Clustering is an extensively studied data mining problem in the text domains. The difficulty finds numerous applications in customer segmentation, classification, collaborative filtering, visualization, document organization, and indexing. In text mining, clustering the sentence is one of the processes and used within general text mining tasks. Several clustering methods and algorithms are used...

A new method for segmentation of the carotid artery for classifying it as diseased or normal towards plaque diagnosis is proposed in this paper. Kernel Fuzzy CMeans clustering is used for segmenting the longitudinal section of the carotid artery using which the wall layers of the artery are identified for classifying it as diseased or normal. As a pre-processing step a–nonlinear mean filter is ...

In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algorithms in dealing with the challenges posed by large collections of vague and uncertain natural data. This paper reviews concept of fuzzy logic and fuzzy clustering. The classical fuzzy c-means algorithm is presented and its limitations are highlighted. Based on the study of the fuzzy c-means algor...

The fusion of information is a domain of research in full effervescence these last years. Because of increasing of the diversity techniques of images acquisitions, the applications of medical images segmentation, in which we are interested, necessitate most of the time to carry out the fusion of various data sources to have information with high quality. In this paper we propose a system of dat...

The prediction of time series has been widely applied to many fields such as enrollments, stocks, weather and so on. In this paper, a new prediction method based on fuzzy cognitive map with information granules is proposed, in which fuzzy cmeans clustering algorithm is used to automatically abstract information granules and transform the original time series into granular time series, and subse...

Resumen. Los cetáceos son mamíferos que son un componente importante de los ecosistemas marinos, por lo que es importante para aumentar el interés y el conocimiento de estos animales. La identificación de los cetáceos se puede realizar mediante la observación de sus patrones a través de su forma aleta caudal. En este trabajo se presenta el algoritmo de segmentación Fuzzy Cmeans (FCM) para imáge...

Content-based image retrieval is one of the techniques of image mining. Content-based image retrieval system (CBIR) has been proposed by the medical community to manage the storage and distribution of images to radiologists, physicians, specialists, clinics, and imaging centers. There are three fundamental steps for Content Based Image Retrieval. They are Visual Feature Extraction, Similarity M...

Data has an important role in all aspects of human life and so analyzing this data for discovering proper knowledge is important. Data mining refers to find useful information (extracting patterns or knowledge) from large amount of data. Clustering is an important data mining technique which aims to divide the data objects into meaningful groups called as clusters. It is the process of grouping...

Firefly algorithm is a swarm-based algorithm that can be used for solving optimization problems. In this paper, we focus on image clustering algorithm using the fuzzy set of possible solution is incorporated into the original firefly to improve the performance. The movement of the firefly still follows the original pattern but they are updated according fuzzy c-means algorithm. All method, k-me...

Software quality and reliability have become the main concern during the software development. It is very difficult to develop software without any fault. The fault-proneness of a software module is the probability that the module contains faults and a software fault is a defect that causes software failures in an executable project. Early detection of fault prone software components enables ve...