Scaling up question-answering to linked data

Vanessa Lopez, Andriy Nikolov, Marta Sabou, Victoria Uren, Enrico Motta, Mathieu d'Aquin

Research output: Chapter in Book/Published conference outputConference publication

Abstract

Linked Data semantic sources, in particular DBpedia, can be used to answer many user queries. PowerAqua is an open multi-ontology Question Answering (QA) system for the Semantic Web (SW). However, the emergence of Linked Data, characterized by its openness, heterogeneity and scale, introduces a new dimension to the Semantic Web scenario, in which exploiting the relevant information to extract answers for Natural Language (NL) user queries is a major challenge. In this paper we discuss the issues and lessons learned from our experience of integrating PowerAqua as a front-end for DBpedia and a subset of Linked Data sources. As such, we go one step beyond the state of the art on end-users interfaces for Linked Data by introducing mapping and fusion techniques needed to translate a user query by means of multiple sources. Our first informal experiments probe whether, in fact, it is feasible to obtain answers to user queries by composing information across semantic sources and Linked Data, even in its current form, where the strength of Linked Data is more a by-product of its size than its quality. We believe our experiences can be extrapolated to a variety of end-user applications that wish to scale, open up, exploit and re-use what possibly is the greatest wealth of data about everything in the history of Artificial Intelligence.
Original languageEnglish
Title of host publicationKnowledge engineering and management by the masses
Subtitle of host publication17th International Conference, EKAW 2010, Lisbon, Portugal, October 11-15, 2010. Proceedings
EditorsPhilipp Cimiano, H. Sofia Pinto
Place of PublicationBerlin (DE)
PublisherSpringer
Pages193-210
Number of pages18
ISBN (Electronic)978-3-642-16438-5
ISBN (Print)978-3-642-16437-8
DOIs
Publication statusPublished - 2010
Event17th international conference Knowledge Engineering and Knowledge - Lisbon, Portugal
Duration: 11 Oct 201015 Oct 2010

Publication series

NameLecture notes in computer science
PublisherSpringer
Volume6317
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th international conference Knowledge Engineering and Knowledge
Abbreviated titleEKAW-2010
CountryPortugal
CityLisbon
Period11/10/1015/10/10
OtherManagement by the Masses

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