Automatic Topic Ontology Construction Using Semantic Relations from Wordnet and Wikipedia

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Automatic Topic Ontology Construction Using Semantic Relations from Wordnet and Wikipedia
Authors
V. Subramaniyaswamy
Publication date
2013
DOI
10.4018/jiit.2013070104
Links
Original

Automatic Topic Ontology Construction Using Semantic Relations from Wordnet and Wikipedia - scientific work related to Wikipedia quality published in 2013, written by V. Subramaniyaswamy.

Overview

Due to the explosive growth of web technology, a huge amount of information is available as web resources over the Internet. Therefore, in order to access the relevant content from the web resources effectively, considerable attention is paid on the semantic web for efficient knowledge sharing and interoperability. Topic ontology is a hierarchy of a set of topics that are interconnected using semantic relations, which is being increasingly used in the web mining techniques. Reviews of the past research reveal that semiautomatic ontology is not capable of handling high usage. This shortcoming prompted the authors to develop an automatic topic ontology construction process. However, in the past many attempts have been made by other researchers to utilize the automatic construction of ontology, which turned out to be challenging due to time, cost and maintenance. In this paper, the authors have proposed a corpus based novel approach to enrich the set of categories in the ODP by automatically identifying the concepts and their associated semantic relationship with corpus based external knowledge resources, such as Wikipedia and WordNet. This topic ontology construction approach relies on concept acquisition and semantic relation extraction. A Jena API framework has been developed to organize the set of extracted semantic concepts, while Protege provides the platform to visualize the automatically constructed topic ontology. To evaluate the performance, web documents were classified using SVM classifier based on ODP and topic ontology. The topic ontology based classification produced better accuracy than ODP.

Embed

Wikipedia Quality

Subramaniyaswamy, V.. (2013). "[[Automatic Topic Ontology Construction Using Semantic Relations from Wordnet and Wikipedia]]". IGI Global. DOI: 10.4018/jiit.2013070104.

English Wikipedia

{{cite journal |last1=Subramaniyaswamy |first1=V. |title=Automatic Topic Ontology Construction Using Semantic Relations from Wordnet and Wikipedia |date=2013 |doi=10.4018/jiit.2013070104 |url=https://wikipediaquality.com/wiki/Automatic_Topic_Ontology_Construction_Using_Semantic_Relations_from_Wordnet_and_Wikipedia |journal=IGI Global}}

HTML

Subramaniyaswamy, V.. (2013). &quot;<a href="https://wikipediaquality.com/wiki/Automatic_Topic_Ontology_Construction_Using_Semantic_Relations_from_Wordnet_and_Wikipedia">Automatic Topic Ontology Construction Using Semantic Relations from Wordnet and Wikipedia</a>&quot;. IGI Global. DOI: 10.4018/jiit.2013070104.