Zhishi.me - Weaving Chinese Linking Open Data

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• 作者：Xing Niu (1) xingniu@apex.sjtu.edu.cn
  Xinruo Sun (1) xrsun@apex.sjtu.edu.cn
  Haofen Wang (1) whfcarter@apex.sjtu.edu.cn
  Shu Rong (1) rongshu@apex.sjtu.edu.cn
  Guilin Qi (2) gqi@seu.edu.cn
  Yong Yu (1) yyu@apex.sjtu.edu.cn
• 刊名：Lecture Notes in Computer Science
• 出版年：2011
• 出版时间：2011
• 年：2011
• 卷：7032
• 期：1
• 页码：205-220
• 全文大小：547.4 KB
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• 作者单位：1. APEX Data & Knowledge Management Lab, Shanghai Jiao Tong University, China2. Southeast University, China
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

Linking Open Data (LOD) has become one of the most important community efforts to publish high-quality interconnected semantic data. Such data has been widely used in many applications to provide intelligent services like entity search, personalized recommendation and so on. While DBpedia, one of the LOD core data sources, contains resources described in multilingual versions and semantic data in English is proliferating, there is very few work on publishing Chinese semantic data. In this paper, we present Zhishi.me, the first effort to publish large scale Chinese semantic data and link them together as a Chinese LOD (CLOD). More precisely, we identify important structural features in three largest Chinese encyclopedia sites (i.e., Baidu Baike, Hudong Baike, and Chinese Wikipedia) for extraction and propose several data-level mapping strategies for automatic link discovery. As a result, the CLOD has more than 5 million distinct entities and we simply link CLOD with the existing LOD based on the multilingual characteristic of Wikipedia. Finally, we also introduce three Web access entries namely SPARQL endpoint, lookup interface and detailed data view, which conform to the principles of publishing data sources to LOD.