We study the problem of context-sensitive ranking for document retrieval, where a context is defined as a sub-collection of documents, and is specified by queries provided by do...
Internet search engines identify web pages that contain user-specified keywords, and then rank these pages according to their (heuristically assessed) relevance to the user’s qu...
People are seldom aware that their search queries frequently mismatch a majority of the relevant documents. This may not be a big problem for topics with a large and diverse set o...
In this paper we process and analyze web search engine query and click data from the perspective of the documents (URL’s) selected. We initially define possible document categor...
Structured documents contain elements defined by the author(s) and annotations assigned by other people or processes. Structured documents pose challenges for probabilistic retrie...