COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency

By Yutao Zhang, Jie Tang, Zhilin Yang, Jian Pei, Philip S. Yu. Knowledge Discovery and Data Mining, 2015

318 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs (2015, methodology): “We employ the network linking algorithm COSNET [ Zhang et al. , 2015 ] to link the academic social network on our system to the LinkedIn network.”
Unifying Virtual and Physical Worlds (2017, background): “…early fusion [Blaschko and Lampert 2008; Chaudhuri et al. 2009] and joint learning [Bruno and Marchand-Maillet 2009; Gao et al. 2013a; Kumar and Daum´e 2011; Kumar et al. 2011; Liu et al. 2012; Zhang et al. 2015; Zeng et al. 2006; Boden et al. 2012; Cai et al. 2013; He et al. 2014; Li et al. 2014].”
Predict Anchor Links across Social Networks via an Embedding Approach (2016, background): “This poses the problem of anchor link prediction , i.e., identifying hidden anchor links across different social networks [Liu et al. , 2014; Tan et al. , 2014; Zhang et al. , 2015; Zhang and Yu, 2015 ] .”
OAG: Toward Linking Large-scale Heterogeneous Entity Graphs (2019, methodology): “• COSNET [39] : This method is a factor graph model which considers user pairwise features as local factors and the relationship between user pairs as correlation factors.”
DualDiv: diversifying items and explanation styles in explainable hybrid recommendation (2019, methodology): “[Dataset] As target users, we randomly selected 300 users of American nationality from Last.fm dataset [17].”