Paper: Joint Annotation of Search Queries

ACL ID P11-1011
Title Joint Annotation of Search Queries
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

Marking up search queries with linguistic an- notations such as part-of-speech tags, cap- italization, and segmentation, is an impor- tant part of query processing and understand- ing in information retrieval systems. Due to their brevity and idiosyncratic structure, search queries pose a challenge to existing NLP tools. To address this challenge, we propose a probabilistic approach for perform- ing joint query annotation. First, we derive a robust set of unsupervised independent an- notations, using queries and pseudo-relevance feedback. Then, we stack additional classi- fiers on the independent annotations, and ex- ploit the dependencies between them to fur- ther improve the accuracy, even with a very limited amount of available training data. We evaluate our method using a range of quer...