Although many studies have been conducted to improve the clustering efficiency, most of the state-of-art schemes suffer from the lack of robustness and stability. This paper is aimed at proposing an efficient approach to elicit prior knowledge in terms of must-link and cannot-link from the estimated distribution of raw data in order to convert a blind clustering problem into a semi-supervised o...

The main purpose of this paper is to achieve improvement in thespeed of Fuzzy Joint Points (FJP) algorithm. Since FJP approach is a basisfor fuzzy neighborhood based clustering algorithms such as Noise-Robust FJP(NRFJP) and Fuzzy Neighborhood DBSCAN (FN-DBSCAN), improving FJPalgorithm would an important achievement in terms of these FJP-based meth-ods. Although FJP has many advantages such as r...

Abstract With the development of urbanization, problem urban traffic congestion is becoming more and serious. An improved k-means clustering algorithm was proposed to solve that traditional center could easily be affected by fall into local optimal solution. Based on big data New York City taxis, operational characteristics are analyzed. The experimental results show K-means has a better analys...

Energy consumption is considered as a critical issue in wireless sensor networks (WSNs). Batteries of sensor nodes have limited power supply which in turn limits services and applications that can be supported by them. An efcient solution to improve energy consumption and even trafc in WSNs is Data Aggregation (DA) that can reduce the number of transmissions. Two main challenges for DA are: (i)...

Supervised clustering is a data mining technique that assigns a set of data to predefined classes by analyzing dataset attributes. It is considered as an important technique for information retrieval, management, and mining in information systems. Since customer satisfaction is the main goal of organizations in modern society, to meet the requirements, 137 call center of Tehran city council is ...