With the development of the Internet, recommender systems have played a more and more important role in the field of big data processing, such as e-business. In order to deal with big data in recommender systems, we propose a clustering and correlation based collaborative filtering algorithm for cloud platform, which improves the traditional user-based collaborative filtering algorithm with k-m...

Kakao ialah salah satu komoditas unggulan dari sektor perkebunan bahkan produksi kakao dinilai mampu meningkatkan devisa negara. Di Indonesia khususnya Provinsi Sulawesi Selatan memiliki yang besar dimana hampir semua Kabupaten/Kota terdapat di memproduksi kakao. Tujuan dalam melakukan penelitian ini untuk pengelompokan daerah pada Selatan. Adapun algoritma digunakan yakni K-Means serta K-Medoi...

We present a new fast online clustering algorithm that reliably recovers arbitrary-shaped data clusters in high throughout data streams. Unlike the existing state-of-the-art online clustering methods based on k-means or k-medoid, it does not make any restrictive generative assumptions. In addition, in contrast to existing nonparametric clustering techniques such as DBScan or DenStream, it gives...

With the huge upsurge of information in day-to-day’s life, it has become difficult to assemble relevant information in nick of time. But people, always are in dearth of time, they need everything quick. Hence clustering was introduced to gather the relevant information in a cluster. There are several algorithms for clustering information out of which in this paper, we accomplish K-means and K-M...

Audio signals are a type of high-dimensional data, and their clustering is critical. However, distance calculation failures, inefficient index trees, and cluster overlaps, derived from the equidistance, redundant attribute, and sparsity, respectively, seriously affect the clustering performance. To solve these problems, an audio-signal clustering algorithm based on the sequential Psim matrix an...