article

Content-based text querying with ontological descriptors

Authors:

Troels Andreasen,

Per Anker Jensen,

Jørgen Fischer Nilsson,

Patrizia Paggio,

Bolette Sandford Pedersen,

Hanne Erdman ThomsenAuthors Info & Claims

Data & Knowledge Engineering, Volume 48, Issue 2

Pages 199 - 219

https://doi.org/10.1016/S0169-023X(03)00105-8

Published: 01 February 2004 Publication History

Abstract

This paper describes a method and a system for content-based querying of texts based on the availability of an ontology for the concepts in the text domain. A key principle in the system is the extraction of conceptual content of noun phrases into descriptors forming an integral part of the ontology.The retrieval of text passages rests on matching descriptors from the text against descriptors from the noun phrases in the query. The match does not need to be exact but is mediated by the ontology invoking in particular taxonomic reasoning with sub- and super-concepts. The paper also reports on a prototype implementation of the system.

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Cited By

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Alexandridis KMaru Y(2012)Collapse and reorganization patterns of social knowledge representation in evolving semantic networksInformation Sciences: an International Journal10.1016/j.ins.2012.02.053200(1-21)Online publication date: 1-Oct-2012
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Hu KWang YTian Y(2010)A Web Knowledge Discovery Engine Based on Concept AlgebraInternational Journal of Cognitive Informatics and Natural Intelligence10.4018/jcini.20100101054:1(80-97)Online publication date: 1-Jan-2010
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Abdelhamid ERafea AEl-Beltagy S(2009)Enhancing search results of concept annotated documentsProceedings of the 10th IEEE international conference on Information Reuse & Integration10.5555/1689250.1689310(330-335)Online publication date: 10-Aug-2009
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Index Terms

Content-based text querying with ontological descriptors
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection
    2. Information retrieval query processing

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Reviews

Reviewer: Jaroslav Pokorny

An approach to querying text sources based on extracting and evaluating semantic content, given a formal ontology for the text domain, is described in this paper. Queries take the form of natural language expressions, and the system is primarily intended to retrieve text segments whose semantic content matches the content of noun phrases in the query phrase. The approach is based on a fully automatic generation of descriptors of natural language text. Querying uses the generalization/specialization relations for ranking matches, rather than reformulating queries. After a short section comparing their approach with other systems, the authors discuss their choice of a feasible ontological representation formalism, in sections 3 and 4. In particular, the descriptors, and their embedding in the ontology by means of a notion of ontological grammar, are introduced. Section 4 addresses the disambiguation of noun phrases, whereas section 5 introduces the notion of semantic roles represented in terms of binary semantic relations. As an application domain for the prototype, the authors use the field of nutrition. Section 6 considers examples of noun phrases from nutrition texts, and their mappings onto descriptors. Finally, sections 7 and 8 describe the query-matching process, and the prototype implementation, respectively. Section 9 concludes the paper, and offers some challenges for the future. The method was developed in the OntoQuery project, and is described in several other papers by the same authors, profusely cited in the text. This detracts from the readability of the paper. While the method is interesting, the authors provide no well-specified experiments justifying their approach. For example, a comparison with other methods of information retrieval would be beneficial. Online Computing Reviews Service

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cover image Data & Knowledge Engineering

Data & Knowledge Engineering Volume 48, Issue 2

NLDB2002

February 2004

111 pages

ISSN:0169-023X

Issue’s Table of Contents

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 February 2004

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Alexandridis KMaru Y(2012)Collapse and reorganization patterns of social knowledge representation in evolving semantic networksInformation Sciences: an International Journal10.1016/j.ins.2012.02.053200(1-21)Online publication date: 1-Oct-2012
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Hu KWang YTian Y(2010)A Web Knowledge Discovery Engine Based on Concept AlgebraInternational Journal of Cognitive Informatics and Natural Intelligence10.4018/jcini.20100101054:1(80-97)Online publication date: 1-Jan-2010
https://dl.acm.org/doi/10.4018/jcini.2010010105
Abdelhamid ERafea AEl-Beltagy S(2009)Enhancing search results of concept annotated documentsProceedings of the 10th IEEE international conference on Information Reuse & Integration10.5555/1689250.1689310(330-335)Online publication date: 10-Aug-2009
https://dl.acm.org/doi/10.5555/1689250.1689310
Giunchiglia FKharkevich UZaihrayeu I(2009)Concept SearchProceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications10.1007/978-3-642-02121-3_33(429-444)Online publication date: 31-May-2009
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Andreasen TBulskov HTerney T(2008)Ontological summaries through hierarchical clusteringProceedings of the 17th international conference on Foundations of intelligent systems10.5555/1786474.1786539(497-507)Online publication date: 20-May-2008
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Tao XLi YNayak R(2008)A knowledge retrieval model using ontology mining and user profilingIntegrated Computer-Aided Engineering10.5555/1402687.140269115:4(313-329)Online publication date: 1-Dec-2008
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Pedersen B(2007)Using shallow linguistic analysis to improve search on Danish compoundsNatural Language Engineering10.1017/S135132490600425613:1(75-90)Online publication date: 1-Mar-2007
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Lee CKao YKuo YWang M(2007)Automated ontology construction for unstructured text documentsData & Knowledge Engineering10.1016/j.datak.2006.04.00160:3(547-566)Online publication date: 1-Mar-2007
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Combining ontological profiles with context in information retrieval

Ontological Extraction of Content for Text Querying

Information retrieval from relational databases using semantic queries

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