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PAKDD
2010
ACM
134views Data Mining» more  PAKDD 2010»
13 years 10 months ago
Generating Diverse Ensembles to Counter the Problem of Class Imbalance
Abstract. One of the more challenging problems faced by the data mining community is that of imbalanced datasets. In imbalanced datasets one class (sometimes severely) outnumbers t...
T. Ryan Hoens, Nitesh V. Chawla
PAKDD
2010
ACM
169views Data Mining» more  PAKDD 2010»
13 years 10 months ago
Correspondence Clustering: An Approach to Cluster Multiple Related Spatial Datasets
Domain experts are frequently interested to analyze multiple related spatial datasets. This capability is important for change analysis and contrast mining. In this paper, a novel ...
Vadeerat Rinsurongkawong, Christoph F. Eick
PAKDD
2010
ACM
208views Data Mining» more  PAKDD 2010»
13 years 10 months ago
Efficient Pattern Mining of Uncertain Data with Sampling
Mining frequent itemsets from transactional datasets is a well known problem with good algorithmic solutions. In the case of uncertain data, however, several new techniques have be...
Toon Calders, Calin Garboni, Bart Goethals
PAKDD
2010
ACM
215views Data Mining» more  PAKDD 2010»
13 years 10 months ago
Mining Closed Episodes from Event Sequences Efficiently
Recent studies have proposed different methods for mining frequent episodes. In this work, we study the problem of mining closed episodes based on minimal occurrences. We study the...
Wenzhi Zhou, Hongyan Liu, Hong Cheng
PAKDD
2010
ACM
134views Data Mining» more  PAKDD 2010»
13 years 10 months ago
A Robust Seedless Algorithm for Correlation Clustering
Abstract. Finding correlation clusters in the arbitrary subspaces of highdimensional data is an important and a challenging research problem. The current state-of-the-art correlati...
Mohammad S. Aziz, Chandan K. Reddy
DEXAW
2005
IEEE
133views Database» more  DEXAW 2005»
13 years 10 months ago
Inductive Databases: Towards a New Generation of Databases for Knowledge Discovery
Data mining applications are typically used in the decision making process. The Knowledge Discovery Process (KDD process for short) is a typical iterative process, in which not on...
Rosa Meo
KDD
2010
ACM
287views Data Mining» more  KDD 2010»
13 years 10 months ago
Designing efficient cascaded classifiers: tradeoff between accuracy and cost
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...
Vikas C. Raykar, Balaji Krishnapuram, Shipeng Yu
KDD
2010
ACM
270views Data Mining» more  KDD 2010»
13 years 10 months ago
An energy-efficient mobile recommender system
The increasing availability of large-scale location traces creates unprecedent opportunities to change the paradigm for knowledge discovery in transportation systems. A particular...
Yong Ge, Hui Xiong, Alexander Tuzhilin, Keli Xiao,...
KDD
2010
ACM
250views Data Mining» more  KDD 2010»
13 years 10 months ago
On community outliers and their efficient detection in information networks
Linked or networked data are ubiquitous in many applications. Examples include web data or hypertext documents connected via hyperlinks, social networks or user profiles connected...
Jing Gao, Feng Liang, Wei Fan, Chi Wang, Yizhou Su...