In the context of big data, many scientific communities aim to provide efficient approaches to
accommodate large-scale datasets. This is the case of the machine-learning community …

Feature selection is an important task in machine learning. It can improve classification
accuracy and effectively reduce the dataset dimensionality by removing no discriminative …

The rapid development of cloud computing and Internet of Things technology has caused
the explosive growth of data scale and the high complexity of data models, leading to cluster …

The map-reduce model is a method for executing large data applications. It is also a parallel
programming model for writing applications that can be executed on the cloud …

An improved parallel K-means algorithm is proposed to address the problems of redundant
features, cluster load imbalance, and center-of-mass sensitivity of parallel K-means …

Due to the rapid development in information technology, Big Data has become one of its
prominent feature that had a great impact on other technologies dealing with data such as …

A large number of real-world optimization and search problems are too computationally
intensive to be solved due to their large state space. Therefore, a mechanism for generating …

: مدل نگاشت-کاهش یک مدل برای اجرای برنامه های کاربردی داده های بزرگ می باشد. همچنین این مدل،
یک مدل برنامه نویسی موازی برای نوشتن برنامه‌هایی می‌باشد که می‌توانند بر روی ابر اجرا شوند …‎