Ranking documents based on large data sets

摘要

A system ranks documents based, at least in part, on a ranking model. The ranking model may be generated to predict the likelihood that a document will be selected. The system may receive a search query and identify documents relating to the search query. The system may then rank the documents based, at least in part, on the ranking model and form search results for the search query from the ranked documents.

主权项

1. A computer-implemented method of ranking search results based on a likelihood of user selection, the method comprising:
receiving a search query from a user; obtaining a plurality of search results that satisfy the search query, wherein each search result identifies a respective document of a plurality of documents; identifying a respective condition for each document of the plurality of documents, wherein each condition comprises one or more features of the user, the search query, and the document; obtaining a ranking model that produces a score for a particular document given a particular condition for the particular document, the score representing a likelihood that the user will select the particular document when identified by a search result provided in response to the search query, the ranking model being trained on training instances that each identify a first document selected by a particular user when the first document was identified in search results provided to the particular user in response to a particular search query; using the ranking model to compute a respective score for each document of the plurality of documents; and ranking the plurality of search results according to the respective computed score for each document of the plurality of documents.