WhoKnows? Evaluating linked data heuristics with a quiz that cleans up DBpedia

WhoKnows? Evaluating linked data heuristics with a quiz that cleans up DBpedia Purpose – Linking Open Data (LOD) provides a vast amount of well structured semantic information, but many inconsistencies may occur, especially if the data are generated with the help of automated methods. Data cleansing approaches enable detection of inconsistencies and overhauling of affected data sets, but they are difficult to apply automatically. The purpose of this paper is to present WhoKnows?, an online quiz that generates different kinds of questionnaires from DBpedia data sets. Design/methodology/approach – Besides its playfulness, WhoKnows? has been developed for the evaluation of property relevance ranking heuristics on DBpedia data, with the convenient side effect of detecting inconsistencies and doubtful facts. Findings – The original purpose for developing WhoKnows? was to evaluate heuristics to rank LOD properties and thus, obtain a semantic relatedness between entities according to the properties by which they are linked. The presented approach is an efficient method to detect popular properties within a limited amount of triples. Ongoing work continues in the development of sound property ranking heuristics for the purpose of detecting the most relevant characteristics of entities. Originality/value – WhoKnows? uses the approach of “Games with a Purpose” to detect inconsistencies in Linked Data and score properties to rank them for sophisticated semantic search scenarios. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Interactive Technology and Smart Education Emerald Publishing

WhoKnows? Evaluating linked data heuristics with a quiz that cleans up DBpedia

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Publisher
Emerald Publishing
Copyright
Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
ISSN
1741-5659
DOI
10.1108/17415651111189478
Publisher site
See Article on Publisher Site

Abstract

Purpose – Linking Open Data (LOD) provides a vast amount of well structured semantic information, but many inconsistencies may occur, especially if the data are generated with the help of automated methods. Data cleansing approaches enable detection of inconsistencies and overhauling of affected data sets, but they are difficult to apply automatically. The purpose of this paper is to present WhoKnows?, an online quiz that generates different kinds of questionnaires from DBpedia data sets. Design/methodology/approach – Besides its playfulness, WhoKnows? has been developed for the evaluation of property relevance ranking heuristics on DBpedia data, with the convenient side effect of detecting inconsistencies and doubtful facts. Findings – The original purpose for developing WhoKnows? was to evaluate heuristics to rank LOD properties and thus, obtain a semantic relatedness between entities according to the properties by which they are linked. The presented approach is an efficient method to detect popular properties within a limited amount of triples. Ongoing work continues in the development of sound property ranking heuristics for the purpose of detecting the most relevant characteristics of entities. Originality/value – WhoKnows? uses the approach of “Games with a Purpose” to detect inconsistencies in Linked Data and score properties to rank them for sophisticated semantic search scenarios.

Journal

Interactive Technology and Smart EducationEmerald Publishing

Published: Nov 22, 2011

Keywords: Online databases; Encyclopaedias; Data management; Semantics; DBpedia; Data cleansing; Serious games; Evaluation

References

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