Defect localisation is essential in software engineering and is an important task in domain-specific data mining. Existing techniques building on call-graph mining can localise different kinds of defects. However, these techniques focus on defects that affect the controlflow and are agnostic regarding the dataflow. In this paper, we introduce dataflowenabled call graphs that incorporate abstrac...

Kansei Engineering was adopted as a method to analyze the critical factors and elements design in developing a new product of software based on consumer’s emotions. However, most analysis in Kansei Engineering are using statistical analysis such as principal component analysis, factor analaysis etc in order to evaluate the average data gathered from all respondents and explore product based on ...

Enormous quantities of trajectory data are collected from many sources, as GPS devices and mobile phones, as sequences of points. These data can be used in many application domains such as traffic management, urban planing, tourism, and bird migration. However, in most applications a higher level of abstraction should be used instead of sample points. In this paper we present an extension of th...

—Data mining is also being useful to give solutions for invasion finding and auditing. While data mining has several applications in protection, there are also serious privacy fears. Because of email mining, even inexperienced users can connect data and make responsive associations. Therefore we must to implement the privacy of persons while working on practical data mining. Using K-mean cluste...

This research, conducted for Frito Lay-North America, Inc, demonstrates how new product designs, package designs, concepts, and prototypes can be created based on the social, emotional, cognitive, and sensory information gathered through a combined methodology based on activity theory, Kansei Engineering and the ZMET process. The study examines how activity theory can be used to observe situati...

UNLABELLED The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experiment...

Data mining is an essential phase in knowledge discovery in database which is actually used to extract hidden patterns from large databases. Data mining concepts and methods can be applied in various fields like marketing, medicine, real estate, customer relationship management, engineering, web mining, etc. The main objective of this paper is to compare the performance accuracy of Multilayer p...

We exhibited the thought of data mining through the free and open source programming Waikato Environment for Knowledge Analysis (WEKA), which allows you to burrow own data for examples and cases. We moreover depicted about the first methodology for data mining — backslide — which allows you to anticipate a numerical worth for a given set of insight qualities. This method for dismemberment is mo...