-Free Distributed Variational InferenceACM Transactions on Knowledge Discovery from Data10.1145/316188612:3(1-24)Online publication date: 23-Jan-2018
https://dl.acm.org/doi/10.1145/3161886
Lakehal AAlti ALaborie SPhilippe R(2018)Ontology-based Context-aware Recommendation Approach For Dynamic Situations Enrichment2018 13th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)10.1109/SMAP.2018.8501880(81-86)Online publication date: Sep-2018
https://doi.org/10.1109/SMAP.2018.8501880
Villegas NSnchez CDaz-Cely JTamura G(2018)Characterizing context-aware recommender systemsKnowledge-Based Systems10.1016/j.knosys.2017.11.003140:C(173-200)Online publication date: 15-Jan-2018
https://dl.acm.org/doi/10.1016/j.knosys.2017.11.003
Xu KZhang WYan Z(2018)A privacy-preserving mobile application recommender system based on trust evaluationJournal of Computational Science10.1016/j.jocs.2018.04.00126(87-107)Online publication date: May-2018
https://doi.org/10.1016/j.jocs.2018.04.001
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