The paradigm shift from 'data-centered pattern mining' to 'domain driven actionable knowledge discovery' has increased the need for considering the business yield (utility) and demand or rate of recurrence of the items (frequency) while mining a retail business transaction database. Such a data mining process will help in mining different types of itemsets of varying business utility and demand...

Sigma-Trees associated with residual vector quantization (RVQ) has been used for image-driven data mining to detect features and objects in a digital image with a degree of success. RVQ methods based on σ-tree structures have been designed to implement successive refinement of information for image segmentation. In such implementations, RVQ based novel methods are devised for pixel-block mining...

This paper describes a query segmentation method for search engines supporting inverse lookup of words and phrases. Data mining in query logs and document corpora is used to produce segment candidates and compute connexity measures. Candidates are considered in context of the whole query, and a list of the most likely segmentations is generated, with each segment attributed with a connexity val...

An important task in signal processing and temporal data mining is time series segmentation. In order to perform tasks such as time series classification, anomaly detection in time series, motif detection, or time series forecasting, segmentation is often a pre-requisite. However, there has not been much research on evaluation of time series segmentation techniques. The quality of segmentation ...

Social scientists face an overload of digitized information. In particular, they must often spend inordinate amounts of time coding and analyzing transcribed speech. This paper describes a study, in the field of learning science, of the feasibility of semi-automatically coding and scoring verbal data. Transcripts from 48 individual learners comprising 2 separate data sets of 44,000 and 23,000 w...

This paper illustrates the linkages between CRM systems, data mining techniques, and the strategic notions of market segmentation and relationship marketing. Using the hypothetical example of a consumer bank, the data in a relationship based marketing environment are illustrated and guidelines for knowledge discovery, data management and strategic marketing are developed.

We address the problem of identifying color variation in color skin lesion color. We adapt a spatial data mining method to this task and integrate with a segmentation method to identify significant color regions in an image. The resulting regions are compared with human perception via Kappa statistical test. Evaluation of the results indicate that the method approximates human judgment well and...

The main goal of this paper is to present and evaluate the possibility of using the methods and tools of Artificial Intelligence and Data Mining to analyze marketing data needed to support decision-making in the process of market segmentation. This paper describes the application of Kohonen’s Neural Networks and Classification Trees (including tools such as CART-Classification and Regression Tr...

data about the prevalence of communicable and non-communicable diseases, as one of the most important categories of epidemiological data, is used for interpreting health status of communities. this study aims to calculate the prevalence of outpatient diseases through the characterization of outpatient prescriptions. the data used in this study is collected from 1412 prescriptions for various ty...

background : chronic kidney disease (ckd) is a complicated kidney problem causing permanent renal failure in progressive stages. the final stage of ckd is called esrd in which most accepted management is hemodialysis (hd). arterio-venus fistula (avf) is the most practical way of making proper access to the blood circulatory system however, maturation of the avf is a challenge, since there are n...