ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
: Topic Modeling Ensembles Zhiyong Shen, Ping Luo, Shengwen Yang, Xukun Shen HP Laboratories HPL-2010-158 Topic model, Ensemble In this paper we propose a framework of topic model...
ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
Given a large graph, like a computer network, which k nodes should we immunize (or monitor, or remove), to make it as robust as possible against a computer virus attack? We need (...
ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
Abstract--The problem of data stream classification is challenging because of many practical aspects associated with efficient processing and temporal behavior of the stream. Two s...
ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
Discovering patterns in a sequence is an important aspect of data mining. One popular choice of such patterns are episodes, patterns in sequential data describing events that often...
ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
We present a mining system that can predict the future health status of the patient using the temporal trajectories of health status of a set of similar patients. The main noveltie...
DMIN
2010
13 years 5 months ago
2010
Recently Vapnik et al. [11, 12, 13] introduced a new learning model, called Learning Using Privileged Information (LUPI). In this model, along with standard training data, the tea...
ADMA
2010
Springer
13 years 5 months ago
2010
Springer
Multi-Agent Clustering (MAC) requires a mechanism for identifying the most appropriate cluster configuration. This paper reports on experiments conducted with respect to a number o...
ADMA
2010
Springer
13 years 5 months ago
2010
Springer
This paper reports on an investigation to compare a number of strategies to include negated features within the process of Inductive Rule Learning (IRL). The emphasis is on generat...