Diversity-enhanced recommendation interface and evaluation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The beyond accuracy user experience of using recommender system is drawing more and more attention. For example, the system interface has been shown to associate positively with overall levels of user satisfaction. However, little is known about how the interfaces can constitute the user experience and the social interactions. In this paper, I plan to propose a visual diversity-enhanced interface that supports the user to inspect and control the multi-relevance recommendations. The goal is to let the users explore the different relevance prospects of recommended items in parallel and to stress their diversity. Two preliminary user studies with real-life tasks were conducted to compare the visual interface to a standard ranked list interface. The users’ subjective evaluations show significant improvement in many metrics. I further show that the users explored a diverse set of recommended items while experiencing an increase in overall user satisfaction. A user-centered evaluation was used to reveal the mediating effects between the subjective and objective conceptual components. The future plans are discussed to extend the current findings.

Original languageEnglish (US)
Title of host publicationCHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages360-362
Number of pages3
ISBN (Electronic)9781450349253
DOIs
StatePublished - Feb 1 2018
Event3rd ACM SIGIR Conference on Human Information Interaction and Retrieval, CHIIR 2018 - New Brunswick, United States
Duration: Mar 11 2018Mar 15 2018

Publication series

NameCHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval
Volume2018-March

Other

Other3rd ACM SIGIR Conference on Human Information Interaction and Retrieval, CHIIR 2018
CountryUnited States
CityNew Brunswick
Period3/11/183/15/18

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Recommender systems

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Information Systems

Cite this

Tsai, C-H. (2018). Diversity-enhanced recommendation interface and evaluation. In CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval (pp. 360-362). (CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval; Vol. 2018-March). Association for Computing Machinery, Inc. https://doi.org/10.1145/3176349.3176357
Tsai, Chun-Hua. / Diversity-enhanced recommendation interface and evaluation. CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval. Association for Computing Machinery, Inc, 2018. pp. 360-362 (CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval).
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abstract = "The beyond accuracy user experience of using recommender system is drawing more and more attention. For example, the system interface has been shown to associate positively with overall levels of user satisfaction. However, little is known about how the interfaces can constitute the user experience and the social interactions. In this paper, I plan to propose a visual diversity-enhanced interface that supports the user to inspect and control the multi-relevance recommendations. The goal is to let the users explore the different relevance prospects of recommended items in parallel and to stress their diversity. Two preliminary user studies with real-life tasks were conducted to compare the visual interface to a standard ranked list interface. The users’ subjective evaluations show significant improvement in many metrics. I further show that the users explored a diverse set of recommended items while experiencing an increase in overall user satisfaction. A user-centered evaluation was used to reveal the mediating effects between the subjective and objective conceptual components. The future plans are discussed to extend the current findings.",
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Tsai, C-H 2018, Diversity-enhanced recommendation interface and evaluation. in CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval. CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval, vol. 2018-March, Association for Computing Machinery, Inc, pp. 360-362, 3rd ACM SIGIR Conference on Human Information Interaction and Retrieval, CHIIR 2018, New Brunswick, United States, 3/11/18. https://doi.org/10.1145/3176349.3176357

Diversity-enhanced recommendation interface and evaluation. / Tsai, Chun-Hua.

CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval. Association for Computing Machinery, Inc, 2018. p. 360-362 (CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval; Vol. 2018-March).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Tsai C-H. Diversity-enhanced recommendation interface and evaluation. In CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval. Association for Computing Machinery, Inc. 2018. p. 360-362. (CHIIR 2018 - Proceedings of the 2018 Conference on Human Information Interaction and Retrieval). https://doi.org/10.1145/3176349.3176357