The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. The theoretical parts and the practical parts are well integrated for readers ...

This report is a self contained description of the results obtained during the second year of PhD and the plan for future work.

The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. The theoretical parts and the practical parts are well integrated for readers ...

The number, the size, and the dynamics of Internet information sources bears abundant evidence of the need of automation in information extraction (IE). This paper deals with the question of how such extraction mechanisms can automatically be created by invoking learning techniques. The underlying scenario of system-supported IE is putting certain constraints on the available training examples....

This thesis reports the investigations into the task of phone-level pronunciation error detection, the performance of which is heavily affected by the imbalanced distribution of the classes in a manually annotated data set of non-native English (Read Aloud responses from the TOEFL Junior Pilot assessment). In order to address problems caused by this extreme class imbalance, two machine learning...

Personalization approaches in learning environments are crucial to foster effective, active, efficient, and satisfactory learning. They can be addressed from different perspectives and also in various educational settings, including formal, informal, workplace, lifelong, mobile, contextualized, and selfregulated learning. PALE workshop offers an opportunity to present and discuss a wide spectru...

We consider three approaches to learning natural resource models involving spatial relationships, based respectively on decision tree learning, genetic programming and inductive logic programming. In each case, the results of spatial learning on a natural resource problem are compared with the results of non-spatial learning from the same data, and improvements in predictivity or simplicity of ...

The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. The theoretical parts and the practical parts are well integrated for readers ...

The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. The theoretical parts and the practical parts are well integrated for readers ...

The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. The theoretical parts and the practical parts are well integrated for readers ...