文章基本信息

标题：SOCIA: Linked Open Data of Context behind Local Concerns for Supporting Public Participation
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作者：Shun Shiramatsu ; Tadachika Ozono ; Toramatsu Shintani 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2015
卷号：6
期号：2
DOI：10.14569/IJACSA.2015.060238
出版社：Science and Information Society (SAI)
摘要：To address public concerns that threat the sustain-ability of local societies, supporting public participation by shar-ing the background context behind these concerns is essentially important. We designed a SOCIA ontology, which was a linked data model, for sharing context behind local concerns with two approaches: (1) structuring Web news articles and microblogs about local concerns on the basis of geographical regions and events that were referred to by content, and (2) structuring public issues and their solutions as public goals. We moreover built a SOCIA dataset, which was a linked open dataset, on the basis of the SOCIA ontology. Web news articles and microblogs related to local concerns were semi-automatically gathered and structured. Public issues and goals were manually extracted from Web content related to revitalization from the Great East Japan Earthquake. Towards more accurate extraction of public concerns, we investigated feature expressions for extracting public concerns from microblogs written in Japanese. To address a technical issue about sample selection bias in our microblog corpus, we formulated a metric in mining feature expressions, i.e., bias-penalized information gain (BPIG). Furthermore, we developed a prototype of a public debate support system that utilized the SOCIA dataset and formulated the similarity between public goals for a goal matching service to facilitate collaboration.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Semantic Web; social computing; natural language processing; linked open data; e-Participation