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To be effective to retain customers and enhance the marketing capabilities, it is necessary to improve the personalization of e-commerce systems. Clustering is a reliable and efficient technology to provide personal service in e-commerce system. However, current research on clustering algorithm usually based on numeric data or categorical data. To analysis customer behavior, mixed data set must be...
In recent years, the advent of high throughput data generation techniques have increased not only the number of objects collected in databases, but also the number of attributes describing these objects. Clustering is the process of grouping the data into classes or clusters, so that objects within a cluster have high similarity in comparison to one another but are very dissimilar to objects in other...
Existing trajectory clustering algorithm TRACLUS uses global parameters, it can not distinguish small, close, and dense trajectory clusters from large and sparse trajectory clusters. Moreover, TRACLUS needs two input parameters and is sensitive to input parameters. To avoid the shortcomings of TRACLUS, a neighborhood-based trajectory clustering algorithm named NBTC is proposed based on the improved...
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