Location of Repository

UBC UOS-TYPED: Regression for Typed-similarity

By Eneko Agirre, Nikolaos Aletras, Aitor Gonzalez-agirre, German Rigau and Mark Stevenson

Abstract

We approach the typed-similarity task using a range of heuristics that rely on information from the appropriate metadata fields for each type of similarity. In addition we train a linear regressor for each type of similarity. The results indicate that the linear regression is key for good performance. Our best system was ranked third in the task.

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.310.8276
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.aclweb.org/antholog... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.