cid 20f623c30109c3d016648df24b06f4abfbfe206595729012f904230c09dee6dc · original · via openalex
Title: FENNEL Authors: Charalampos E. Tsourakakis; Christos Gkantsidis; Božidar Radunović; Milan Vojnović Venue: ACM International Conference on Web Search and Data Mining (WSDM) Year: 2014 Canonical: doi:10.1145/2556195.2556213 URL: https://doi.org/10.1145/2556195.2556213 Collector: openalex OA: false ABSTRACT Balanced graph partitioning in the streaming setting is a key problem to enable scalable and efficient computations on massive graph data such as web graphs, knowledge graphs, and graphs arising in the context of online social networks. Two families of heuristics for graph partitioning in the streaming setting are in wide use: place the newly arrived vertex in the cluster with the largest number of neighbors or in the cluster with the least number of non-neighbors.