Language model trained using predicted queries from statistical machine translation
AssigneeMicrosoft Corporation
InventorsMichael Levit, Dilek Hakkani-Tur, Gokhan Tur
Life of this patent
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AssigneeMicrosoft Corporation
InventorsMichael Levit, Dilek Hakkani-Tur, Gokhan Tur
Estimating the term…
A Statistical Machine Translation (SMT) model is trained using pairs of sentences that include content obtained from one or more content sources (e.g. feed(s)) with corresponding queries that have been used to access the content. A query click graph may be used to assist in determining candidate pairs for the SMT training data. All/portion of the candidate pairs may be used to train the SMT model. After training the SMT model using the SMT training data, the SMT model is applied to content to determine predicted queries that may be used to search for the content. The predicted queries are used to train a language model, such as a query language model. The query language model may be interpolated other language models, such as a background language model, as well as a feed language model trained using the content used in determining the predicted queries.
A method for training a language model, comprising:
A computer-readable medium storing computer-executable instructions for training a query language model, comprising:
A system or extracting natural language examples for training a query language model, comprising:
Dependencies are inferred from the claim text.