Attribute Extraction For Classification
Attribute Extraction for Classification is a computational method that identifies and isolates distinguishing semantic or syntactic features from product descriptions or textual data to enable their systematic categorization into predefined classes based on intrinsic characteristics.
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2.5K
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105
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49
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2017–2026
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PANDA: Pose Aligned Networks for Deep Attribute Modeling
Ning Zhang, Manohar Paluri, Marc’Aurelio Ranzato et al. · 2014 · 500 citations
Text mining for product attribute extraction
Rayid Ghani, Katharina Probst, Yan Liu et al. · ACM SIGKDD Explorations Newsletter · 2006 · 241 citations
Learning to Generate Product Reviews from Attributes
Li Dong, Shaohan Huang, Furu Wei et al. · 2017 · 186 citations · Full text
Hierarchical Fine-Grained Image Forgery Detection and Localization
Xiao Guo, Xiaohong Liu, Zhiyuan Ren et al. · 2023 · 165 citations
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Google (United States)
Mountain View, United States
3 h-index
4 publications
133 citations
Meta (Israel)
Tel Aviv, Israel
2 h-index
8 publications
2.1K citations
University of California, Berkeley
Berkeley, United States
2 h-index
4 publications
1K citations
Berkeley College
New York, United States
1 h-index
2 publications
1K citations

Chongqing University
Chongqing, China
1 h-index
4 publications
120 citations

Southeast University
Nanjing, China
1 h-index
3 publications
54 citations

Indian Institute of Technology Madras
Chennai, India
1 h-index
1 publications
17 citations

Zhejiang University of Technology
Hangzhou, China
1 h-index
5 publications
60 citations
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1 publications · 49 citations
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1 publications · 30 citations
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1 publications · 48 citations
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