Ontology-crowd-relevance deep response generation
First Claim
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1. A system comprising:
- one or more processors;
memory; and
one or more modules stored in the memory and executable by the one or more processors to perform operations comprising;
accessing a plurality of data items, the plurality of data items being associated with one or more labels and one or more sub-labels;
determining, using at least one of latent Dirichlet allocation, a word cloud, and a classifier model, an ontology for the plurality of data items the ontology including one or more ontological elements, the ontology including a product of the label and the sub-label, the one or more ontological elements comprise a label of the one or more labels that is semantically associated with a data item of the data items and a sub-label of the sub-labels that is semantically associated with a portion of the data item;
crowdsourcing response templates including sending, to a plurality of devices with associated different users, a request for a respective user of the different users to generate one or more response templates based on the one or more ontological elements, one or more of the response templates including a question with a subject of the question as a slot and an ontological element of the one or more ontological elements in the question;
receiving, from the plurality of devices, the response templates generated by the different users and directed to the one or more ontological elementsstoring the response templates in a database;
receiving a new data item associated with the one or more ontological elements; and
based at least in part on receiving the new data item, accessing an individual response template of the response templates stored in the database, the individual response template mapped to the one or more ontological elements.
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Abstract
Generating responses to input utilizing an ontology-crowd-relevance methodology is described. The techniques described herein access a plurality of data items and determine an ontology associated with the plurality of data items. The ontology includes one or more ontological elements. Furthermore, the techniques describe sending, to a plurality of devices, a request to generate response templates based on the one or more ontological elements and receiving, from the plurality of devices, the response templates directed to the one or more ontological elements.
15 Citations
11 Claims
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1. A system comprising:
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one or more processors; memory; and one or more modules stored in the memory and executable by the one or more processors to perform operations comprising; accessing a plurality of data items, the plurality of data items being associated with one or more labels and one or more sub-labels; determining, using at least one of latent Dirichlet allocation, a word cloud, and a classifier model, an ontology for the plurality of data items the ontology including one or more ontological elements, the ontology including a product of the label and the sub-label, the one or more ontological elements comprise a label of the one or more labels that is semantically associated with a data item of the data items and a sub-label of the sub-labels that is semantically associated with a portion of the data item; crowdsourcing response templates including sending, to a plurality of devices with associated different users, a request for a respective user of the different users to generate one or more response templates based on the one or more ontological elements, one or more of the response templates including a question with a subject of the question as a slot and an ontological element of the one or more ontological elements in the question; receiving, from the plurality of devices, the response templates generated by the different users and directed to the one or more ontological elements storing the response templates in a database; receiving a new data item associated with the one or more ontological elements; and based at least in part on receiving the new data item, accessing an individual response template of the response templates stored in the database, the individual response template mapped to the one or more ontological elements. - View Dependent Claims (2, 3, 4, 5)
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6. A computer-implemented method comprising:
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accessing a plurality of data items, the plurality of data items being associated with one or more labels and one or more sub-labels; determining, using at least one of latent Dirichlet allocation, a word cloud, and a classifier model, an ontology for the plurality of data items, the ontology including one or more ontological elements, the ontology including a product of one or more labels of the one or more labels and one or more sub-labels of the one or more sub-labels, the one or more ontological elements comprise a label of the one or more labels that is semantically associated with a data item of the data items, and a sub-label of the one or more sub-labels that is semantically associated with a portion of the data item; crowdsourcing response templates including sending, to a plurality of devices, a request for respective users of the plurality of devices to generate a response template associated with a label of the one or more labels and a sub-label of the one or more sub-labels; receiving, from the plurality of devices, a plurality of response templates generated by the respective users and associated with the label and the sub-label, wherein the plurality of response templates are applicable to data items associated with the label and sub-label, one or more of the plurality of response templates including a question with a subject of the question as a slot and the label and the sub-label in the question; storing at least some response templates of the plurality of response templates in a database; receiving a new data item associated with the one or more ontological elements; and based at least in part on receiving the new data item, accessing individual response templates of the response templates stored in the database, the individual response templates mapped to the one or more ontological elements. - View Dependent Claims (7, 8, 9, 10, 11)
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Specification