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Explanation-Guided Fairness Testing through Genetic Algorithm [article]

Ming Fan, Wenying Wei, Wuxia Jin, Zijiang Yang, Ting Liu
2022 arXiv   pre-print
The fairness characteristic is a critical attribute of trusted AI systems. A plethora of research has proposed diverse methods for individual fairness testing.  ...  Experiments on multiple real-world benchmarks, including tabular and text datasets, show that ExpGA presents higher efficiency and effectiveness than four state-of-the-art approaches.  ...  The evaluation experiments demonstrate that ExpGA can detect discriminatory samples much faster with a higher success rate than four state-of-the-art methods, both on the text and tabular benchmarks.  ... 
arXiv:2205.08335v1 fatcat:kwcxbsoif5ct3cq4m4i77rwee4

Pro-active Multi-Dimensional Recommender System using Multi-Agents

Hend Al Tair, Mohamed Jamal Zemerly, Mahmoud AL-Qutayri, Marcello Leida
2012 International Journal of Interactive Mobile Technologies  
The recommender system proposed in this paper uses multi-agents and multi-dimensional contextual information to achieve proactive behavior.  ...  recommender systems currently used in many applications, including tourism, tend to simply be reactive to user request.  ...  In this paper we propose a multi-agent recommender system that is based on multi-dimensional rating approach using the Knowledge-base Hybrid recommender system.  ... 
doi:10.3991/ijim.v6i3.2012 fatcat:phxrs7bctzg3xfdtnhvwm3pfrm

Multiple Choice Questions based Multi-Interest Policy Learning for Conversational Recommendation [article]

Yiming Zhang, Lingfei Wu, Qi Shen, Yitong Pang, Zhihua Wei, Fangli Xu, Bo Long, Jian Pei
2022 arXiv   pre-print
Conversational recommendation system (CRS) is able to obtain fine-grained and dynamic user preferences based on interactive dialogue. Previous CRS assumes that the user has a clear target item.  ...  As a result, we first propose a more realistic CRS learning setting, namely Multi-Interest Multi-round Conversational Recommendation, where users may have multiple interests in attribute instance combinations  ...  In MCR task, the system focuses on whether to ask attributes or make recommendations based on policy learning at each turn, and adjusts action flexibly via users' feedback, which aims to hit the target  ... 
arXiv:2112.11775v2 fatcat:756ch63bxndtlhgwxokyqupdlm

Multi-Criteria Recommender Systems [chapter]

Gediminas Adomavicius, YoungOk Kwon
2015 Recommender Systems Handbook  
This chapter aims to provide an overview of the class of multi-criteria recommender systems.  ...  Then, it focuses on the category of multi-criteria rating recommenders -techniques that provide recommendations by modelling a user's utility for an item as a vector of ratings along several criteria.  ...  Manouselis was funded with support by the European Commission and more specifically, the project ECP-2006-EDU-410012 "Organic.Edunet: A Multilingual Federation of Learning Repositories with Quality Content  ... 
doi:10.1007/978-1-4899-7637-6_25 fatcat:sqvrygjkarci3iugg6dn6n5xym

New Recommendation Techniques for Multicriteria Rating Systems

Gediminas Adomavicius, YoungOk Kwon
2007 IEEE Intelligent Systems  
While traditional single-rating recommender systems have been successful in a number of personalization applications, the research area of multi-criteria recommender systems has been largely untouched.  ...  In this paper we propose two new approaches -the similarity-based approach and the aggregation function-based approach -to incorporating and leveraging multi-criteria rating information in recommender  ...  This allowed the recommender systems to identify favorite content attributes (e.g., "comedy" movies) based on the content analysis of the previously rated items, and then also to recommend items to a user  ... 
doi:10.1109/mis.2007.58 fatcat:3ktpd24gwrhkrghayblvfg6gvi

Analysis and Classification of Multi-Criteria Recommender Systems

Nikos Manouselis, Constantina Costopoulou
2007 World wide web (Bussum)  
This paper proposes a Web-based tool that allows for simulated testing of a special class of multi-criteria recommender systems, namely multi-attribute collaborative filtering systems.  ...  More specifically, it introduces a number of collaborative filtering algorithms that are based on Multi-Attribute Utility Theory (MAUT), and presents the design and implementation of a Web-based tool termed  ...  She holds a BSc in Mathematics from the National and Kapodistrian University of Athens, Greece (1986), an MSc in Software Engineering from Cranfield Institute of Technology, UK (1989), and a PhD in Electrical  ... 
doi:10.1007/s11280-007-0019-8 fatcat:hx5tebe4tnbgfj2srfcn7kq3je

A BERT-Based Multi-Criteria Recommender System for Hotel Promotion Management

Yuanyuan Zhuang, Jaekyeong Kim
2021 Sustainability  
Based on this predicted ratings, a multi-criteria recommender system recommends personalized Top-N customers for each hotel.  ...  This study suggests a multi-criteria recommender system to recommend a suitable target customers for the hotel.  ...  Therefore, in this study, a multi-criteria recommender system is used in the recommendation process based on the similarity-based method in [36] . Nie et al.  ... 
doi:10.3390/su13148039 fatcat:hvcfenr3ibdsxozaxfmeh7l5ee

Layered Evaluation of Multi-Criteria Collaborative Filtering for Scientific Paper Recommendation

