This paper presents a prototype-driven framework for classifying evolving data streams. Our framework uses cluster prototypes to summarize the data and to determine whether the cur...
— With growing amount of data gathered nowadays, the need for efficient data mining methodologies is getting more and more common. There is a large number of different classifi...
— In recent applications of clustering such as gene expression microarray analysis, collaborative filtering, and web mining, object similarity is no longer measured by physical ...
−Document clustering has become an increasingly important task in analyzing huge numbers of documents distributed among various sites. The challenging aspect is to analyze this e...
— The extension approach of frequent itemset mining can be applied to discover the relations among documents. Several schemes, i.e., n-gram, stemming, stopword removal and term w...
Outlier detection has recently become an important problem in many industrial and financial applications. This problem is further complicated by the fact that in many cases, outlie...
Dragoljub Pokrajac, Aleksandar Lazarevic, Longin J...
— We present K2GA, an algorithm for learning Bayesian network structures from data. K2GA uses a genetic algorithm to perform stochastic search, while employing a modified versio...
–The OBSERVER is a video surveillance system that detects and predicts abnormal behaviors aiming at the intelligent surveillance concept. The system acquires color images from a ...
— This paper introduces a novel method, GAIS, for detecting interleaved sequential patterns from databases. A case, where data is of low quality and has errors is considered. Pat...