The Fuzzy c-means is one of the most popular ongoing area of research among all types of
researchers including Computer science, Mathematics and other areas of engineering, as …

To promote sustainable development, the smart city implies a global vision that merges
artificial intelligence, big data, decision making, information and communication technology …

Introducing a handful of pairwise constraints into fuzzy clustering models to revise
memberships has been proven beneficial to boosting clustering performance. However …

Data mining (DM) is an instrument of pattern detection and retrieval of knowledge from a
large quantity of data. Many robust early detection services and other health-related …

Clustering is one type of unsupervised learning where the goal is to partition the set of
objects into groups called clusters. Faced to the difficulty to design a general purpose …

Semisupervised clustering methods improve performance by randomly selecting pairwise
constraints, which may lead to redundancy and instability. In this context, active clustering is …

Fuzzy co-clustering algorithms are the effective techniques for multi-dimensional clustering
in which all features are considered of equal importance (relevance). In fact, the features' …

Clustering is a well-known unsupervised machine learning approach capable of
automatically grouping discrete sets of instances with similar characteristics. Constrained …

Text mining has been a popular research topic in the field of natural language processing.
With the emergence of Web 2.0 and the development of social software, the amount of text …

In semisupervised fuzzy clustering, this article extends the traditional pairwise constraint (ie,
must-link or cannot-link) to fuzzy pairwise constraint. The fuzzy pairwise constraint allows a …