Graph-based Text Similarity
Graph-Based Text Similarity is a text similarity measurement approach that represents textual elements and their relationships as graph structures, where nodes denote linguistic units and edges capture semantic or syntactic dependencies, distinguishing it from vector-space or sequence-based models by explicitly modeling structural and relational information.
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14K
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416
Authors
188
Institutions
Publications per year
2017–2026
38
Parents
150
Review Graph Based Online Store Review Spammer Detection
Guan Wang, Sihong Xie, Bing Liu et al. · 2011 · 382 citations
You are how you click: clickstream analysis for Sybil detection
Gang Wang, Tristan Konolige, Christo Wilson et al. · 2013 · 258 citations
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Carnegie Mellon University
Pittsburgh, United States
5 h-index
8 publications
474 citations
University of Michigan
Ann Arbor, United States
5 h-index
11 publications
3.9K citations
Stanford University
Stanford, United States
5 h-index
10 publications
5K citations
University of Maryland, College Park
College Park, United States
4 h-index
9 publications
753 citations

University of North Texas
Denton, United States
3 h-index
6 publications
1.2K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
3 h-index
7 publications
96 citations

City University of Hong Kong
Hong Kong, Hong Kong
3 h-index
9 publications
474 citations

Peking University
Beijing, China
3 h-index
7 publications
261 citations
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Conference · 3 publications · 379 citations
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3 publications · 133 citations
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Conference · 2 publications · 3.5K citations
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2 publications · 134 citations
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Repository · 2 publications · 222 citations
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