A Semaphore Based Multiprocessing k-Mean Algorithm for Massive Biological Data
نویسندگان
چکیده
منابع مشابه
A Distributed and Parallel Clustering Algorithm for Massive Biological Data
Distributed processing today is a largely advantageous technology of bridging together a system of multiple computers and processor systems in running applications. The concept of Distributed processing has allowed time cutting and therefore reduction in costs. Using this, we aim to address clustering techniques in developing new method for further reduction in time and costs. The problem of cl...
متن کاملPersistent K-Means: Stable Data Clustering Algorithm Based on K-Means Algorithm
Identifying clusters or clustering is an important aspect of data analysis. It is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. It is a main task of exploratory data mining, and a common technique for statistical data analysis This paper proposed an improved version of K-Means algorithm, namely Persistent K...
متن کاملClustering of Data Using K-Mean Algorithm
Clustering is associate automatic learning technique geared toward grouping a collection of objects into subsets or clusters. The goal is to form clusters that are coherent internally, however well completely different from one another. In plain words, objects within the same cluster ought to be as similar as potential, whereas objects in one cluster ought to be as dissimilar as potential from ...
متن کاملAn efficient K-means algorithm for Massive Data
Due to the progressive growth of the amount of data available in a wide variety of scientific fields, it has become more difficult to manipulate and analyze such information. Even though datasets have grown in size, the K-means algorithm remains as one of the most popular clustering methods, in spite of its dependency on the initial settings and high computational cost, especially in terms of d...
متن کاملAn efficient K -means clustering algorithm for massive data
The analysis of continously larger datasets is a task of major importance in a wide variety of scientific fields. In this sense, cluster analysis algorithms are a key element of exploratory data analysis, due to their easiness in the implementation and relatively low computational cost. Among these algorithms, the K-means algorithm stands out as the most popular approach, besides its high depen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Asian Journal of Scientific Research
سال: 2008
ISSN: 1992-1454
DOI: 10.3923/ajsr.2008.444.450