http://dx.doi.org/10.1111/j.1467-8640.2011.00382.x">
 

Document Type

Journal Article

Department/Unit

Department of Computer Science

Title

Semantic mapping from natural language questions to OWL queries

Language

English

Abstract

Natural language question-and-answering is one of the most convenient means for communicating with the Semantic Web, which is typically in the form of online knowledge bases encoded in Web Ontology Language (OWL). To understand a natural language question, it is essential that it can be translated into a query that is understandable by the knowledge bases. This article is concerned with the task of semantic mapping from natural language questions to OWL queries, and proposes an automatic and domain-independent mapping framework, called Three-Phases Semantic Mapping (TPSM). The TPSM framework approaches the task of semantic mapping in three interrelated phases: (i) formalizing knowledge, (ii) building semantic mapping, and (iii) combining OWL queries. First, formalizing knowledge formalizes the units of mapping in the natural language and OWL knowledge. Second, semantic mapping builds the transverse mapping between questions and OWL knowledge, as formalized in the first phase, by means of working with the so-called Fuzzy Constraint Satisfaction Problems (FCSP). Third, combining OWL queries obtains valid Resource Description Framework (RDF) models by applying predefined templates and their corresponding combining methods. We have implemented a prototype semantic mapping system based on the framework, and have conducted a series of experimental validations involving OWL knowledge bases in different domains as queried by various types of questions. © 2011 Wiley Periodicals, Inc.

Keywords

fuzzy constraint satisfaction problem, natural language question-and-answering, semantic mapping, Semantic Web

Publication Date

2011

Source Publication Title

Computational Intelligence

Volume

27

Issue

2

Start Page

280

End Page

314

Publisher

Wiley

ISSN (print)

08247935

ISSN (electronic)

14678640

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