Name
Abstract | ||
|---|---|---|
This paper introduces a linear time graph-based soft clustering algorithm. The algorithm applies a simple idea: given a graph, vertex pairs are assigned to the same cluster if either vertex has maximal affinity to the other. Clusters of varying size, shape, and density are found automatically making the algorithm suited to tasks such Word Sense Induction (WSI), where the number of classes is unknown and where class distributions may be skewed. The algorithm is applied to two WSI tasks, obtaining results comparable with those of systems adopting existing, state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-37247-6_30 | CICLing |
Keywords | Field | DocType |
varying size,maximal affinity,vertex pair,wsi task,simple idea,soft clustering algorithm,linear time,graph-based soft clustering algorithm,word sense induction,class distribution,state-of-the-art method,word sense | Cluster (physics),Fuzzy clustering,Computer science,Theoretical computer science,Artificial intelligence,Natural language processing,Time complexity,Reverse-delete algorithm,Graph,Vertex (geometry),Word-sense induction,Algorithm,Word-sense disambiguation | Conference |
Citations | PageRank | References |
15 | 0.69 | 35 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Hope | 1 | 15 | 0.69 |
| Bill Keller | 2 | 87 | 6.26 |