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Relation Strength-Aware Clustering of Heterogeneous Information Networks with Incomplete Attributes

Summary: Model-based clustering for heterogeneous networks with incomplete attributes, mapping objects into a space using attributes and links. Learns link-type strengths for clustering, with iterative refinement weights and clustering quality reinforce. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10487
Venue
VLDB
Year
2012
Pagerank
7.0524417e-05
Overall Rank
3,484 | 75.77%
DOI
-

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
313 Graph Clustering Based on Structural/Attribute Similarities 2009 VLDB 0.00028097557
3,817 A Particle-and-Density Based Evolutionary Clustering Method for Dynamic Networks 2009 VLDB 6.730222e-05
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