English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Clustering is an important task in the process of data analysis which can be viewed as a data modeling technique that provides an attractive mechanism to automatically find the hidden structure of large data sets (Jain et al., 1999). Informally, this task consists of the division of data items (objects, instances, etc.) into groups or categories, such that all objects in the same group are similar to each other, while dissimilar from objects in the other groups. Clustering plays an important role in data mining applications such as Web analysis, information retrieval, medical diagnosis, and many other domains. Recently, we have proposed a clustering method based on the concept of b-coloring of a graph (Irving & Manlov, 1999). A graph b-coloring is an assignment of colors to the vertices of the graph such that: i. no two adjacent vertices (vertices joined by an weighted edge representing the dissimilarity between objects) have the same color (

Toward Improving b-Coloring Based Clustering Using a Greedy re-Coloring Algorithm