Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations

Veronika Bogina; Julia Sheidin; Tsvi Kuflik; Shlomo Berkovsky

doi:10.1145/3399715.3399813

Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations

Veronika Bogina, Julia Sheidin, Tsvi Kuflik, Shlomo Berkovsky

Department of Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

There is an increasing evidence that data visualization is an important and useful tool for quick understanding and filtering of large amounts of data. In this paper, we contribute to this body of work with a study that compares chord and ranked list for presentation of a temporal TV program genre similarity in next-program recommendations. We consider genre similarity based on the similarity of temporal viewing patterns. We discover that chord presentation allows users to see the whole picture and improves their ability to choose items beyond the ranked list of top similar items. We believe that similarity visualization may be useful for the provision of both the recommendations and their explanations to the end users.

Original language	English
Title of host publication	Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020
Editors	Genny Tortora, Giuliana Vitiello, Marco Winckler
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450375351
DOIs	https://doi.org/10.1145/3399715.3399813
State	Published - 28 Sep 2020
Event	2020 International Conference on Advanced Visual Interfaces, AVI 2020 - Salerno, Italy Duration: 28 Sep 2020 → 2 Oct 2020

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	2020 International Conference on Advanced Visual Interfaces, AVI 2020
Country/Territory	Italy
City	Salerno
Period	28/09/20 → 2/10/20

Bibliographical note

Publisher Copyright:
© 2020 ACM.

Keywords

Visualization
recommender system
similarity

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3399715.3399813

Cite this

Bogina, V., Sheidin, J., Kuflik, T., & Berkovsky, S. (2020). Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations. In G. Tortora, G. Vitiello, & M. Winckler (Eds.), Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3399715.3399813

Bogina, Veronika ; Sheidin, Julia ; Kuflik, Tsvi et al. / Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations. Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020. editor / Genny Tortora ; Giuliana Vitiello ; Marco Winckler. Association for Computing Machinery, 2020. (ACM International Conference Proceeding Series).

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title = "Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations",

abstract = "There is an increasing evidence that data visualization is an important and useful tool for quick understanding and filtering of large amounts of data. In this paper, we contribute to this body of work with a study that compares chord and ranked list for presentation of a temporal TV program genre similarity in next-program recommendations. We consider genre similarity based on the similarity of temporal viewing patterns. We discover that chord presentation allows users to see the whole picture and improves their ability to choose items beyond the ranked list of top similar items. We believe that similarity visualization may be useful for the provision of both the recommendations and their explanations to the end users.",

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author = "Veronika Bogina and Julia Sheidin and Tsvi Kuflik and Shlomo Berkovsky",

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year = "2020",

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doi = "10.1145/3399715.3399813",

language = "English",

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Bogina, V, Sheidin, J, Kuflik, T & Berkovsky, S 2020, Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations. in G Tortora, G Vitiello & M Winckler (eds), Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020. ACM International Conference Proceeding Series, Association for Computing Machinery, 2020 International Conference on Advanced Visual Interfaces, AVI 2020, Salerno, Italy, 28/09/20. https://doi.org/10.1145/3399715.3399813

Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations. / Bogina, Veronika; Sheidin, Julia; Kuflik, Tsvi et al.
Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020. ed. / Genny Tortora; Giuliana Vitiello; Marco Winckler. Association for Computing Machinery, 2020. (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Bogina V, Sheidin J, Kuflik T, Berkovsky S. Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations. In Tortora G, Vitiello G, Winckler M, editors, Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020. Association for Computing Machinery. 2020. (ACM International Conference Proceeding Series). doi: 10.1145/3399715.3399813

Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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