Automatic Inclusion of Semantics over Keyword-Based Linked Data Retrieval

Md-Mizanur RAHOMAN  Ryutaro ICHISE  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E97-D   No.11   pp.2852-2862
Publication Date: 2014/11/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2014EDP7073
Type of Manuscript: PAPER
Category: Data Engineering, Web Information Systems
Keyword: 
linked data,  keyword,  information access,  data statistics,  

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Summary: 
Keyword-based linked data information retrieval is an easy choice for general-purpose users, but the implementation of such an approach is a challenge because mere keywords do not hold semantic information. Some studies have incorporated templates in an effort to bridge this gap, but most such approaches have proven ineffective because of inefficient template management. Because linked data can be presented in a structured format, we can assume that the data's internal statistics can be used to effectively influence template management. In this work, we explore the use of this influence for template creation, ranking, and scaling. Then, we demonstrate how our proposal for automatic linked data information retrieval can be used alongside familiar keyword-based information retrieval methods, and can also be incorporated alongside other techniques, such as ontology inclusion and sophisticated matching, in order to achieve increased levels of performance.