@INPROCEEDINGS { Rsds3265,
author = {Mehata, K.M. and Siromoney, Arul and Maheswari, V. Uma}, 
title = {The Variable Precision Rough Set Inductive Logic Programming Model and Web Usage Graphs}, 
booktitle = {Proceedings of International Workshop on Rough Set Theory and Granular Computing (RSTGC-2001)}, 
conference = {International Workshop on Rough Set Theory and Granular Computing}, 
series =  = {Bulletin of International Rough Set Society}, 
volume = 5, 
pages = {339-343}, 
month = {May}, 
year = 2001, 
editor = {Hirano, Shoji and Inuiguchi, Masahiro and Tsumoto, Shusaku}, 
issn = {1346-0013}, 
abstract = {The Variable Precision Rough Set Inductive Logic Programming model (VPRSILP model) extends the Variable Precision Rough Set (VPRS) model to Inductive Logic Programming (ILP). Then generic Rough Set Inductive Logic Programming (gRS-ILP)model provides a framework for ILP when the setting is imprecise and any induced logic program will not be able to distinguish between certain positive and negative examples. The gRS-ILP model is extended to the VPRSILP model is applied in this paper to Web usage graphs and an illustrative experiment is presented.}, 
keywords = {rough set theory (RST), inductive logic programming, machine learning, knowledge discovery from data, web usage graphs, }, 
}