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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
Moreover, ExpGA only requires prediction probabilities of the tested model, resulting in a better generalization capability to various models.  ...  Benefiting from this combination of explanation results and GA, ExpGA is both efficient and effective to detect discriminatory individuals.  ...  The novelty of ExpGA is the combination of explanation results and GA, thus determining its high efficiency and effectiveness in discriminatory sample detection.  ... 
arXiv:2205.08335v1 fatcat:kwcxbsoif5ct3cq4m4i77rwee4

Towards understandable personalized recommendations: Hybrid explanations

Martin Svrcek, Michal Kompan, Maria Bielikova
2018 Computer Science and Information Systems  
Therefore, it is important to make recommendations transparent and understandable to users. To address these problems, we propose a novel hybrid method of personalized explanation of recommendations.  ...  Nowadays, personalized recommendations are widely used and popular. There are a lot of systems in various fields, which use recommendations for different purposes.  ...  VG 1/0646/15 and VG 1/0667/18, and is the partial result of the Research & Development Operational Programme for the projects ITMS 26240220084 and ITMS 26240220039, co-funded by the European Regional Development  ... 
doi:10.2298/csis171217012s fatcat:lp6htzlmdrbw5ktdjewtkr3ufy

Context Style Explanation for Recommender Systems

Masahiro Sato, Koki Nagatani, Takashi Sonoda, Qian Zhang, Tomoko Ohkuma
2019 Journal of Information Processing  
Recommender systems support users by helping them choose items, and explanations for the recommendations further enhance such support.  ...  We evaluate the persuasiveness and usefulness of the context-style explanation by a crowdsourcing-based user study in a restaurant recommendation setting.  ...  Her recent research interest is recommender system and personalization. Tomoko Ohkuma received her M.S. degree from Keio University in 1996. In 1996, she joined Fuji Xerox.  ... 
doi:10.2197/ipsjjip.27.720 fatcat:hnlgmbfarref5eme62bym4q5f4

A generalized taxonomy of explanations styles for traditional and social recommender systems

Alexis Papadimitriou, Panagiotis Symeonidis, Yannis Manolopoulos
2011 Data mining and knowledge discovery  
Moreover, since there is inadequate research in the impact of social web in contemporary recommender systems and their explanation styles, we study new emerged social recommender systems i.e.  ...  Up until now, the type of an explanation style was considered in accordance to the recommender system that employed it.  ...  In Sect. 1.1 we define a generalized taxonomy of explanation styles. Section 2 presents the aforementioned explanation styles by demonstrating their usage in various recommender systems.  ... 
doi:10.1007/s10618-011-0215-0 fatcat:3jp3b4muz5fm3neqfuk7ekwzru

Incorporating Phrase-level Sentiment Analysis on Textual Reviews for Personalized Recommendation

Yongfeng Zhang
2015 Proceedings of the Eighth ACM International Conference on Web Search and Data Mining - WSDM '15  
of recommendation, and the automatic generation of user or item profiles.  ...  In this research, we stress the importance of incorporating textual reviews for recommendation through phrase-level sentiment analysis, and further investigate the role that the texts play in various important  ...  generation for hybrid recommender systems.  ... 
doi:10.1145/2684822.2697033 dblp:conf/wsdm/Zhang15 fatcat:75nhsktyuzam3ggbyrg3you56m

TasteWeights

Svetlin Bostandjiev, John O'Donovan, Tobias Höllerer
2012 Proceedings of the sixth ACM conference on Recommender systems - RecSys '12  
The system employs hybrid techniques from traditional recommender system literature, in addition to a novel interactive interface which serves to explain the recommendation process and elicit preferences  ...  This paper presents an interactive hybrid recommendation system that generates item predictions from multiple social and semantic web resources, such as Wikipedia, Facebook, and Twitter.  ...  RELATED WORK Research related to this work falls into the categories of hybrid recommender systems and the role of interaction and visualization for recommendation systems in general.  ... 
doi:10.1145/2365952.2365964 dblp:conf/recsys/BostandjievOH12 fatcat:3drt2wbo2zcknohqiszrjth6ku

ExMrec2vec: Explainable Movie Recommender System based on Word2vec

Amina SAMIH, Abderrahim GHADI, Abdelhadi FENNAN
2021 International Journal of Advanced Computer Science and Applications  
Hence the presence of recommender systems in many areas, in particular, movies recommendations.  ...  This work aims to improve the quality of recommendation and the simplicity of recommendation explanation based on the word2vec graph embeddings model.  ...  Second, the explanations provided are complex, unintuitive, and hard to understand by an average user (he needs the technical background to understand explanations). VI.  ... 
doi:10.14569/ijacsa.2021.0120876 fatcat:67zged2ubrabrdkthuoyn3md7a

Foundations of Explainable Knowledge-Enabled Systems [article]

