We address an ensemble clustering problem, where reliable clusters are locally embedded in given multiple partitions. We propose a new nonnegative matrix factorization (NMF)-based method, in which locally reliable clusters are explicitly considered by using instance-wise weights over clusters. Our method factorizes the input cluster assignment matrix into two matrices H and W , which are optimi...

Clustering words is a widely used technique in statistical natural language processing. It requires syntactic, semantic, and contextual features. Especially, semantic clustering is gaining a lot of interest. It consists in grouping a set of words expressing the same idea or sharing the same semantic properties. In this paper, we present a new method to integrate semantic classes in a Statistica...

A Wireless Sensor Network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. In sensing applications, data packets are flowing from sensor nodes to base station. In data collection processes, bottom up approach is used. In bottom up approach, all nodes send their sensed data packets to base stati...

The behavior of visitors browsing in a web site offers a lot of information about their requirements and the way they use the respective site. Analyzing such behavior can provide the necessary information in order to improve the web site’s structure. The literature contains already several suggestions on how to characterize web site usage and to identify the respective visitor requirements base...

Co-clustering is the simultaneous partitioning of the rows and columns of a matrix such that the blocks induced by the row/column partitions are good clusters. Motivated by several applications in text mining, market-basket analysis, and bioinformatics, this problem has attracted a lot of attention in the past few years. Unfortunately, to date, most of the algorithmic work on this problem has b...

We study the problem of k-means clustering in the presence of outliers. The goal is to cluster a set of data points to minimize the variance of the points assigned to the same cluster, with the freedom of ignoring a small set of data points that can be labeled as outliers. Clustering with outliers has received a lot of attention in the data processing community, but practical, efficient, and pr...

The selection of RE techniques for a project is usually based on personal preference or existing company practice rather than on characteristics of RE techniques and the project at hand. Moreover, research has shown that there are a lot of very useful RE techniques that are not widely used. The few approaches currently available for the selection of RE techniques provide only little guidance fo...

Lot-sizing and capacity planning are important supply chain decisions, and competition and cooperation affect the performance of these decisions. In this paper, we look into the dynamic lot sizing and resource competition problem of an industry consisting of multiple firms. A capacity competition model combining the complexity of time-varying demand with cost functions and economies os scale ar...

Despite considerable progress within wilderness and adventure therapy research over the last decade, researchers are still unable to precisely answer why, how, and for whom this treatment modality works. There is also a need for more knowledge regarding the circumstances under which the treatment does not appear to be effective. In this realist synthesis, we attempt to unpack this "black box" o...

Patient-physician interactions are increasingly influenced by the extraordinary diversification of populations and rapid expansion of medical knowledge that characterize our modern era. By contrast, the patient-physician interaction models currently used to teach medical trainees have little capacity to address these twin challenges. We developed a new model of patient-physician interaction to ...