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ICMLA
2004
15 years 5 months ago
Outlier detection and evaluation by network flow
Detecting outliers is an important topic in data mining. Sometimes the outliers are more interesting than the rest of the data. Outlier identification has lots of applications, su...
Ying Liu, Alan P. Sprague
GECCO
2008
Springer
250views Optimization» more  GECCO 2008»
15 years 5 months ago
Community detection in social networks with genetic algorithms
A new genetic algorithm to detect communities in social networks is presented. The algorithm uses a fitness function able to identify groups of nodes in the network having dense ...
Clara Pizzuti
CORR
2007
Springer
170views Education» more  CORR 2007»
15 years 4 months ago
The structure of verbal sequences analyzed with unsupervised learning techniques
Data mining allows the exploration of sequences of phenomena, whereas one usually tends to focus on isolated phenomena or on the relation between two phenomena. It offers invaluab...
Catherine Recanati, Nicoleta Rogovschi, Youn&egrav...
WSDM
2012
ACM
329views Data Mining» more  WSDM 2012»
13 years 11 months ago
Beyond 100 million entities: large-scale blocking-based resolution for heterogeneous data
A prerequisite for leveraging the vast amount of data available on the Web is Entity Resolution, i.e., the process of identifying and linking data that describe the same real-worl...
George Papadakis, Ekaterini Ioannou, Claudia Niede...
ICTAI
2007
IEEE
15 years 10 months ago
Dragon Toolkit: Incorporating Auto-Learned Semantic Knowledge into Large-Scale Text Retrieval and Mining
The majority of text retrieval and mining techniques are still based on exact feature (e.g. words) matching and unable to incorporate text semantics. Many researchers believe that...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu