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QK-Means: A clustering technique based on community detection and K-Means for deployment of cluster head nodes
(2012-08-22)
Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually deployed in a monitoring field in order to detect some physical phenomenon. Due to the low dependability of individual nodes, small radio ...
CHSMST+: An algorithm for spatial clustering
(2017-06-07)
Spatial clustering has been widely studied due to its application in several areas. However, the algorithms of such technique still need to overcome several challenges to achieve satisfactory results on a timely basis. ...
Flexible document organization: comparing fuzzy and possibilistic approaches
(Institute of Electrical and Electronics Engineers - IEEEIstanbul, 2015-08)
System flexibility means the ability of a system to manage imprecise and/or uncertain information. A lot of commercially available Information Retrieval Systems (IRS) address this issue at the level of query formulation. ...
Density-based clustering validation
(Society for Industrial and Applied Mathematics - SIAMPhiladelphia, 2014-04)
One of the most challenging aspects of clustering is validation, which is the objective and quantitative assessment of clustering results. A number of different relative validity criteria have been proposed for the validation ...
Electrical consumers data clustering through optimum-path forest
(2011-12-21)
Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the ...
Combining classification and clustering for tweet sentiment analysis
(Universidade de São Paulo - USPUniversidade Federal de São Carlos - UFSCarCentro de Robótica de São Carlos - CROBSociedade Brasileira de Computação - SBCSociedade Brasileira de Automática - SBASão Carlos, 2014-10)
The goal of sentiment analysis is to determine opinions, emotions, and attitudes presented in source material. In tweet sentiment analysis, opinions in messages can be typically categorized as positive or negative. To ...
CHSMST plus : An Algorithm for Spatial Clustering
(Ieee, 2016-01-01)
Spatial clustering has been widely studied due to its application in several areas. However, the algorithms of such technique still need to overcome several challenges to achieve satisfactory results on a timely basis. ...
Intrusion detection in computer networks using optimum-path forest clustering
(2012-12-01)
Nowadays, organizations face the problem of keeping their information protected, available and trustworthy. In this context, machine learning techniques have also been extensively applied to this task. Since manual labeling ...
ClusMAM: fast and effective unsupervised clustering of large complex datasets using metric access methods
(Association for Computing Machinery - ACMUniversity of PisaScuola Superiore Sant’AnnaPisa, 2016-04)
An efficient and effective clustering process is a core task of data mining analysis, and has become more important in the nowadays scenario of big data, where scalability is an issue. In this paper we present the ClusMAM ...
The alpha-cluster model applied to 74Ge.
(Sociedade Brasileira de FísicaMaresias, 2013-09-01)
There are few studies using cluster models in the nuclei around the intermediate and heavy mass regions. The alpha-cluster model is based on the interaction between an alpha particle and a nucleus chosen as a core. This ...