Robust Classification Of Rare Queries Using Web Knowledge

The authors propose a methodology for building a practical robust query classification system that can identify thousands of query classes with reasonable accuracy, while dealing in real-time with the query volume of a commercial web search engine. They use a blind feedback technique: Given a query, they determine its topic by classifying the web search results retrieved by the query. Motivated by the needs of search advertising, they primarily focus on rare queries, which are the hardest from the point of view of machine learning, yet in aggregation account for a considerable fraction of search engine traffic.