Paper: Heuristic Search for Non-Bottom-Up Tree Structure Prediction

ACL ID D11-1083
Title Heuristic Search for Non-Bottom-Up Tree Structure Prediction
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011

State of the art Tree Structures Prediction techniques rely on bottom-up decoding. These approaches allow the use of context-free fea- tures and bottom-up features. We discuss the limitations of mainstream techniques in solving common Natural Language Process- ing tasks. Then we devise a new framework that goes beyond Bottom-up Decoding, and that allows a better integration of contextual features. Furthermore we design a system that addresses these issues and we test it on Hierar- chical Machine Translation, a well known tree structure prediction problem. The structure of the proposed system allows the incorpora- tion of non-bottom-up features and relies on a more sophisticated decoding approach. We show that the proposed approach can find bet- ter translations using a smaller portion of t...