Paper: Semantic Tagging of Web Search Queries

ACL ID P09-1097
Title Semantic Tagging of Web Search Queries
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

We present a novel aproach to parse web search queries for the purpose of automatic taging of the queries. We wil define a set of probabilistic context-fre rules, which generates bags (i.e. multi-sets) of words. Us- ing this new type of rule in combination with the traditional probabilistic phrase structure rules, we define a hybrid gramar, which treats each search query as a bag of chunks (i.e. phrases). A hybrid probabilistic parser is used to parse the queries. In order to take contextual information into acount, a discriminative model is used on top of the parser to re-rank the n-best parse tres gen- erated by the parser. Experiments show that our aproach outperforms a basic model, which is based on Conditional Random Fields.