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» Approximate data mining in very large relational data
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152
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SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
14 years 4 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
ACL
2012
13 years 4 months ago
Towards the Unsupervised Acquisition of Discourse Relations
This paper describes a novel approach towards the empirical approximation of discourse relations between different utterances in texts. Following the idea that every pair of event...
Christian Chiarcos
AUSDM
2006
Springer
118views Data Mining» more  AUSDM 2006»
15 years 5 months ago
Efficiently Identifying Exploratory Rules' Significance
How to efficiently discard potentially uninteresting rules in exploratory rule discovery is one of the important research foci in data mining. Many researchers have presented algor...
Shiying Huang, Geoffrey I. Webb
126
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PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
14 years 11 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
135
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BIRTHDAY
2003
Springer
15 years 7 months ago
Spatial Data Management for Virtual Product Development
Abstract: In the automotive and aerospace industry, millions of technical documents are generated during the development of complex engineering products. Particularly, the universa...
Hans-Peter Kriegel, Martin Pfeifle, Marco Pöt...