ICASSP
2011
IEEE
13 years 4 months ago
2011
IEEE
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...
JDCTA
2010
13 years 7 months ago
2010
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...
TKDE
2011
13 years 7 months ago
2011
—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...
TKDE
2002
14 years 6 days ago
2002
CORR
2002
Springer
14 years 12 days ago
2002
Springer
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...
JSS
2007
14 years 14 days ago
2007
Discovering sequential patterns is an important problem for many applications. Existing algorithms find qualitative sequential patterns in the sense that only items are included ...
TKDE
2008
14 years 14 days ago
2008
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...
JIIS
2006
14 years 16 days ago
2006
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...
JCP
2008
14 years 17 days ago
2008
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...
IDA
2006
Springer
14 years 17 days ago
2006
Springer
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...