Intent classification from multiple sources when building a conversational system
AssigneeInternational Business Machines Corporation
InventorsRajendra G. UGRANI, Neil R. MALLINAR
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AssigneeInternational Business Machines Corporation
InventorsRajendra G. UGRANI, Neil R. MALLINAR
Estimating the term…
Embodiments for training a conversational system using intent classification are provided. Example utterances recommended to be associated with a particular semantic scope of intent are received from a plurality of sources. Respective ones of the example utterances from the plurality of sources are portioned and stored in a plurality of pools. The respective example utterances from the plurality of pools are collated into a unified pool according to weighting assigned to each one of the plurality of pools, the weighting associated with user actions taken on the respective example utterances. A unified set of the example utterances from the unified pool is output for selection by the user to train an intent classifier associated with the semantic scope of intent for the conversational system.
A method for training a conversational system using intent classification, by a processor, comprising:
A system for training a conversational system using intent classification, comprising:
A computer program product for training a conversational system using intent classification, by a processor, the computer program product embodied on a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:
The computer program product of claim 20, further including an executable portion that tags each of the example utterances with a string source field and version field;
Dependencies are inferred from the claim text.