As the amount of available data continues to increase, more and more effective means for discovering important patterns and relationships within that data are required. Although t...
Graphs or networks can be used to model complex systems. Detecting community structures from large network data is a classic and challenging task. In this paper, we propose a nove...
This paper describes a framework for defining domain specific Feature Functions in a user friendly form to be used in a Maximum Entropy Markov Model (MEMM) for the Named Entity Re...
In ubiquitous computing, behavior routine learning is the process of mining the context-aware data to find interesting rules on the user’s behavior, while preference learning tri...
Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as op...