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| Multi Granularity Knowledge Organization Model for User Generated Content |
| Wang Zhongyi, Zheng Xin, Wang Keying |
| School of Information Management, Central China Normal University, Wuhan 430079 |
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Abstract As an important text resource of network information resources in the era of big data, user generated content (UGC) has received increasing attention from scholars in various fields. Compared with traditional texts, it is more difficult to organize massive and fragmented UGC texts. Aiming at the fragmentation characteristics of the UGC text, this study proposes a multi granularity knowledge organization model based on the knowledge element. By extracting fragmented UGC knowledge element and establishing multi granularity association and multi granularity index, the fragmented UGC is organized from point to surface and from part to whole. On the one hand, in the empirical research part, pieces of fragmented UGC text are related to “retrieval” to complete multi-granularity knowledge organization, and the user interface is provided to complete the knowledge retrieval service; on the other hand, the effectiveness and scientificity of the multi granularity knowledge organization model proposed in this paper are proved by comparative experiments.
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Received: 01 April 2021
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