Paper: Using Search-Logs to Improve Query Tagging

ACL ID P12-2047
Title Using Search-Logs to Improve Query Tagging
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2012

Syntactic analysis of search queries is im- portant for a variety of information-retrieval tasks; however, the lack of annotated data makes training query analysis models diffi- cult. We propose a simple, efficient proce- dure in which part-of-speech tags are trans- ferred from retrieval-result snippets to queries at training time. Unlike previous work, our final model does not require any additional re- sources at run-time. Compared to a state-of- the-art approach, we achieve more than 20% relative error reduction. Additionally, we an- notate a corpus of search queries with part- of-speech tags, providing a resource for future work on syntactic query analysis.