Recommendation algorithms apply knowledge discovery techniques to the problem of making product recommendation during a live interaction and achieving widespread success in Ecommerce nowadays. With the magnitudes of users and items grow rapidly, resulting in the extreme sparsity of user rating data and the decreasing of real time performance. To solve the problem, the paper proposed a personali...

Clustering of data items is one of the important applications of graph partitioning using a graph model. The pairwise similarities between all data items form the adjacency matrix of a weighted graph that contains all the necessary information for clustering. In this paper we propose a novel hybrid-evolutionary algorithm based on graph partitioning approach for data clustering. The algorithm is...

This paper proposes an energy-efficient geocast algorithm for wireless sensor networks with guaranteed delivery of packets from the sink to all nodes located in several geocast regions. Our approach is different from those existing in the literature. We first propose a hybrid clustering scheme: in the first phase we partition the network in cliques using an existing energy-efficient clustering ...

There are two broad approaches for differentially private data analysis. The interactive approach aims at developing customized differentially private algorithms for various data mining tasks. The non-interactive approach aims at developing differentially private algorithms that can output a synopsis of the input dataset, which can then be used to support various data mining tasks. In this pape...

The visual analysis of large movement data sets can be a challenging task. This study proposes an approach for identifying interesting movement patterns that combines human knowledge and decision making with a hybrid clustering-classification method. Rather than performing an unsupervised clustering of the entire data set, a stratified random sample of the full data set is used to identify init...

This article presents a study of academic performance evaluation using soft computing techniques inspired by the successful application of K-means, fuzzy C-means (FCM), subtractive clustering (SC), hybrid subtractive clustering-fuzzy C-means (SC-FCM) and hybrid subtractive clustering-adaptive neuro fuzzy inference system (SC-ANFIS) methods for solving academic performance evaluation problems. M...

Many efforts have been done to tackle the problem of information abundance in the World Wide Web. Growth in the number of web users and the necessity of making the information available on the web, make web recommender systems very critical and popular. Recommender systems use the knowledge obtained through the analysis of users' navigational behavior, to customize a web site to the needs of ea...