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DAWAK
2001
Springer
15 years 4 months ago
A Theoretical Framework for Association Mining Based on the Boolean Retrieval Model
Data mining has been defined as the non- trivial extraction of implicit, previously unknown and potentially useful information from data. Association mining is one of the important...
Peter Bollmann-Sdorra, Aladdin Hafez, Vijay V. Rag...
ISCI
2008
83views more  ISCI 2008»
14 years 11 months ago
A diversity maintaining population-based incremental learning algorithm
In this paper we propose a new probability update rule and sampling procedure for population-based incremental learning. These proposed methods are based on the concept of opposit...
Mario Ventresca, Hamid R. Tizhoosh
LREC
2008
60views Education» more  LREC 2008»
15 years 1 months ago
A Framework for Identity Resolution and Merging for Multi-source Information Extraction
In the context of ontology-based information extraction, identity resolution is the process of deciding whether an instance extracted from text refers to a known entity in the tar...
Milena Yankova, Horacio Saggion, Hamish Cunningham
COLING
2002
14 years 11 months ago
Inducing Information Extraction Systems for New Languages via Cross-language Projection
Information extraction (IE) systems are costly to build because they require development texts, parsing tools, and specialized dictionaries for each application domain and each na...
Ellen Riloff, Charles Schafer, David Yarowsky
HIPC
2003
Springer
15 years 5 months ago
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...