The aim is to improve and develop a novel scheme detect loyalties of customers using pattern growth method.Novel Pattern method compared with upper bound taxonomy sequence algorithm are used online sales customer loyalties. Sample size determined the G Power calculator found be 10 per group. Totally 20 samples used. Pretest power 80% CI 95%. Based on analysis Novel has an accuracy 80.8% 67.25%....

In this paper, we introduce a new method of designing Venn Machine taxonomy based on Support Vector Machines and k-means clustering for both binary and multi-class problems. We compare this algorithm to some other multi-probabilistic predictors including SVM Venn Machine with homogeneous intervals and a recently developed algorithm called Venn-ABERS predictor. These algorithms were tested on a ...

In this paper, we devise an efficient algorithm for clustering market-basket data. Different from those of the traditional data, the features of market-basket data are known to be of high dimensionality, sparsity, and with massive outliers. Clustering transactions across different levels of the taxonomy is of great importance for marketing strategies as well as for the result representation of ...

This paper presents an efficient algorithm for disparity map computation with an adaptive window by establishing two frame stereo correspondence. Adaptive window based approach has a clear advantage of producing dense depth maps from stereo images. In recent years there has not been much research on adaptive window based approach due its high complexity and large computation time. Adaptive wind...

Many domains are naturally organized in an abstraction hierarchy or taxonomy, where the instances in “nearby” classes in the taxonomy are similar. In this paper, we provide a general probabilistic framework for clustering data into a set of classes organized as a taxonomy, where each class is associated with a probabilistic model from which the data was generated. The clustering algorithm simul...

We consider a general form of information sources, consisting of a set of objects classified by terms arranged in a taxonomy. The query-based access to the information stored in sources of this kind, is plagued with uncertainty, due, among other things, to the possible linguistic mismatch between the user and the object classification. To overcome this uncertainty in all situations in which the...

In this paper we introduce the concept of conflictive animations and discuss its applicability in programming and algorithm design courses. Conflictive animations are animations that deviate from the expected behaviour of the program or algorithm they are supposed to present. With respect to the engagement taxonomy, we propose several ways of learning with conflictive animations. We also initia...

for RSA based on the repertory grid. The algorithm incorporates user relevance judgments as a means to deal with the inherent problems associated with the specification of semantic attributes. The algorithm is implemented and tested on the human face image database and the initial results are encouraging. In essence, we have developed an overall methodology/test bed to facilitate experimentatio...

In this paper we describe our work in progress in the automatic development of a taxonomy of Spanish nouns, we offer the Perl implementation we have so far, and we discuss the different problems that still need to be addressed. We designed a statistically-based taxonomy induction algorithm consisting of a combination of different strategies not involving explicit linguistic knowledge. Being all...

We describe here a properly recent application of the Gröbner Cover algorithm (GC) providing an algebraic support to Dynamic Geometry computations of geometrical loci. It provides a complete algebraic solution of locus computation as well as a suitable taxonomy allowing to distinguish the nature of the different components. We included a new algorithm Locus into the Singular grobcov.lib library...