Abstract
Work in inductive learning has mostly been concentrated on classifying. However, there are many applications in which it is desirable to order rather than to classify instances. For modelling ordering problems, we generalize the notion of information tables to ordered information tables by adding order relations in attribute values. Then we propose a data analysis model by analyzing the dependency of attributes to describe the properties of ordered information tables. The problem of mining ordering rules is formulated as finding association between orderings of attribute values and the overall ordering of objects. An ordering rules may state that “if the value of an objectx on an attribute a is ordered ahead of the value of another objecty on the same attribute, thenx is ordered ahead ofy”. For mining ordering rules, we first transform an ordered information table into a binary information table, and then apply any standard machine learning and data mining algorithms. As an illustration, we analyze in detail Maclean’s universities ranking for the year 2000.
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SAI Ying received the B.A. degree in computer science and the M.S. degree in computer software from Shandong University, and received the Ph.D. degree from the National University of Defense Technology, P.R. China. She worked as a visiting scholar for one year in the University of Regina, Canada. She is an associate professor of computer science at Shandong Finance Institute. Her research interests are intelligent information systems, machine learning, data mining and rough set theory. She is a member of the Machine Learning Society of China.
Y. Y. Yao is a professor of computer science in the University of Regina, Canada. His main interests are information retrieval and uncertainty management in intelligent information systems, including uncertain reasoning, fuzzy sets, rough sets, granular computing, etc. He is a member of ACM and SIGIR, IEEE and IEEE Computer Society, Advisory Board of the International Rough Set Society, and a coordinator and member of Advisory Board of GrC: A Special Interest Group on Granular Computing in BISC. He is a managing editor of Bulletin of International Rough Set Society, an associate editor of Journal of Computing and Information and an editorial board member of International Journal of Knowledge and Information Systems.
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Sai, Y., Yao, Y.Y. Analyzing and mining ordered information tables. J. Comput. Sci. & Technol. 18, 771–779 (2003). https://doi.org/10.1007/BF02945466
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DOI: https://doi.org/10.1007/BF02945466