Paper: Incorporating Topic Information Into Semantic Analysis Models

ACL ID P04-3025
Title Incorporating Topic Information Into Semantic Analysis Models
Venue Annual Meeting of the Association of Computational Linguistics
Session System Demonstration
Year 2004
Authors

This paper reports experiments in classifying texts based upon their favorability towards the subject of the text using a feature set enriched with topic information on a small dataset of music reviews hand-annotated for topic. The results of these experiments suggest ways in which incorporating topic information into such models may yield improvement over models which do not use topic information.