The community-search problem and how to plan a successful cocktail party

By Mauro Sozio, Aristides Gionis. Knowledge Discovery and Data Mining, 2010

543 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.

Answering Elementary Science Questions by Constructing Coherent Scenes using Background Knowledge (2015, methodology): “Inspired by Sozio et al’s work (Sozio and Gionis, 2010) on finding strongly interconnected subgroups in social networks, we have developed an iterative node removal algorithm for extracting this subgraph.”
Local search of communities in large graphs (2014, methodology): “We do this by using a greedy algorithm [5].”
Effective Community Search for Large Attributed Graphs (2016, methodology): “Non-attributed [22, 11] [26, 5, 4, 15, 18] Attributed [34, 21, 20, 29, 23] ACQ (This paper)”
Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees (2013, background): “This variant is inspired by the community-search problem [30], which has many applications, such as finding thematic groups, organizing social events, tag suggestion.”
From TagME to WAT: a new entity annotator (2014, background): “Since the dense sub-graph problem is NP-hard they adopted a light approximation algorithm [15].”
Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions (2015, methodology): “[58] developed a greedy algorithm with the extension of the algorithm proposed in [123].”