- Jamie Callan, Kevyn Collins-Thompson. 2008. Robust model estimation methods for information retrieval. Abstract: Information retrieval algorithms attempt to match a user's description of their information need with relevant information in a collection of documents or other data. Applications include Web search engines, filtering and recommendation systems, computer-assisted language tutors, and many others. A key challenge of retrieval algorithms is to perform effective matching when many factors, such as the user's true information need, may be highly uncertain and can only be partially observed via a small number of keywords. This dissertation develops broadly applicable algorithms for measuring and exploiting such uncertainty in retrieval algorithms to make them more effective and reliable. Our contributions include new theoretical models, statistical methods, evaluation techniques, and retrieval algorithms. 
