Testing is one of the most widely used techniques to increase the quality and reliability of complex software systems. In this paper we refine our previous work on passive testing with invariants to incorporate (probabilistic) knowledge obtained from users of the system under test by using data mining techniques. We adapt our previous approach in order to reduce costs. We emphasize the use of d...

The healthcare environment is generally perceived as being ‘information rich’ yet ‘knowledge poor’. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerous applications in business and scientific domain. Valuable knowledge c...

Over the past few decades, rapid changes in information technology have drastically changed the functions and activities of multimedia. Data mining has become more popular for extracting knowledge from multimedia data sets such as audio, video, speech, text, web, image and a combination of several types of these data sets. These are increasingly available and are semi-structured data or unstruc...

Image mining is an expansion of data mining in the field of image processing. Image mining handles with the hidden knowledge extraction, image data association and additional patterns which are not clearly gathered in the images. It is an interdisciplinary field that incorporates techniques like Image Processing, Data Mining, Machine Learning, Database and Artificial Intelligence. The most impo...

Medical image mining is one of the most rewarding and challenging field of application in data mining and knowledge discovery. Soft computing is a consortium of methodologies that provides flexible information processing capability. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning, and limited truth in order to achieve tractability, robustness, and low-cos...

The techniques of data mining are very popular in the area of agriculture. The advancement in Agricultural research has been improved by technical advances in computation, automation and data mining. Now a days ,data mining is being used in a vast areas .The products of data mining system and domain specific data mining application soft ware’s are available for tailor made use, but data mining ...

Data mining has recently emerged as an important issue of multimedia research. New trends are focused on knowledge discovery in large multimedia repositories, however, traditional data mining approaches do not seem to bear fruits. There is a need to use new techniques to mine knowledge from multimedia, link content top context and more importantly, to exploit them in real life applications. In ...

Process mining techniques can be used to extract non-trivial process related knowledge and thus generate interesting insights from event logs. Similarly, bioinformatics aims at increasing the understanding of biological processes through the analysis of information associated with biological molecules. Techniques developed in both disciplines can benefit from one another, e.g., sequence analysi...

Many data mining techniques are these days in use for ontology learning – text mining, Web mining, graph mining, link analysis, relational data mining, and so on. In the current state-of-the-art bundle there is a lack of “software mining” techniques. This term denotes the process of extracting knowledge out of source code. In this paper we approach the software mining task with a combination of...

Data mining consists of evolving set of techniques that can be used to extract valuable information and knowledge from massive volumes of data. Data mining research & tools have focused on commercial sector applications. Data and Information or Knowledge has a significant role on human activities. Data mining is the knowledge discovery process by analyzing the large volumes of data from various...