Nikos Manouselis, Katrien Verbert
2013 Procedia Computer Science  
Such multi-criteria recommendation approaches are researched as a paradigm for building intelligent systems that can be tailored to multiple interest indicators of end-users -such as combinations of implicit  ...  In this paper, we study how layered evaluation can be applied for the case of a multi-criteria recommendation service that we plan to deploy for paper recommendation using the Mendeley dataset.  ...  Katrien Verbert is a Post-doctoral Fellow of the Research Foundation -Flanders (FWO).  ... 
doi:10.1016/j.procs.2013.05.285 fatcat:vkzjilxcu5hazcrqcak5de4pdq

A Multi-attribute Collaborative Filtering Recommendation Algorithm Based on Improved Group Decision-Making [chapter]

Changrui Yu, Yan Luo, Kecheng Liu
2014 IFIP Advances in Information and Communication Technology  
The paper builds an evaluation model of user interest based on resource multi-attributes, proposes a modified Pearson-Compatibility multiattribute group decision-making algorithm, and introduces the algorithm  ...  Finally, the effectiveness of the algorithm is proved by an experiment of collaborative recommendation among multi-users based on virtual environment.  ...  Then an online multi-attribute rating system based on the movie database and a collaborative filtering recommendation system based on group-decision making are designed and developed.  ... 
doi:10.1007/978-3-642-55355-4_33 fatcat:deis63qtujfi3jtsmmkvjoz2zm

A Recommendation System for Cloud Services Selection Based on Intelligent Agents

Abid Mahmood, Umar Shoaib, M. Shahzad Sarfraz
2018 Indian Journal of Science and Technology  
Objectives: To provide a recommendation system for cloud services selection based on intelligent agents.  ...  In this study, we proposed a service selector system on computer trust merit of the cloud purveyor.  ...  So there is a need for recommendation/selection system or agent. 1 At its first step, the agent will group together similar services based on the attributes of services and assigning a similarity index  ... 
doi:10.17485/ijst/2018/v11i9/119843 fatcat:xoxz4kdc3rhbviopwhxeknknvi

A Multi Criteria Recommendation Engine Model for Cloud Renderfarm Services

Ruby Annette, Aisha Banu W, Subash Chandran P
2018 International Journal of Electrical and Computer Engineering (IJECE)  
This work proposes a multi criteria recommendation engine model for recommending these Cloud renderfarm services to animators.  ...  The services are recommended based on the functional requirements of the animation file to be rendered like the rendering software, plug-in required etc and the non functional Quality of Service (QoS)  ...  Multi Criteria Recommender Systems The systems that are based on the Multi Criteria Decision Making methods for generating the recommendations are called the Multi Criteria Recommender Systems.  ... 
doi:10.11591/ijece.v8i5.pp3214-3220 fatcat:wfyooh2jxncbra3cpsccaw7gr4

Recommender System Based on Algorithm of Bicluster Analysis RecBi [article]

Dmitry I. Ignatov, Jonas Poelmans, Vasily Zaharchuk
2012 arXiv   pre-print
In this paper we propose two new algorithms based on biclustering analysis, which can be used at the basis of a recommender system for educational orientation of Russian School graduates.  ...  The final version of this recommender system will be used by Higher School of Economics.  ...  One of the most recent innovations in recommender system research is applying methods based on biclustering.  ... 
arXiv:1202.2892v1 fatcat:wzcwpkmumnfezkgdw63myjnwse

Implementation of Simple Multi Attribute Rating Technique Method using Decision Support System Concept (Case Recommendation of Salon Place in Pematangsiantar City)

Indra Riyana Rahadjeng, Agus Perdana Windarto
2019 IJISTECH (International Journal Of Information System & Technology)  
This research can also be used as recommendations in the form of information in deciding whether consumers visit the salon or not based on research results.  ...  The method used in decision making is the SMART (Simple Multi Attribute Rating Technique) method.  ...  SMART Method SMART (Simple Multi Attribute Rating Technique) is a multi-criteria decision making technique based on the theory that each alternative consists of a number of criteria that have values and  ... 
doi:10.30645/ijistech.v3i1.29 fatcat:coy27et5qfevbmhx2xnwtoscqi

Advances and Challenges in Conversational Recommender Systems: A Survey [article]

Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke, Tat-Seng Chua
2021 arXiv   pre-print
We summarize the key challenges of developing CRSs in five directions: (1) Question-based user preference elicitation. (2) Multi-turn conversational recommendation strategies. (3) Dialogue understanding  ...  Based on these research directions, we discuss some future challenges and opportunities. We provide a road map for researchers from multiple communities to get started in this area.  ...  The critiquing-based recommender system is such a solution that is designed to elicit users' feedback on certain attributes, rather than items. Sounds good, let me try it!  ... 
arXiv:2101.09459v6 fatcat:j7djzhrv6fazpogmnj7r4e4f2y

Architecture for Context-Aware Pro-Active Recommender System

H. Al Tair, M. J. Zemerly, M. Al-Qutayri, M. Leida
2012 International Journal of Multimedia and Image Processing  
This paper presents architecture of a contextaware pro-active recommender system.  ...  The proposed recommender system provides recommendations pro-actively by using multi-agent technology.  ...  Integrating a multi-dimensional recommender system with a multi-agent system will lead to an enhancement of the pro-activity of recommender system especially for the tourism domain.  ... 
doi:10.20533/ijmip.2042.4647.2012.0016 fatcat:exddcl26drfpxhhzj6snviu4lu
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