Named entity recognition in query

摘要

Named Entity Recognition in Query (NERQ) involves detection of a named entity in a given query and classification of the named entity into one or more predefined classes. The predefined classes may be based on a predefined taxonomy. A probabilistic approach may be taken to detecting and classifying named entities in queries, the approach using either query log data or click through data and Weakly Supervised Latent Dirichlet Allocation (WS-LDA) to construct and train a topic model.

主权项

1. A computer-implemented method of recognizing named entities in a query with a recognition module operating on a processor, the method comprising:
receiving an input query from a user; detecting a named entity in the input query; representing the input query as one or more triples (e, t, c), wherein e represents the detected named entity, t represents a context of the detected named entity, and c represents a classification for the detected named entity that is determined based at least in part on a trained probabilistic topic model and a predefined taxonomy; calculating a joint probability for individual ones of the one or more triples; identifying a largest joint probability associated with a respective one of the one or more triples; predicting an assigned classification for the detected named entity based at least in part on the identified largest joint probability; and outputting the detected named entity and the assigned classification to the user.