SEMANTICALLY-RELEVANT DISCOVERY OF SOLUTIONS

摘要

Systems, methods, and computer-readable media for providing semantically-relevant discovery of solutions are described herein. In some examples, a computing device can receive an input, such as a query. The computing device can process each word of the input sequentially to determine a semantic representation of the input. Techniques and technologies described herein determine a response to the input, such as an answer, based on the semantic representation of the input matching a semantic representation of the response. An output including one or more relevant responses to the request can then be provided to the requestor. Example techniques described herein can apply machine learning to train a model with click-through data to provide semantically-relevant discovery of solutions. Example techniques described herein can apply recurrent neural networks (RNN) and/or long short term memory (LSTM) cells in the machine learning model.

主权项

1. A system comprising:
a processor; a computer-readable media including instructions for a semantic relevance framework, for actuation by the processor, the semantic relevance framework comprising:
a mapping module including instructions to configure the processor to sequentially process one or more words of a query and determine a semantic representation of the query; anda matching module including instructions to configure the processor to identify one or more responses with corresponding semantic representations that are substantially similar to the semantic representation of the query.