Paper: Modeling Sentences in the Latent Space

ACL ID P12-1091
Title Modeling Sentences in the Latent Space
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2012
Authors

Sentence Similarity is the process of comput- ing a similarity score between two sentences. Previous sentence similarity work finds that latent semantics approaches to the problem do not perform well due to insufficient informa- tion in single sentences. In this paper, we show that by carefully handling words that are not in the sentences (missing words), we can train a reliable latent variable model on sentences. In the process, we propose a new evaluation framework for sentence similarity: Concept Definition Retrieval. The new frame- work allows for large scale tuning and test- ing of Sentence Similarity models. Experi- ments on the new task and previous data sets show significant improvement of our model over baselines and other traditional latent vari- able models. Our results indicate...