Large-scale clustering has found wide applications in many fields and received much attention in recent years. However, most existing large-scale clustering methods can only achieve mediocre performance, because they are sensitive to the unavoidable presence of noise in the large-scale data. To address this challenging problem, we thus propose a large-scale sparse clustering (LSSC) algorithm. I...

Nonnegative matrix factorization (NMF) is a common method in data mining that have been used in different applications as a dimension reduction, classification or clustering method. Methods in alternating least square (ALS) approach usually used to solve this non-convex minimization problem.  At each step of ALS algorithms two convex least square problems should be solved, which causes high com...

In this work, a two-step approach is adopted for scheduling tasks with synchronous communication. To that end, an efficient algorithm, called GLB-Synch, is introduced for mapping clusters and ordering tasks on processors in one integrated step. The algorithm used the information obtained during the clustering step for selecting a cluster to be mapped on the least loaded processor. A performance...

In this paper we present a multi-class extension to our approach for modelling out-of-vocabulary (OOV) words [1]. Instead of augmenting the word search space with a single OOV model, we add several OOV models, one for each class of words. We present two approaches for designing the OOV word classes. The first approach relies on using common part-of-speech tags. The second approach is a data-dri...

In this paper we present a multi-class extension to our approach for modelling out-of-vocabulary (OOV) words [1]. Instead of augmenting the word search space with a single OOV model, we add several OOV models, one for each class of words. We present two approaches for designing the OOV word classes. The first approach relies on using common part-of-speech tags. The second approach is a data-dri...

Motorcycle crashes constitute a significant proportion of traffic accidents all over the world. The aim of this paper was to examine the motorcycle crash patterns and rider fault status across the provinces of Iran. For this purpose, 6638 motorcycle crashes occurred in Iran through 2009-2012 were used as the analysis data and a two-step clustering approach was adopted as the analysis framework....

Zoning the pollution of a river may be the first or even the most important step in water quality management. In order to resolve its pollution, fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates mutiple parameters In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering ...

nonnegative matrix factorization (nmf) is a common method in data mining that have been used in different applications as a dimension reduction, classification or clustering method. methods in alternating least square (als) approach usually used to solve this non-convex minimization problem.  at each step of als algorithms two convex least square problems should be solved, which causes high com...