Paper: UCAM-CORE: Incorporating structured distributional similarity into STS

ACL ID S13-1011
Title UCAM-CORE: Incorporating structured distributional similarity into STS
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes methods that were sub- mitted as part of the *SEM shared task on Semantic Textual Similarity. Multiple kernels provide different views of syntactic structure, from both tree and dependency parses. The kernels are then combined with simple lex- ical features using Gaussian process regres- sion, which is trained on different subsets of training data for each run. We found that the simplest combination has the highest consis- tency across the different data sets, while in- troduction of more training data and models requires training and test data with matching qualities.