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Information Extraction
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Automatic document metadata extraction using support vector machines
Ontology Learning from Text
The future of citation indexing: An interview with Eugene Garfield
Methodology for the Design and Evaluation of Ontologies
Federated database systems for managing distributed, heterogeneous, and autonomous databases
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Ontology research and development. Part 1 - a review of ontology generation
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Ontology research and development. Part 1 - a review of ontology generation
(
Citations: 73
)
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Ying Ding
,
Schubert Foo
Ontology is an important emerging discipline that has the huge potential to improve information organization, management and understanding. It has a crucial role to play in enabling content-based access, interoperability, communications, and providing qualitatively new levels of services on the
next generation
of Web transformation in the form of the Semantic Web. The issues pertaining to ontology generation, mapping and maintenance are critical key areas that need to be understood and addressed. This timely survey is presented in two parts. This first part reviews the state-of-the-art techniques and work done on semi- automatic and automatic ontology generation, as well as the problems facing these researches. The second complimentary survey is dedicated to
ontology mapping
and ontology evolving. Through this survey, we identified that shallow
information extraction
and
natural language processing
techniques are deployed to extract concepts or classes from free-text or semi-structured data. However,
relation extraction
is a very complex and difficult issue to resolve and it has turned out to be the main impedance to
ontology learning
and applicability. Further researches are encouraged to find appropriate and efficient ways to detect or identify relations through semi-automatic automatic means.
Published in 2002.
DOI:
10.1177/016555150202800204
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Citation Context
(13)
...‘Shared’ reflects that ontology knowledge accepted by the communities.” 1993;
Ding and Foo, 2002
)...
Chris Biemann
.
Ontology Learning from Text: A Survey of Methods
...The integration of knowledge acquisition with machinelearning techniques has already proved extremely beneficial for knowledge acquisition [
6
, 10, 11, 13]...
Min-yuh Day
,
et al.
A knowledge-based approach to citation extraction
...classify data instances to build the conceptual tree of the ontology [
13
]...
...generation studies, for example [
13
], SCORE (Semantic Content Organization and Re-...
...by ontology generation research [
13
], the practicality of this type of approaches has not...
...us that it is very difficult to build a large size domain ontology [
13
]...
Yihong Ding
.
Web Semantic Annotation Using Data-Extraction Ontologies
...Heterogeneity is a problem encountered in many information systems [1,
2
]. It can lead to a degradation of the quality from the perspective of the user when his terminology does not match the terminology of the system nor does the cognitive landscape s/he has formed of a domain match with the structures presented within an interface...
Sabine Heinz
,
et al.
Implementation and Evaluation of a Virtual Library Shelf for Informati...
...[
6
]) have addressed the issue of collecting conceptual information from domain-specific text...
Judith L. Klavans
,
et al.
Tackling the Internet Glossary Glut: Automatic Extraction and Evaluati...
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