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Measuring "Why" in Recommender Systems: a Comprehensive Survey on the Evaluation of Explainable Recommendation
[article]
2022
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With this survey, we finally aim to provide a clear and comprehensive review on the evaluation of explainable recommendation. ...
A fundamental problem of explainable recommendation is how to evaluate the explanations. In the past few years, various evaluation strategies have been proposed. ...
The main contributions of this paper are summarized as follows: • We provide a systematic and comprehensive survey on the evaluation of explainable recommendation, which to the best of our knowledge, is ...
doi:10.48550/arxiv.2202.06466
fatcat:xat3nnrrg5epvfnzha5x3x3l2y
Towards reproducibility in recommender-systems research
2016
User modeling and user-adapted interaction
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In this article, we examine the challenge of reproducibility in recommender-system research. ...
For example, in one news-recommendation scenario, the performance of a content-based filtering approach was twice as high as the second-best approach, while in another scenario the same content-based filtering ...
This, in turn, would ease future research, increase the value of individual research contributions, and support the operators of recommender systems who seek the most effective recommendation approaches ...
doi:10.1007/s11257-016-9174-x
fatcat:xhcr64duqza73ipqjkgeavgi7a
A Survey of Explanations in Recommender Systems
2007
2007 IEEE 23rd International Conference on Data Engineering Workshop
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This paper provides a comprehensive review of explanations in recommender systems. ...
We highlight seven possible advantages of an explanation facility, and describe how existing measures can be used to evaluate the quality of explanations. ...
Below we describe previous evaluations of explanation facilities, supplemented with a description of how existing measures could be adapted to evaluate the explanation facility in a recommender system. ...
doi:10.1109/icdew.2007.4401070
dblp:conf/icde/TintarevM07
fatcat:dkq4va4pvjcmxpe3noetkes7si
PREFER Recommendations - Why, when and how to assess and use patient preferences in medical product decision-making
[article]
2022
Zenodo
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The PREFER Recommendations provide expert and evidence-based guidance from six years of research on when and how to design and conduct a patient preference study. ...
organisations in European countries and in the US. ...
on a DCE comprehension task. ...
doi:10.5281/zenodo.6470922
fatcat:od2totouxzh7jj4tjyd5hv5fhy
PREFER Recommendations - Why, when and how to assess and use patient preferences in medical product decision-making
[article]
2022
Zenodo
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The PREFER Recommendations provide expert and evidence-based guidance from six years of research on when and how to design and conduct a patient preference study. ...
organisations in European countries and in the US. ...
on a DCE comprehension task. ...
doi:10.5281/zenodo.6592304
fatcat:zy6b2cl3bjacrifzsnhilrzvse
Advances and Challenges in Conversational Recommender Systems: A Survey
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2101.09459v3 fatcat:x6irqgc7wfcmbonymeohls3dfaOther Versions
Recommender systems exploit interaction history to estimate user preference, having been heavily used in a wide range of industry applications. ...
The recent rise of conversational recommender systems (CRSs) changes this situation fundamentally. ...
Acknowledgments This work is supported by the National Natural Science Foundation of China (U19A2079, 61972372) and the National Key Research and Development Program of China (2020AAA0106000). ...
arXiv:2101.09459v6
fatcat:j7djzhrv6fazpogmnj7r4e4f2y
Graph Neural Networks in Recommender Systems: A Survey
[article]
2022
arXiv
pre-print
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2022 pre-print arXiv:2011.02260v3 fatcat:qe2oh6g22nalvkgrxqb2bgqvvyOther Versions
This article aims to provide a comprehensive review of recent research efforts on GNN-based recommender systems. ...
With the explosive growth of online information, recommender systems play a key role to alleviate such information overload. ...
Explainability Explainability is beneficial for recommender systems: on the one hand, explainable recommendations to users allow them to know why the items are recommended and could be persuasive; on the ...
arXiv:2011.02260v4
fatcat:hvk22yyid5bzjnzmzchyti25ja
Novelty and Diversity in Recommender Systems
[chapter]
2015
Recommender Systems Handbook
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We also propose a new formalization and unification of the way novelty and diversity are evaluated on Recommender Systems, considering rank and relevance as additional and meaningful aspects for the evaluation ...
In the present work we propose an Information Retrieval approach to the evaluation and enhacement of novelty and diversity in Recommender Systems. ...
