Proceeding of: 7th International Symposium on Intelligent Data Analysis. IDA-2007. Ljubljana, Slovenia, September, 6th-8th, 2007.Sequence classification is a significant problem that arises in many different real-world applications. The purpose of a sequence classifier is to assign a class label to a given sequence. Also, to obtain the pattern that characterizes the sequence is usually very useful. In this paper, a technique to discover a pattern from a given sequence is presented followed by a general novel method to classify the sequence. This method considers mainly the dependencies among the neighbouring elements of a sequence. In order to evaluate this method, a UNIX command environment is presented, but the method is general enough to...
In this paper, we review some pattern recognition schemes published in recent years. After giving th...
Processing of image sequences is a very actual trend now. This is confirmed with a vast amount of re...
this paper we present a practical technique for detecting a broader class of linear induction variab...
Proceeding of: 7th International Symposium on Intelligent Data Analysis. IDA-2007. Ljubljana, Sloven...
Sequence classification is an important task in data mining. We address the problem of sequence clas...
Sequence classification is an efficient task in data mining. The knowledge obtained from training st...
International audienceSequential pattern mining is one of the most studied and challenging tasks in ...
In this paper we present the interesting Behavioral Constraint Miner (iBCM), a new approach towards ...
Sequence labeling is the task of assigning a label sequence to an observation sequence. Since many m...
this paper we present a novel methodology for sequence classification, based on sequential pattern m...
The Scanning N-Tuple classifier (SNT) is a fast and accurate method for classifying sequences. Appli...
Sequential pattern mining in data streams environment is an interesting data mining problem. The pro...
International audienceSequential data are generated in many domains of science and technology. Altho...
The problem of sequence categorization is to generalize from a corpus of labeled sequences procedure...
In this paper we present an innovative procedure for sequence mining and representation. It can be u...
In this paper, we review some pattern recognition schemes published in recent years. After giving th...
Processing of image sequences is a very actual trend now. This is confirmed with a vast amount of re...
this paper we present a practical technique for detecting a broader class of linear induction variab...
Proceeding of: 7th International Symposium on Intelligent Data Analysis. IDA-2007. Ljubljana, Sloven...
Sequence classification is an important task in data mining. We address the problem of sequence clas...
Sequence classification is an efficient task in data mining. The knowledge obtained from training st...
International audienceSequential pattern mining is one of the most studied and challenging tasks in ...
In this paper we present the interesting Behavioral Constraint Miner (iBCM), a new approach towards ...
Sequence labeling is the task of assigning a label sequence to an observation sequence. Since many m...
this paper we present a novel methodology for sequence classification, based on sequential pattern m...
The Scanning N-Tuple classifier (SNT) is a fast and accurate method for classifying sequences. Appli...
Sequential pattern mining in data streams environment is an interesting data mining problem. The pro...
International audienceSequential data are generated in many domains of science and technology. Altho...
The problem of sequence categorization is to generalize from a corpus of labeled sequences procedure...
In this paper we present an innovative procedure for sequence mining and representation. It can be u...
In this paper, we review some pattern recognition schemes published in recent years. After giving th...
Processing of image sequences is a very actual trend now. This is confirmed with a vast amount of re...
this paper we present a practical technique for detecting a broader class of linear induction variab...