Software developers often encapsulate reusable code as Application Programming Interfaces (APIs). The co-evolution of applications and APIs may motivate an API migration: the replacement of application dependencies to an original API by dependencies to an alternative API that provides similar functionality and abstractions. In this dissertation, we investigate issues associated with API migrati...

With an exponentially increasing amount of astronomical data, the complexity and dimension of astronomical data are likewise growing rapidly. Extracting information from such data becomes a critical and challenging problem. For example, some algorithms can only be employed in the low-dimensional spaces, so feature selection and feature extraction become important topics. Here we describe the di...

Due to the rise of technology, the possibility of fraud in different areas such as banking has been increased. Credit card fraud is a crucial problem in banking and its danger is over increasing. This paper proposes an advanced data mining method, considering both feature selection and decision cost for accuracy enhancement of credit card fraud detection. After selecting the best and most effec...

Feature selection has become an important task for effective application of data mining techniquesin real-world high dimensional datasets. It is a process that selects a subset of original features by removing irrelevant and redundant features on the basis of the evaluation criteria without loss of information content. A feature selection method helps to reduce computational complexity of learn...

This paper is a principal idea of case-based reasoning to feature weighting. The feature weighting method called CaDFeW (CAse-based Dynamic FEature Weighting) stores classification performance of randomly generated feature weight vectors. Also it retrieve similar feature weighting success story from the feature weighting case base and then designs a better feature weight vector dynamically for ...

In this paper, we propose an adaptive wrapper generator that can generate adaptable wrapper for adapting networked information sources (NIS) format changes. When NIS’s format changed, the adaptable wrapper can start recovery phase to discover the extraction rule of the new format of target NIS. The wrapper can automatically adapt the changes of content tag and accurately extract information. Th...

This paper presents a novel feature selection approach to deal with issues of high dimensionality in biomedical data classification. Extensive research has been performed in the field of pattern recognition and machine learning. Dozens of feature selection methods have been developed in the literature, which can be classified into three main categories: filter, wrapper and hybrid approaches. Fi...

Modern agent and mediator systems communicate to a multitude of Web information providers to better satisfy the user requests. They use wrappers to extract relevant information from HTML pages and annotate it with user-defined labels. A number of approaches exploit the regularity in page structures to induce instances of wrapper classes. The power of a class is crucial; a more powerful class pe...

The problem of Web phishing attacks has grown considerably in recent years and phishing is considered as one of the most dangerous Web crimes, which may cause tremendous and negative effects on online business. In a Web phishing attack, the phisher creates a forged or phishing website to deceive Web users in order to obtain their sensitive financial and personal information. Several conventiona...

Semi-supervised wrapper methods are concerned with building effective supervised classifiers from partially labeled data. Though previous works have succeeded in some fields, it is still difficult to apply semi-supervised wrapper methods to practice because the assumptions those methods rely on tend to be unrealistic in practice. For practical use, this paper proposes a novel semi-supervised wr...