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» Learning Classifiers from Semantically Heterogeneous Data
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ICML
2000
IEEE
14 years 9 months ago
Discovering Homogeneous Regions in Spatial Data through Competition
If all features causing heterogeneity were observed, a mixture of experts approach (Jacobs et al., 1991) is likely to be superior to using a single model. When unobserved or very n...
Slobodan Vucetic, Zoran Obradovic
CORR
2002
Springer
97views Education» more  CORR 2002»
13 years 8 months ago
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
This paper presents a simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (thumbs down). The classification of a review is...
Peter D. Turney
MCS
2004
Springer
14 years 2 months ago
Learn++.MT: A New Approach to Incremental Learning
An ensemble of classifiers based algorithm, Learn++, was recently introduced that is capable of incrementally learning new information from datasets that consecutively become avail...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
SSDBM
2000
IEEE
155views Database» more  SSDBM 2000»
14 years 1 months ago
Knowledge-Based Integration of Neuroscience Data Sources
The need for information integration is paramount in many biological disciplines, because of the large heterogeneity in both the types of data involved and in the diversity of app...
Amarnath Gupta, Bertram Ludäscher, Maryann E....
JIS
2010
125views more  JIS 2010»
13 years 7 months ago
Representing and sharing folksonomies with semantics
Websites that provide content creation and sharing features have become quite popular recently. These sites allow users to categorize and browse content using ‘tags’ or free-t...
Hak Lae Kim, Stefan Decker, John G. Breslin