Extensive growth of data gives the motivation to find meaningful patterns among the huge data. Sequential pattern provides us interesting relationships between different items in sequential database. In the real world, there are several applications in which specific sequences are more important than other sequences. Traditional Sequential pattern approaches are suffering from two disadvantages...

Subspace analysis is one of popular multivariate data analysis methods, which has been widely used in pattern recognition. Typically data space belongs to very high dimension, but only a few principal components need to be extracted. In this paper, we present a fast sequential algorithm which behaves like expectation maximization (EM), for subspace analysis or tracking. In addition we also pres...

let l := u3(11). in this article, we classify groups with the same order and degree pattern as an almost simple group related to l. in fact, we prove that l, l:2 and l:3 are od-characterizable, and l:s3 is 5-fold od-characterizable.

Feature selection, representation and extraction are integral to statistical pattern recognition systems. Usually features are represented as vectors that capture expert knowledge of measurable discriminative properties of the classes to be distinguished. The feature selection process entails manual expert involvement and repeated experiments. Automatic feature selection is necessary when (i) e...

heretofore, a vast spectrum of pattern recognition methods has been considered by researchers to design credit scoring models. but what has not been considered enough in these studies is the lack of consideration of the needs of this subject which differentiate it from a simple classification. it is necessary to observe the costs of a wrong classification, because practically the cost of improp...

Predicting the next request of a user as she visits Web pages has gained importance as Web-based activity increases. There are a number of different approaches to prediction. Markov models and their variations, collaborative filtering models, or models based on pattern recognition techniques such as sequence mining, association rule mining, clustering user sessions or user, have been found well...

Identifying human activities is a key task for the development of advanced and effective ubiquitous applications in fields like Ambient Assisted Living. Depending on the availability of labeled data, recognition methods can be categorized as either supervised or unsupervised. Designing a comprehensive activity recognition system that works on a real-world setting is extremely challenging becaus...