A robust framework for web information extraction and retrieval

Rayner Alfred, and Patricia Anthony, and Gan, Kim Soon and Chin, Kim On (2014) A robust framework for web information extraction and retrieval. International Journal Of Machine Learning and Computing, 4 (2). pp. 151-156. ISSN 2010-3700


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The large volume of online and offline information that is available today has overwhelmed users’ efficiency and effectiveness in processing this information in order to extract relevant information. The exponential growth of the volume of Internet information complicates information access. Thus, it is a very time consuming and complex task for user in accessing relevant information. Information retrieval (IR) is a branch of artificial intelligence that tackles the problem of accessing and retrieving relevant information. The aim of IR is to enable the available data source to be queried for relevant information efficiently and effectively. This paper describes a robust information retrieval framework that can be used to retrieve relevant information. The proposed information retrieval framework is designed to assist users in accessing relevant information effectively and efficiently as it handles queries based on user preferences. Each component and module involved in the proposed framework will be explained in terms of functionality and the processes involved.

Item Type: Article
Uncontrolled Keywords: Document recommender agent, agent technology, information retrieval
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: FACULTY > Faculty of Computing and Informatics
Depositing User: Unnamed user with email storage.bpmlib@ums.edu.my
Date Deposited: 13 Nov 2015 03:37
Last Modified: 12 Oct 2017 07:19
URI: http://eprints.ums.edu.my/id/eprint/12228

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