Natural language query translation for semantic search

Querying semantic knowledge base often requires the understanding of the ontology schema and proficiency with the query language. Several approaches have existed but mainly dealing with the disambiguation problem which are solved by executing clarification dialogues. This paper addresses the automa...

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Main Authors: Mohd Sharef, Nurfadhlina, Noah, Shahrul Azman
Format: Article
Language:English
Published: Advanced Institute of Convergence Information Technology (AICIT) 2013
Online Access:http://psasir.upm.edu.my/id/eprint/30614/1/Natural%20language%20query%20translation%20for%20semantic%20search.pdf
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author Mohd Sharef, Nurfadhlina
Noah, Shahrul Azman
author_facet Mohd Sharef, Nurfadhlina
Noah, Shahrul Azman
author_sort Mohd Sharef, Nurfadhlina
collection UPM
description Querying semantic knowledge base often requires the understanding of the ontology schema and proficiency with the query language. Several approaches have existed but mainly dealing with the disambiguation problem which are solved by executing clarification dialogues. This paper addresses the automatic translation of natural language queries into its SPARQL equivalent statement without involving clarification dialogues. We demonstrate that this is achieveable by annotating all ontology concepts in the query. Next the connections between the classes are identified so that the shared properties can be loaded before they are matched with the terms in the query. Then, the identified ontology triples are arranged to construct a valid SPARQL query according to their relation in the ontology schema. We compare the performance of MyAutoSPARQL against FREyA, an NLI that utilizes clarification dialogue. We evaluate our approach on selection typed queries and compare the performance against FREyA. The results show that despite the absent of clarification dialogues, MyAutoSPARQL performance is better than FREyA.
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spelling upm.eprints-306142015-10-07T01:53:16Z http://psasir.upm.edu.my/id/eprint/30614/ Natural language query translation for semantic search Mohd Sharef, Nurfadhlina Noah, Shahrul Azman Querying semantic knowledge base often requires the understanding of the ontology schema and proficiency with the query language. Several approaches have existed but mainly dealing with the disambiguation problem which are solved by executing clarification dialogues. This paper addresses the automatic translation of natural language queries into its SPARQL equivalent statement without involving clarification dialogues. We demonstrate that this is achieveable by annotating all ontology concepts in the query. Next the connections between the classes are identified so that the shared properties can be loaded before they are matched with the terms in the query. Then, the identified ontology triples are arranged to construct a valid SPARQL query according to their relation in the ontology schema. We compare the performance of MyAutoSPARQL against FREyA, an NLI that utilizes clarification dialogue. We evaluate our approach on selection typed queries and compare the performance against FREyA. The results show that despite the absent of clarification dialogues, MyAutoSPARQL performance is better than FREyA. Advanced Institute of Convergence Information Technology (AICIT) 2013-09 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30614/1/Natural%20language%20query%20translation%20for%20semantic%20search.pdf Mohd Sharef, Nurfadhlina and Noah, Shahrul Azman (2013) Natural language query translation for semantic search. International Journal of Digital Content Technology and its Applications, 7 (13). pp. 53-63. ISSN 1975-9339; ESSN: 2233-9310 http://www.aicit.org/JDCTA/ppl/JDCTA3500PPL.pdf
spellingShingle Mohd Sharef, Nurfadhlina
Noah, Shahrul Azman
Natural language query translation for semantic search
title Natural language query translation for semantic search
title_full Natural language query translation for semantic search
title_fullStr Natural language query translation for semantic search
title_full_unstemmed Natural language query translation for semantic search
title_short Natural language query translation for semantic search
title_sort natural language query translation for semantic search
url http://psasir.upm.edu.my/id/eprint/30614/1/Natural%20language%20query%20translation%20for%20semantic%20search.pdf
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