For evaluation purposes, the authors measure the diversity of a recommendation list by a metric called intra-list similarity (ILS). ...
doi:10.1007/978-1-4899-7637-6_26
fatcat:53veooy4dzgzxcr3volnel46w4
Reputation-Enhanced Recommender Systems
[chapter]
2017
IFIP Advances in Information and Communication Technology
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Since the concept of reputationenhanced recommender systems has attracted considerable attention in recent years, the main aim of the paper is to provide a comprehensive survey of the approaches proposed ...
This paper goes beyond the commonly dominating focus on optimizing algorithms and instead follows the idea of enhancing recommender systems with reputation data. ...
The research leading to these results was supported by the "Bavarian State Ministry of Education, Science and the Arts" as part of the FORSEC research association. ...
doi:10.1007/978-3-319-59171-1_13
fatcat:ws53hxu25fdhphens5frnugcaa
User-Centric vs. System-Centric Evaluation of Recommender Systems
[chapter]
2013
Lecture Notes in Computer Science
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The quality of a RS can be defined from two perspectives: system-centric, in which quality measures (e.g., precision, recall) are evaluated using vast datasets of preferences and opinions on items previously ...
The paper investigates if a similar mismatch also exists in the domain of e-tourism. ...
This phenomenon could explain why users not receiving personalized recommendations take more initiative in changing the sorting of hotels in the list. ...
doi:10.1007/978-3-642-40477-1_21
fatcat:n75vmcnirvck7bxuclyac3p4wy
Graph Neural Networks in Recommender Systems: A Survey
2022
ACM Computing Surveys
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This article aims to provide a comprehensive review of recent research efforts on GNN-based recommender systems. ...
With the explosive growth of online information, recommender systems play a key role to alleviate such information overload. ...
ACKNOWLEDGEMENT This work is supported by NSFC (No. 61832001), Beijing Academy of Artiicial Intelligence (BAAI), and PKU-Tencent Joint Research Lab. ...
doi:10.1145/3535101
fatcat:hgv2tbx3k5hzbnkupwsysqwjmy
Measuring self-reported sunburn: challenges and recommendations
2001
Chronic Diseases in Canada
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Recommendations for measurement of sunburn and for further research are included. ...
Key issues that program evaluators and researchers should consider in determining the strengths and limitations of various definitions, measures and approaches are examined. ...
We wish to acknowledge the participants in the 1998 National Workshop on Measurement of Sun-Related Behaviours as well as the collegiality of those researchers who shared their unpublished reports and ...
pmid:11779421
fatcat:ely3yfynyvcsjjnxmhuf4m7czu
Current State and Future Trends in Location Recommender Systems
2017
International Journal of Information Technology and Computer Science
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For this purpose, topic pairs; "location and recommender system" and "location and recommendation system" were searched in the Web of Knowledge database. ...
It is expected that the issues presented in this paper will advance the discussion of next generation location recommendation systems. ...
Evaluation Techniques A crucial step of all recommender system research is choosing a right methodology to evaluate the quality of the recommendations. ...
doi:10.5815/ijitcs.2017.06.01
fatcat:rrz2xtgnkfeetd62v6dqh6nzeu
Why ask if you know? Acmg's potential errors in making Newborn screening (NBS) recommendations from using surveyed opinions for incidence scoring when actual data are available
2015
Value in Health
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A305 only reviewed oncology orphans thereby resulting in inconsistent access. Alternative funding mechanisms sometimes provide a temporary reimbursement fix in the UK. ...
CONCLUSIONS: Significant differences exist between the number of orphan drug approvals and time to access in the US vs. EU. ...
OBJECTIVES: In 2006, the American College of Medical Genetics (ACMG) recommended expanding NBS, relying largely on scoring from a stakeholder survey on 19 attributes of 84 rare conditions. ...
doi:10.1016/j.jval.2015.03.1778
fatcat:batnbguczzgwbdge2xkae7iynu
A systematic review and taxonomy of explanations in decision support and recommender systems
2017
User modeling and user-adapted interaction
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2020 pre-print arXiv:2006.08672v1 fatcat:2l4mk42qqzda5ntned5fvewidq
This is a family of systems that includes recommender systems, which is one of the most successful classes of advice-giving software in practice. ...
In this work, we systematically review the literature on explanations in advice-giving systems. ...
Acknowledgments The authors would like to thank Michael Jugovac for carefully proofreading this paper. Ingrid Nunes also would like to thank for research grants CNPq ...
doi:10.1007/s11257-017-9195-0
fatcat:zffwtjitfzcmhewinlyz6bxpxa
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