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Clustering large data is one of the recently challenging tasks that is used in many application areas such as social networking, bioinformatics and many others. Traditional clustering algorithms need to be modified to handle the increasing data sizes. In this paper, a scalable design and implementation of glowworm swarm optimization clustering (MRCGSO) using MapReduce is introduced to handle big data...
Clustering is an important tool in many fields such as exploratory data mining and pattern recognition. It consists in organizing a large data set into groups of objects that are more similar to each other than to those in other groups. Despite its use for over three decades, it is still subject to a lot of controversy. In this paper, we cast clustering as a Pareto based multi-objective optimization...
Searching and discovering the relevant information on the web have always been challenging task. It is very hard to wade through the large number of returned documents in a response to a user query. This leads to the need to organize a large set of documents into categories through clustering. There is a need of efficient clustering algorithms for organizing documents. Clustering on large dataset...
This paper proposes the Fuzzy Particle Swarm Clustering (FPSC) algorithm, which is an extension of the crisp data clustering algorithm PSC particularly tailored to deal with fuzzy clusters. The main structural changes of the original PSC algorithm to design FPSC occurred in the selection and evaluation steps of the winner particle, comparing the degree of membership of each object from the database...
Extending instruction set architecture (ISA) of embedded processors is an effective way to enhance performance and energy efficiency. The typical approaches for identifying custom instructions (CIs) limit the maximum number of input and output (I/O) operands to the available register file port. Recently, there are several work that explore CI candidates without imposing a limit on the number of input...
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