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Exploring Ratings in Subjective Databases

Abstract : Subjective data links people to content items and reflects who likes or dislikes what. The valuable information this data contains is virtually infinite and satisfies various information needs. Yet, as of today, dedicated tools to explore this data are lacking. In this paper, we develop a framework for Subjective Data Exploration (SDE). Our solution enables the joint exploration of items, people, and people's opinions on items, in a guided multi-step process where each step aggregates the most useful and diverse trends in the form of rating maps. Because of the large search space of possible rating maps, we leverage pruning strategies based on confidence intervals and multi-armed bandits. Our large-scale experiments with human subjects and real datasets, demonstrate the need for dedicated SDE frameworks and the effectiveness and efficiency of our approach. CCS CONCEPTS • Human-centered computing → Systems and tools for interaction design; Visualization systems and tools.
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https://hal.archives-ouvertes.fr/hal-03379586
Contributor : Sihem Amer-Yahia Connect in order to contact the contributor
Submitted on : Friday, October 15, 2021 - 9:24:54 AM
Last modification on : Tuesday, November 9, 2021 - 9:25:48 AM

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Sihem Amer-Yahia, Tova Milo, Brit Youngmann. Exploring Ratings in Subjective Databases. SIGMOD/PODS '21: International Conference on Management of Data, Apr 2021, Virtual Event China, France. pp.62-75, ⟨10.1145/3448016.3457259⟩. ⟨hal-03379586⟩

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