An Enhanced Web Document Search Engine using a Semantic Network

Nguyen, Sang and Nguyen, Tuan (2016) An Enhanced Web Document Search Engine using a Semantic Network. REV Journal on Electronics and Communications 14.8, 5 (3-4).

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Abstract

With the rapid advancement of ICT technology, the World Wide Web (referred to as the Web) has become the biggest information repository whose volume keeps growing on a daily basis. The challenge is how to find the most wanted information from the Web with a minimum effort. This paper presents a novel ontology-based framework for searching the related web pages to a given term within a few given specific websites. With this framework, a web crawler first learns the content of web pages within the given websites, then the topic modeller finds the relations between web pages and topics via keywords found on the web pages using the Latent Dirichlet Allocation (LDA) technique. After that, the ontology builder establishes an ontology which is a semantic network of web pages based on the topic model. Finally, a reasoner can find the related web pages to a given term by making use of the ontology. The framework and related modelling techniques have been verified using a few test websites and the results convince its superiority over the existing web search tools.

Item Type: Article
Additional Information: Open Access Journal
Uncontrolled Keywords: Semantic network, ontology, topic models, search engine
Subjects: Q Science > Q Science (General)
Divisions: School of Science > Applied Computing
Depositing User: Tuan Nguyen
Date Deposited: 26 Feb 2019 12:30
Last Modified: 26 Feb 2019 12:30
URI: http://bear.buckingham.ac.uk/id/eprint/218

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