Identifying Transmedia Works from User-Generated Knowledge Bases : Japanese Pop Culture Study Case
Résumé
As Japanese pop culture spreads worldwide, digital libraries compiling information about works through representative media (manga, anime, video games) emerge. Some of these works may share the same story, characters or universe, thus being part of a conceptual instance which we call a transmedia work in this paper. Transmedia works are abstract entities composed of works through several media linked together by semantic relationships. Identifying works belonging to the same trans-media work is still a challenge to enhance access, retrieval and organization of media in digital libraries. To overcome this challenge, semantic relationships between works should be identified. As no authority data yet describes semantic relationships between works, we need to find this information in knowledge bases generated by users such as Wikipedia. More precisely, we exploit DBpedia, Wikipedia's Linked Data counterpart , to respect the semantic web standards. In this paper, we present our method and experiment in building work entity datasets of Japanese pop culture (manga, anime and video games) and extracting relationships between these works in order to ease identification of transmedia works from the semantic data structure used in DBpedia. We also extract pertinent information to link works to bibliographic data in the future. We propose an evaluation of our contribution and demonstrate that we can easily and relevantly identify works belonging to the same transmedia work from user-generated knowledge bases.
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