NDLI: HARE: A Hybrid SPARQL Engine to Enhance Query Answers via Crowdsourcing

Content Provider	ACM Digital Library
Author	Flöck, Fabian Simperl, Elena Vidal, Maria-Esther Acosta, Maribel
Abstract	Due to the semi-structured nature of RDF data, missing values affect answer completeness of queries that are posed against RDF. To overcome this limitation, we present HARE, a novel hybrid query processing engine that brings together machine and human computation to execute SPARQL queries. We propose a model that exploits the characteristics of RDF in order to estimate the completeness of portions of a data set. The completeness model complemented by crowd knowledge is used by the HARE query engine to on-the-fly decide which parts of a query should be executed against the data set or via crowd computing. To evaluate HARE, we created and executed a collection of 50 SPARQL queries against the DBpedia data set. Experimental results clearly show that our solution accurately enhances answer completeness.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISBN	9781450338493
DOI	10.1145/2815833.2815848
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-10-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Crowdsourcing Crowd knowledge Completeness model Sparql query Query execution Microtasks Rdf data Hybrid system
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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HARE: A Hybrid SPARQL Engine to Enhance Query Answers via Crowdsourcing