Name
Abstract | ||
|---|---|---|
The measurement of phrasal semantic relatedness is an important metric for many natural language processing applications. In this paper, we present three approaches for measuring phrasal semantics, one based on a semantic network model, another on a distributional similarity model, and a hybrid between the two. Our hybrid approach achieved an F-measure of 77.4% on the task of evaluating the semantic similarity of words and compositional phrases. |
Year | Venue | Field |
|---|---|---|
2013 | joint conference on lexical and computational semantics | Semantic similarity,Computer science,Semantic network,Artificial intelligence,Natural language processing,Semantics,Semantic computing,Semantic compression |
DocType | Volume | Citations |
Conference | abs/1708.05801 | 1 |
PageRank | References | Authors |
0.37 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Reda Siblini | 1 | 8 | 2.46 |
| Leila Kosseim | 2 | 313 | 43.58 |