The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Data Mining Using Qualitative Information on the Web
|
|
Author(s): Taeho Hong (Pusan National University, Korea)and Woojong Suh (Inha University, Korea)
Copyright: 2005
Pages: 21
Source title:
Web Engineering: Principles and Techniques
Source Author(s)/Editor(s): Woojong Suh (Inha University, Korea)
DOI: 10.4018/978-1-59140-432-3.ch015
Purchase
|
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.
Related Content
|
Dina Darwish.
© 2024.
28 pages.
|
|
Dina Darwish.
© 2024.
28 pages.
|
|
Muhammad Ahmed, Adnan Ahmad, Furkh Zeshan, Hamid Turab.
© 2024.
33 pages.
|
|
Pankaj Bhambri.
© 2024.
17 pages.
|
|
Kaushikkumar Patel.
© 2024.
20 pages.
|
|
Vijaya Kittu Manda, Arnold Mashud Abukari, Vivek Gupta, Madavarapu Jhansi Bharathi.
© 2024.
24 pages.
|
|
Pankaj Bhambri.
© 2024.
17 pages.
|
|
|