Person name queries often bring up web pages that correspond to individuals sharing the same name. The Web People Search (WePS) task consists of organizing search results for ambiguous person name queries into meaningful clusters, with each cluster referring to one individual. This paper presents a fuzzy ant based clustering approach for this multi-document person name disambiguation problem. T...

Ideally, document clustering methods should produce clusters that are semantically relevant and readily understandable as collections of documents belonging to particular contexts or topics. However, existing popular document clustering methods often ignore term-document corpus-based semantics while relying upon generic measures of similarity. In this paper, we present CDIM, an algorithmic fram...

Hybrid clustering combines partitional and hierarchical clustering for computational effectiveness and versatility in cluster shape. In such clustering, a dissimilarity measure plays a crucial role in the hierarchical merging. The dissimilarity measure has great impact on the final clustering, and data-independent properties are needed to choose the right dissimilarity measure for the problem a...

Cell biologists have developed methods to label membrane proteins with gold nanoparticles and then extract spatial point patterns of the gold particles from transmission electron microscopy images using image processing software. Previously, the resulting patterns were analyzed using the Hopkins statistic, which distinguishes nonclustered from modestly and highly clustered distributions, but is...

Human development is a paradigm that places humans as the main target of all activities, namely controling over resources, improving health and education. The Development Index (HDI) in Indonesia varies each district, especially 3T areas. area an classified underdeveloped, remote outermost terms economy, health, education infrastructure. k-Medoids method partitional clustering for grouping seve...

In recent years, there has been a great upsurge in the application of data clustering, statistical classification, and related machine learning techniques to the field of molecular biology, in particular analysis of DNA microarray expression data. Clustering methods can be used to group co-expressed genes, shedding light on gene function and co-regulation. Alternatively, they can group samples ...

Abstract Since the emergence of Bitcoin, cryptocurrencies have grown significantly, not only in terms capitalization but also number. Consequently, cryptocurrency market can be a conducive arena for investors, as it offers many opportunities. However, is difficult to understand. This study aims describe, summarize, and segment main trends entire 2018, using data analysis tools. Accordingly, we ...

Partitional graph clustering algorithms like K-means and Star necessitate a priori decisions on the number of clusters and threshold on the weight of edges to be considered, respectively. These decisions are difficult to make and their impact on clustering performance is significant. We propose a family of algorithms for weighted graph clustering that neither requires a predefined number of clu...

Partitional graph clustering algorithms like K-means and Star necessitate a priori decisions on the number of clusters and threshold on the weight of edges to be considered, respectively. These decisions are difficult to make and their impact on clustering performance can be significant. We propose a family of algorithms for weighted graph clustering that neither requires a predefined number of...