Paper: Effective Use Of WordNet Semantics Via Kernel-Based Learning

ACL ID W05-0601
Title Effective Use Of WordNet Semantics Via Kernel-Based Learning
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2005

Research on document similarity has shown that complex representations are not more accurate than the simple bag-of- words. Term clustering, e.g. using latent semantic indexing, word co-occurrences or synonym relations using a word ontol- ogy have been shown not very effective. In particular, when to extend the similar- ity function external prior knowledge is used, e.g. WordNet, the retrieval system decreases its performance. The critical is- sues here are methods and conditions to integrate such knowledge. In this paper we propose kernel func- tions to add prior knowledge to learn- ing algorithms for document classifica- tion. Such kernels use a term similarity measure based on the WordNet hierarchy. The kernel trick is used to implement such space in a balanced and statistically co- her...