@INPROCEEDINGS { Rsds4837,
author = {Wang, Guoyin}, 
title = {KT: Knowledge Technology - The Next Step of Information Technology (IT)}, 
booktitle = {Rough Sets and Knowledge Technology}, 
conference = {Rough Sets and Knowledge Technology}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 5589, 
pages = {27--29}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {July}, 
year = 2009, 
editor = {Wen, Peng and Li, Yuefeng and Polkowski, Lech and Yao, Yiyu and Tsumoto, Shusaku and Wang, Guoying}, 
url = {http://www.springerlink.com/content/q0857121u072/?p=fc4581dabf904891bbe1f9cc3f4fdd0d&pi=313}, 
issn = {0302-9743}, 
isbn = {978-3-642-02961-5}, 
abstract = {We are living in an information technology (IT) era now. Advances in computing, communications, digital storage technologies, and high-throughput data-acquisition technologies, make it possible to gather and store incredible volumes of data and information. What will be the next step of IT? Many researchers predict that the next step of IT might be Knowledge Technology (KT). KT refers to a fuzzy set of tools enabling better acquisition, representation, organization, exchange and application of information and knowledge. In this talk, we will address some issues about the development of IT to KT. Some KT related events happened in the past years [1-5], organizations of KT [6-8], and understandings of KT [9-12] will be introduced. One of the most important issues for developing KT, knowledge acquisition and data mining, will be discussed in a new view of translation [13, 14]. Some basic issues of data mining will be analyzed in this view. A new model of data mining, domain-oriented data-driven data mining (3DM), will be proposed [14-17]. The relationship between traditional domain-driven (or user-driven) data mining models [18-20] and our proposed 3DM model will also be analyzed [21]. Some domain-oriented data-driven data mining algorithms for mining such knowledge as default rule [22], decision tree [23], and concept lattice [24] from database will be introduced. The experiment results of these algorithms are also shown to illustrate the efficiency and performance of the knowledge acquired by 3DM data mining algorithms.}, 
keywords = {knowledge technology, data mining, knowledge acquisition, rough set, data driven, domain driven, domain oriented, }, 
}