FREyA: An Interactive Way of Querying Linked Data Using Natural Language

Damljanović, Danica; Agatonović, Milan; Cunningham, Hamish

doi:10.1007/978-3-642-25953-1_11

Cited by 117 publications

(94 citation statements)

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“…Several work on NL questions to query the Semantic Web have been carried out, like Aqualog (Lopez, Pasin, & Motta, 2005), SQUALL (Ferré, 2012) or FREyA (Damljanovic, Agatonovic, & Cunningham, 2012), which use SPARQL for querying knowledge bases built in RDF. In PANTO and Querix (Kaufmann, Bernstein, & Zumstein, 2006), they accept generic NL questions and outputs SPARQL queries.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Enrichment of the phenotypic and genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Peral

Ferrández

Gregorio

et al. 2015

Ecological Informatics

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Section: Accepted Manuscriptmentioning

confidence: 99%

Enrichment of the phenotypic and genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Peral

Ferrández

Gregorio

et al. 2015

Ecological Informatics

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“…These approaches mainly rely on linguistic resources to expand and disambiguate keywords, with the drawbacks of coverage and lack of generality in the relationships considered mentioned earlier. FREyA [5] is a natural language interface for querying ontologies. It performs syntactic parsing of the NLQ and involves the user in the translation process if necessary.…”

Section: Related Workmentioning

confidence: 99%

Mapping Keywords to Linked Data Resources for Automatic Query Expansion

Augenstein

Gentile

Norton³

et al. 2013

Advanced Information Systems Engineering

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Abstract. Linked Data is a gigantic, constantly growing and extremely valuable resource, but its usage is still heavily dependent on (i) the familiarity of end users with RDF's graph data model and its query language, SPARQL, and (ii) knowledge about available datasets and their contents. Intelligent keyword search over Linked Data is currently being investigated as a means to overcome these barriers to entry in a number of different approaches, including semantic search engines and the automatic conversion of natural language questions into structured queries. Our work addresses the specific challenge of mapping keywords to Linked Data resources, and proposes a novel method for this task. By exploiting the graph structure within Linked Data we determine which properties between resources are useful to discover, or directly express, semantic similarity. We also propose a novel scoring function to rank results. Experiments on a publicly available dataset show a 17% improvement in Mean Reciprocal Rank over the state of the art.

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“…In (Priebe and Pernul 2003a, b) Aqualog (Lopez et al 2005), SQUALL (Ferré 2012) or FREyA (Damljanovic et al 2012),…”

mentioning

confidence: 99%

A framework for enriching Data Warehouse analysis with Question Answering systems

et al. 2014

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FREyA: An Interactive Way of Querying Linked Data Using Natural Language

Cited by 117 publications

References 10 publications

Enrichment of the phenotypic and genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Enrichment of the phenotypic and genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Mapping Keywords to Linked Data Resources for Automatic Query Expansion

A framework for enriching Data Warehouse analysis with Question Answering systems

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