In this paper, we present a general framework to discover spatial associations and spatio-temporal episodes for scientific datasets. In contrast to previous work in this area, fea...
There has been much recent interest in on-line data mining. Existing mining algorithms designed for stored data are either not applicable or not effective on data streams, where r...
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Peculiarity rules are a new type of useful knowledge that can be discovered by searching the relevance among peculiar data. A main task in mining such knowledge is peculiarity iden...
Muneaki Ohshima, Ning Zhong, Yiyu Yao, Chunnian Li...
We describe a generic framework for representing and reasoning with annotated Semantic Web data, formalise the annotated language, the corresponding deductive system, and address ...
Umberto Straccia, Nuno Lopes 0002, Gergely Lukacsy...