AquaLog: An Ontology-Portable Question Answering System for the Semantic Web

López, Vanessa; Pasin, Michele; Motta, Enrico

doi:10.1007/11431053_37

Cited by 148 publications

(89 citation statements)

References 15 publications

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“…Our evaluation has been performed with the knowledge base from which our institute portal is automatically generated 3 . The underlying ontology is the SWRC ontology [11], which allows for the representation of researchers, their publications, active projects etc.…”

Section: Discussionmentioning

confidence: 99%

“…[5], [3], [4], [7]). While these approaches have been shown to yield remarkable results, it is not clear if users always want to specify a full natural language question.…”

Section: Related Workmentioning

confidence: 99%

“…an ontology (cf. [3], [4]) or database schema [5], not as much work has been carried out with respect to the formal interpretation of keyword queries. A notable exception is the approach described in [6], which we discuss further in the related work section.…”

Section: Introductionmentioning

confidence: 99%

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Ontology-Based Interpretation of Keywords for Semantic Search

et al. 2007

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Abstract. Current information retrieval (IR) approaches do not formally capture the explicit meaning of a keyword query but provide a comfortable way for the user to specify information needs on the basis of keywords. Ontology-based approaches allow for sophisticated semantic search but impose a query syntax more diAEcult to handle. In this paper, we present an approach for translating keyword queries to DL conjunctive queries using background knowledge available in ontologies. We present an implementation which shows that this interpretation of keywords can then be used for both exploration of asserted knowledge and for a semantics-based declarative query answering process. We also present an evaluation of our system and a discussion of the limitations of the approach with respect to our underlying assumptions which directly points to issues for future work.

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Section: Discussionmentioning

confidence: 99%

“…[5], [3], [4], [7]). While these approaches have been shown to yield remarkable results, it is not clear if users always want to specify a full natural language question.…”

Section: Related Workmentioning

confidence: 99%

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Ontology-Based Interpretation of Keywords for Semantic Search

et al. 2007

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“…We did not find any data manipulation capabilities. Hence, LingoLogic seems to belong to the category of NLI-based ontology/database querying tools such as PRECISE [23], AquaLog/PowerAqua [16,15], START [13], SWAT [6], or Ginseng [5] -the GINO predecessor. PRE-CISE, Ginseng, and SWAT were evaluated with the Mooney databases [31], which also have associated NL queries collected from users.…”

Section: Related Workmentioning

confidence: 99%

GINO – A Guided Input Natural Language Ontology Editor

Bernstein

Kaufmann

2006

Lecture Notes in Computer Science

127

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Abstract. The casual user is typically overwhelmed by the formal logic of the Semantic Web. The gap between the end user and the logic-based scaffolding has to be bridged if the Semantic Web's capabilities are to be utilized by the general public. This paper proposes that controlled natural languages offer one way to bridge the gap. We introduce GINO, a guided input natural language ontology editor that allows users to edit and query ontologies in a language akin to English. It uses a small static grammar, which it dynamically extends with elements from the loaded ontologies. The usability evaluation shows that GINO is well-suited for novice users when editing ontologies. We believe that the use of guided entry overcomes the habitability problem, which adversely affects most natural language systems. Additionally, the approach's dynamic grammar generation allows for easy adaptation to new ontologies.

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“…Based on this hypothesis, we have developed the AquaLog [12] ontology-based question answering system. The novelty of the system with respect to traditional QA systems is that it relies on the knowledge encoded in the underlying ontology and its explicit semantics to disambiguate the meaning of the questions and to provide answers.…”

Section: Motivating Scenario: Question Answering On the Semantic Webmentioning

confidence: 99%

PowerMap: Mapping the Real Semantic Web on the Fly

López

Sabou

Motta

2006

Lecture Notes in Computer Science

Self Cite

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Abstract. Ontology mapping plays an important role in bridging the semantic gap between distributed and heterogeneous data sources. As the Semantic Web slowly becomes real and the amount of online semantic data increases, a new generation of tools is developed that automatically find and integrate this data. Unlike in the case of earlier tools where mapping has been performed at the design time of the tool, these new tools require mapping techniques that can be performed at run time. The contribution of this paper is twofold. First, we investigate the general requirements for run time mapping techniques. Second, we describe our PowerMap mapping algorithm that was designed to be used at run-time by an ontology based question answering tool.

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AquaLog: An Ontology-Portable Question Answering System for the Semantic Web

Cited by 148 publications

References 15 publications

Ontology-Based Interpretation of Keywords for Semantic Search

Ontology-Based Interpretation of Keywords for Semantic Search

GINO – A Guided Input Natural Language Ontology Editor

PowerMap: Mapping the Real Semantic Web on the Fly

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