Sequences of events, items, or tokens occurring in an ordered metric space appear often in
data and the requirement to detect and analyze frequent subsequences is a common …

In this paper, we propose a 3-step DNA sequence mining algorithm, called 3s-DNASM,
incorporating prefix span, length and width constraints and group search optimization. The …

Using automated data analysis to understand what makes a play successful in football can
enable teams to make data-driven decisions that may enhance their performance …

Within Information Extraction tasks, Named Entity Recognition has received much attention
over latest decades. From symbolic/knowledge-based to data-driven/machine-learning …

Ces dernières décennies, le développement considérable des technologies de l'information
et de la communication a modifié en profondeur la manière dont nous avons accès aux …

During the past decade, sequential pattern mining has been the core of numerous research
efforts. It is now possible to efficiently extract knowledge of users' behavior from a huge set of …

In present scenario almost every system and working is computerized and hence all
information and data are being stored in Computers. Huge collections of data are emerging …

An important challenge in modern functional proteomics is the prediction of the functional
behavior of proteins. Motifs in protein chains can make such a prediction possible. The …

This paper describes an approach to constructing a probabilistic process model
representing knowledge worker activity out of a log of primitive events, such as e-mails, web …

Computational neuroscience is being revolutionized with the advent of multi-electrode
arrays that provide real-time, dynamic perspectives into brain function. Mining neuronal …