Community-Driven Linked Data Authoring and Production of Consolidated Linked Data

被引:7
作者
Shakya, Aman [1 ]
Takeda, Hideaki [2 ]
Wuwongse, Vilas [3 ]
机构
[1] Grad Univ Adv Studies SOKENDAI, Natl Inst Informat, Dept Informat, Hayama, Kanagawa, Japan
[2] Univ Tokyo, Tokyo 1138654, Japan
[3] Asian Inst Technol, Pathum Thani 12120, Thailand
关键词
Concept Consolidation; Data Integration; Emergent Semantics; Freebase; Structured Data; Linked Data; Social Semantic Web; StYLiD; TOOL; WEB; ONTOLOGIES;
D O I
10.4018/jswis.2009081902
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
User-generated content can help the growth of linked data. However, we lack interfaces enabling ordinary people to author linked data. Secondly, people have multiple perspectives on the same concept and different contexts. Thirdly, not enough ontologies exist to model various data. Therefore, we propose an approach to enable people to share various data through an easy-to-use social platform. Users define their own concepts and multiple conceptualizations are allowed. These are consolidated using semi-automatic schema alignment techniques supported by the community. Further, concepts are grouped semi-automatically by similarity. As a result of consolidation and grouping, informal lightweight ontologies emerge gradually. We have implemented a social software, called StYLiD, to realize our approach. It can serve as a platform motivating people to bookmark and share different things. It may also drive vertical portals for specific communities with integrated data from multiple sources. Experimental observations support the validity of our approach.
引用
收藏
页码:23 / 48
页数:26
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