This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The res...
Jianfeng Gao, Qiang Wu, Chris Burges, Krysta Marie...
Tables are a universal idiom to present relational data. Billions of tables on Web pages express entity references, attributes and relationships. This representation of relational...
Work on evaluating and improving the relevance of web search engines typically use human relevance judgments or clickthrough data. Both these methods look at the problem of learni...
Hao Ma, Raman Chandrasekar, Chris Quirk, Abhishek ...
Web directory hierarchy is critical to serve user’s search request. Creating and maintaining such directories without human experts involvement requires good classification of we...
We present a method for learning to find English to Chinese transliterations on the Web. In our approach, proper nouns are expanded into new queries aimed at maximizing the probab...