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» Learning the Relative Importance of Features in Image Data
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111
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IJCNLP
2005
Springer
15 years 9 months ago
Topic Tracking Based on Linguistic Features
This paper explores two linguistically motivated restrictions on the set of words used for topic tracking on newspaper articles: named entities and headline words. We assume that n...
Fumiyo Fukumoto, Yusuke Yamaji
172
Voted
AMAI
2007
Springer
15 years 3 months ago
Relational concept discovery in structured datasets
Relational datasets, i.e., datasets in which individuals are described both by their own features and by their relations to other individuals, arise from various sources such as d...
Marianne Huchard, Mohamed Rouane Hacene, Cyril Rou...
151
Voted
MM
2009
ACM
269views Multimedia» more  MM 2009»
15 years 10 months ago
Semi-supervised topic modeling for image annotation
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...
ICCV
2009
IEEE
16 years 8 months ago
Using machine learning to predict where people look
For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a scene. Where eye tracking devices are not a viable o...
Tilke Judd, Krista Ehinger, Fr´edo Durand, Antoni...
166
Voted
SIGIR
2008
ACM
15 years 3 months ago
Learning to reduce the semantic gap in web image retrieval and annotation
We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
Changhu Wang, Lei Zhang 0001, Hong-Jiang Zhang