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» Predicting labels for dyadic data
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KDD
2006
ACM
113views Data Mining» more  KDD 2006»
14 years 10 months ago
A new efficient probabilistic model for mining labeled ordered trees
Mining frequent patterns is a general and important issue in data mining. Complex and unstructured (or semi-structured) datasets have appeared in major data mining applications, i...
Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhi...
IUI
2010
ACM
14 years 6 months ago
Towards maximizing the accuracy of human-labeled sensor data
We present two studies that evaluate the accuracy of human responses to an intelligent agent’s data classification questions. Prior work has shown that agents can elicit accurat...
Stephanie Rosenthal, Anind K. Dey
CLEF
2009
Springer
13 years 7 months ago
ImageCLEF 2009 Medical Image Annotation Task: PCTs for Hierarchical Multi-Label Classification
In this paper, we describe an approach for the automatic medical image annotation task of the 2009 CLEF cross-language image retrieval campaign (ImageCLEF). This work is focused o...
Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, ...
BIBM
2008
IEEE
142views Bioinformatics» more  BIBM 2008»
14 years 4 months ago
Using Global Sequence Similarity to Enhance Biological Sequence Labeling
Identifying functionally important sites from biological sequences, formulated as a biological sequence labeling problem, has broad applications ranging from rational drug design ...
Cornelia Caragea, Jivko Sinapov, Drena Dobbs, Vasa...
DIS
2009
Springer
14 years 4 months ago
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Annalisa Appice, Michelangelo Ceci, Donato Malerba