Information retrieval systems conventionally assess document relevance using the bag of words model. Consequently, relevance scores of documents retrieved for different queries a...
Deepak Agarwal, Evgeniy Gabrilovich, Robert Hall, ...
With the advent of Web 2.0 tagging became a popular feature. People tag diverse kinds of content, e.g. products at Amazon, music at Last.fm, images at Flickr, etc. Clicking on a t...
Web search components such as ranking and query suggestions analyze the user data provided in query and click logs. While this data is easy to collect and provides information abo...
Jeff Huang, Ryen W. White, Georg Buscher, Kuansan ...
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
We introduce a new approach to analyzing click logs by examining both the documents that are clicked and those that are bypassed--documents returned higher in the ordering of the ...
Atish Das Sarma, Sreenivas Gollapudi, Samuel Ieong