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Perceptual Relational Attributes: Navigating and Discovering Shared Perspectives from User-Generated Reviews

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2019

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Gesellschaft für Informatik, Bonn

Zusammenfassung

Effectively modelling and querying experience items like movies, books, or games in databases is challenging because these items are better described by their resulting user experience or perceived properties than by factual attributes. However, such information is often subjective, disputed, or unclear. Thus, social judgments like comments, reviews, discussions, or ratings have become a ubiquitous component of most Web applications dealing with such items, especially in the e-commerce domain. However, they usually do not play major role in the query process, and are typically just shown to the user. In this paper, we will discuss how to use unstructured user reviews to build a structured semantic representation of database items such that these perceptual attributes are (at least implicitly) represented and usable for navigational queries. Especially, we argue that a central challenge when extracting perceptual attributes from social judgments is respecting the subjectivity of expressed opinions. We claim that no representation consisting of only a single tuple will be sufficient. Instead, such systems should aim at discovering shared perspectives, representing dominant perceptions and opinions, and exploiting those perspectives for query processing.

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Lofi, Christoph; Valle Torre, Manuel; Ye, Mengmeng (2019): Perceptual Relational Attributes: Navigating and Discovering Shared Perspectives from User-Generated Reviews. BTW 2019. DOI: 10.18420/btw2019-11. Gesellschaft für Informatik, Bonn. PISSN: 1617-5468. ISBN: 978-3-88579-683-1. pp. 169-189. Wissenschaftliche Beiträge. Rostock. 4.-8. März 2019

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