Shruthi Chari, Daniel M. Gruen, Oshani Seneviratne, Deborah L. McGuinness
2020 arXiv   pre-print
With the proliferation of AI-enabled systems in sometimes critical settings, there is a need for them to be explainable to end-users and decision-makers.  ...  Additionally, borrowing from the strengths of past approaches and identifying gaps needed to make explanations user- and context-focused, we propose new definitions for explanations and explainable knowledge-enabled  ...  We thank our colleagues from IBM Research, Amar Das, Morgan Foreman and Ching-Hua Chen, and from RPI, James P. McCusker, and Rebecca Cowan, who greatly assisted the research and document preparation.  ... 
arXiv:2003.07520v1 fatcat:pz54e4ag35hf3osr7dfbmhb4ze

Social media recommendation based on people and tags

Ido Guy, Naama Zwerdling, Inbal Ronen, David Carmel, Erel Uziel
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
Each recommended item is accompanied by an explanation that includes the people and tags that led to its recommendation, as well as their relationships with the user and the item.  ...  We study personalized item recommendation within an enterprise social media application suite that includes blogs, bookmarks, communities, wikis, and shared files.  ...  Our system can be viewed as a variation of a hybrid CF-CB recommender system, in which related people and tags are used analogously to traditional CF and CB systems, respectively.  ... 
doi:10.1145/1835449.1835484 dblp:conf/sigir/GuyZRCU10 fatcat:26vyau5gp5dr3iu3fezeyyib3y

Online Recommendation Systems in a B2C E-Commerce Context: A Review and Future Directions

Seth Li, Elena Karahanna
2015 Journal of the AIS  
As Häubl and Thrifts (2000) discuss, RS (which they term "recommendation agent") is a specific type of interactive decision aid tool, which can generate personalized recommendations based on a consumer's  ...  Using a recommendation process theoretical framework, we categorize these studies in three major areas addressed by RS research: understanding consumers, delivering recommendations, and the impacts of  ...  Acknowledgements We thank the Senior Editor Choon-Ling Sia and the two anonymous reviewers for their feedback and their support during the review process.  ... 
doi:10.17705/1jais.00389 fatcat:4f6uhejzirejjb7xfn4syydchu

Each to his own

Bart P. Knijnenburg, Niels J.M. Reijmer, Martijn C. Willemsen
2011 Proceedings of the fifth ACM conference on Recommender systems - RecSys '11  
In an online experiment with an energy-saving recommender system the interaction methods are compared in terms of perceived control, understandability, trust in the system, user interface satisfaction,  ...  The results show that most users (and particularly domain experts) are most satisfied with a hybrid recommender that combines implicit and explicit preference elicitation, but that novices and maximizers  ...  ACKNOWLEDGEMENTS We thank Alfred Kobsa and Robin Keller for their extensive feedback on several early drafts of this paper.  ... 
doi:10.1145/2043932.2043960 dblp:conf/recsys/KnijnenburgRW11 fatcat:llyvh3g7vrf6bdyaa2jeyi5ddm

A TV Program Recommender Framework

Na Chang, Mhd Irvan, Takao Terano
2013 Procedia Computer Science  
In addition, we also address several issues, such as accuracy, diversity, novelty, explanation and group recommendations, which are important in building a TV program recommender system.  ...  In the area of intelligent systems, research about recommender systems is a critical topic and has been applied in many fields. In this paper, we focus on TV program recommender systems.  ...  systems in terms of accuracy, diversity, novelty, explanation and group recommendation.  ... 
doi:10.1016/j.procs.2013.09.136 fatcat:dj2jdwrsjzecjnba4a2zfcb26m

A Hybrid, Multi-dimensional Recommender for Journal Articles in a Scientific Digital Library

Andre Vellino, David Zeber
2007 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops  
[16] go further and show how explanations can help users understand the remaining recommendation opportunities if the current recommendation doesn't match their interest.  ...  Hybrid Systems Hybrid approaches take various forms, which are neatly summarized by Burke [9] and Adomavicius [1] .  ... 
doi:10.1109/wi-iatw.2007.29 fatcat:cvsml2p3grallbly4w2x4zvijm

A Hybrid, Multi-dimensional Recommender for Journal Articles in a Scientific Digital Library

Andre Vellino, David Zeber
2007 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops  
[16] go further and show how explanations can help users understand the remaining recommendation opportunities if the current recommendation doesn't match their interest.  ...  Hybrid Systems Hybrid approaches take various forms, which are neatly summarized by Burke [9] and Adomavicius [1] .  ... 
doi:10.1109/wiiatw.2007.4427552 dblp:conf/iat/VellinoZ07 fatcat:zqcxjkzau5c7rh3hhjkuijfitm

Explanations of recommendations

Nava Tintarev
2007 Proceedings of the 2007 ACM conference on Recommender systems - RecSys '07  
We will consider both an explanation's content and its presentation. As a domain, we are currently investigating explanations for a movie recommender, and developing a prototype system.  ...  We have identified seven different aims of explanations, and in this thesis we will consider how explanations can be optimized for some of these aims.  ...  However, the definition of a good explanation is still largely open and depends on the general aim of the recommender system.  ... 
doi:10.1145/1297231.1297275 dblp:conf/recsys/Tintarev07 fatcat:lerzs33i4nds7atjfwoau5jjuu
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