Data Mining Using Qualitative Information on the Web

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Author(s): Taeho Hong (Pusan National University, Korea)and Woojong Suh (Inha University, Korea)
Copyright: 2008
Pages: 19
Source title: Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59904-951-9.ch080

Keywords: Data Mining and Databases / Data Warehousing / Information Science Reference / Library & Information Science

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Abstract

Data mining has drawn much attention in generating the useful information from Web data. Data mining techniques have typically considered quantitative information rather than qualitative, though the qualitative information can often be used to improve the quality of a result. This chapter provides a hybrid data mining application, KBNMiner (Knowledge-Based News Miner), to predict interest rates on the basis of qualitative information on the Web as well as quantitative information stored in a database. The KBNMiner is developed through the integration of cognitive maps and neural networks. To validate the effectiveness of the KBNMiner, an experiment with Web news information is conducted and its results are discussed.

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