Learning to predict rare events from time-series data with non-numerical features is an important real-world problem. An example of such a problem is the task of predicting telecommunication equipment failures from network alarm data. For a variety of reasons, existing statistical and machine learning methods are not well suited to solving this class of problems. This paper describes timeweaver...

Introduction: One of the most significant elements of entrepreneurshipcurriculum design is teaching-learning methods, which plays a key rolein studies and researches related to such a curriculum. It is the teachingmethod, and systematic, organized and logical ways of providing lessonsthat should be consistent with entrepreneurship goals and contents, andshould also be developed according to the...

0

Identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. In this article, we have tried to design an intelligent system which can separate and classify student according to learning factor and pe...

Success in collaboratively learning subject matter means both learning the subject matter (collaborating to learn), and learning how to effectively manage the team interaction (learning to collaborate). Supporting on-line learning teams means supporting both these activities. We focus on the problem of assimilating the knowledge needed to address interaction problems that may arise during colla...