Music consists of both local and long-term temporal information. However, for a genre classification task, most of the text categorization based approaches only capture local temp...
Encoding can express the hierarchical relationship in the area of mining the multi-level sequential pattern, up to now all the algorithms of which find frequent sequences just acc...
—Classification has been used for modeling many kinds of data sets, including sets of items, text documents, graphs, and networks. However, there is a lack of study on a new kind...
In this paper, we first define a difference measure between the old and new sequential patterns of stream data, which is proved to be a distance. Then we propose an experimental me...
Discovering sequential patterns is an important problem for many applications. Existing algorithms find qualitative sequential patterns in the sense that only items are included ...
Chulyun Kim, Jong-Hwa Lim, Raymond T. Ng, Kyuseok ...
Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, mining spatio-temporal sequential patterns ident...
In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data: the data streams. In data stream pro...
This paper proposes a new sequential pattern mining method. The method introduces a new evaluation criterion satisfying the Apriori property. The criterion is calculated by the fre...
Text categorization is a well-known task based essentially on statistical approaches using neural networks, Support Vector Machines and other machine learning algorithms. Texts are...