Cluster analysis is a crucial technique in unsupervised machine learning, pattern recognition, and data analysis. However, current clustering algorithms suffer from the need for manual determination of parameter values, low accuracy, inconsistent performance concerning size structure. To address these challenges, novel algorithm called fully automated density-based method (FADBC) proposed. The ...

One fundamental problem that confronts information retrieval is to efficiently support query with higher accuracy and less logic hops. This paper presents HSPIR (Hierarchical Semantic P2P-based Information Retrieval) that distributes document indices through the P2P network hierarchically based on documents semantics generated by Latent Semantic Indexing (LSI) [1]. HSPIR uses CAN [2] and Range ...

Clustering ensemble performance is affected by two main factors: diversity and quality. Selection of a subset of available ensemble members based on diversity and quality often leads to a more accurate ensemble solution. However, there is not a certain relationship between diversity and quality in selection of subset of ensemble members. This paper proposes the Hierarchical Cluster Ensemble Sel...

An efficient shot summarization method is presented based on agglomerative clustering of the shot frames. Unlike other agglomerative methods, our approach relies on a cluster merging criterion that computes the content homogeneity of a merged cluster. An important feature of the proposed approach is the automatic estimation of the number of a shot's most representative frames, called keyframes....

Hierarchical Clustering is a procedure of cluster analysis which aims to construct a hierarchy of clusters. There are two kinds of hierarchical clustering i.e. Agglomerative, which is a bottom – up approach, where all the observations start in its own cluster, and pairs of clusters are merged moving up the hierarchy, and the other one is divisive, which is a top down approach, where each observ...

The first GC and GC/MS analyses of the essential oils hydrodistilled from dry leaves of Arctostaphylos uva-ursi and Vaccinium vitis-idaea enabled the identification of 338 components in total (90.4 and 91.7% of the total GC peak areas, respectively). Terpenoids, fatty acids, fatty acid- and carotenoid derived compounds were predominant in the two samples. Both oils were characterized by high re...

Equitable regional development is still difficult to implement. Many interests in determining priorities make it realize the main goals of national development. Political and underutilization statistical data are often other obstacles carrying out This study aims classify be used analyse existing inequalities. Gross domestic income (GRDP) this study. The researcher hierarchical agglomerative cl...

We present a method for refining clusters of 3D curves using a new coherence measure. Curves are common geometric models used for representing the information derived from different types of data, in particular scientific data represented as vector and tensor fields. Our method starts with an initial set of clusters. For each cluster, we probe samples from the cluster by “slicing” it with a pla...

Many researchers have studied the population of individuals with mild mental retardation (MIMR) as if it is a clear entity. Few researchers have investigated potential subtypes within the MIMR population. The purpose of the present study was to investigate which subtypes can be identified on the basis of intellectual, adaptive and behavioral functioning. Seventy-three individuals with MIMR were...