P
Paul Haahr
Researcher at Google
Publications - 34
Citations - 1155
Paul Haahr is an academic researcher from Google. The author has contributed to research in topics: Web search query & Ranking (information retrieval). The author has an hindex of 14, co-authored 34 publications receiving 1155 citations.
Papers
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Patent
Information retrieval based on historical data
Anurag Acharya,Matt Cutts,Jeffrey Dean,Paul Haahr,Monika Henzinger,Urs Hoelzle,Steve Lawrence,Karl Pfleger,Olcan Sercinoglu,Simon Tong +9 more
TL;DR: In this paper, a system (125) identifies a document and obtains one or more types of history data associated with the document, and generates a score for the document based on at least part of the history data.
Patent
System and method for providing search query refinements
Paul Haahr,Steven D. Baker +1 more
TL;DR: In this paper, a system and method for providing search query refinements are presented, where a stored query and a stored document are associated as a logical pairing and a weight is assigned to the logical pairing.
Patent
Multi-stage query processing system and method for use with tokenspace repository
TL;DR: In this paper, a multi-stage query processing system and method enables multistage query scoring, including snippet generation, through incremental document reconstruction facilitated by a multilevel mapping scheme.
Patent
Document scoring based on query analysis
Jeffrey Dean,Paul Haahr,Monika Henzinger,Steve Lawrence,Karl Pfleger,Olcan Sercinoglu,Simon Tong +6 more
TL;DR: In this paper, a system may determine an extent to which a document is selected when the document is included in a set of search results, generate a score for the document based, at least in part, on the degree to which the document was selected, and rank the document with regard to at least one other document based on the score.
Patent
Systems and methods for providing search query refinements
Steven D. Baker,Paul Haahr +1 more
TL;DR: In this paper, a system and method for generating query refinement suggestions may include collecting refinement data for at least one received source query and then clustering the collected refinement data to form a cluster.