SYSTEMS AND METHODS FOR LEARNING NEW TRAINED CONCEPTS USED TO RETRIEVE CONTENT RELEVANT TO THE CONCEPTS LEARNED
A system configured for learning new trained concepts used to retrieve content relevant to the concepts learned. The system may comprise one or more hardware processors configured by machine-readable instructions to obtain one or more digital media items. The one or more hardware processors may be further configured to obtain an indication conveying a concept to be learned from the one or more digital media items. The one or more hardware processors may be further configured to receive feedback associated with individual ones of the one or more digital media items. The one or more hardware processors may be configured to obtain individual neural network representations for the individual ones of the one or more digital media items. The one or more hardware processors may be configured to determine a trained concept based on the feedback and the neural network representations of the one or more digital media items.
1 . A system configured for learning new trained concepts used to retrieve content relevant to the concepts learned, the system comprising:
one or more hardware processors configured by machine-readable instructions to:
obtain one or more digital media items;
obtain an indication conveying a concept to be learned from the one or more digital media items;
receive feedback associated with individual ones of the one or more digital media items, wherein the feedback is based on one or both of (1) selection of one or more positive examples of the concept to be learned from the one or more digital media items, or (2) selection of one or more negative examples of the concept to be learned from the one or more digital media items, a given positive example being a digital media item comprising the concept to be learned, and a given negative example being a digital media item lacking the concept to be learned;
obtain individual neural network representations for the individual ones of the one or more digital media items, a given neural network representation including one or more neural network layers; and
determine a trained concept based on (1) the feedback and (2) the neural network representations of the one or more digital media items, the trained concept being usable for retrieving digital media items relevant to the concept to be learned.
2 . The system of claim 1 , wherein determining the trained concept includes determining additional neural network layers based on (1) the feedback and (2) the neural network representations of the one or more digital media items.
3 . The system of claim 1 , wherein receiving feedback for individual ones of the digital media items includes obtaining confirmation of information associated with the individual ones of the digital media items.
4 . The system of claim 1 , wherein receiving feedback for individual ones of the digital media items includes obtaining confirmation of previous predictions related to the concept to be learned.
5 . The system of claim 1 , wherein the one or more hardware processors are further configured by machine-readable instructions to:
receive queries for digital media items related to the concept being learned; and
use the trained concept to obtain results of the queries.
6 . The system of claim 5 , wherein the one or more hardware processors are further configured by machine-readable instructions to:
receive additional feedback associated with the results of the queries, wherein the feedback is based on one or both of (1) selection of one or more positive examples of the concept being learned from results of the queries, or (2) selection of one or more negative examples of the concept being learned from the results of the queries.
7 . The system of claim 6 , wherein the one or more hardware processors are further configured by machine-readable instructions to:
adjust the trained concept based on the additional feedback and neural network representations of the results of the queries.
8 . A method for learning new trained concepts used to retrieve content relevant to the concepts learned with a system comprising one or more hardware processors, the method comprising:
obtaining, with the one or more hardware processors, one or more digital media items;
obtaining, with the one or more hardware processors, an indication conveying a concept to be learned from the one or more digital media items;
receiving, with the one or more hardware processors, feedback associated with individual ones of the one or more digital media items, wherein the feedback is based on one or both of (1) selection of one or more positive examples of the concept to be learned from the one or more digital media items, or (2) selection of one or more negative examples of the concept to be learned from the one or more digital media items, a given positive example being a digital media item comprising the concept to be learned, and a given negative example being a digital media item lacking the concept to be learned;
obtaining, with the one or more hardware processors, individual neural network representations for the individual ones of the one or more digital media items, a given neural network representation including one or more neural network layers; and
determining, with the one or more hardware processors, a trained concept based on (1) the feedback and (2) the neural network representations of the one or more digital media items, the trained concept being usable for retrieving digital media items relevant to the concept to be learned.
9 . The method of claim 8 , wherein determining the trained concept includes determining additional neural network layers based on (1) the feedback and (2) the neural network representations of the one or more digital media items.
10 . The method of claim 8 , wherein receiving feedback for individual ones of the digital media items includes obtaining confirmation of information associated with the individual ones of the digital media items.
11 . The method of claim 8 , wherein receiving feedback for individual ones of the digital media items includes obtaining confirmation of previous predictions related to the concept to be learned.
12 . The method of claim 8 , further comprising:
receiving, with the one or more hardware processors, queries for digital media items related to the concept being learned; and
using, with the one or more hardware processors, the trained concept to obtain results of the queries.
13 . The method of claim 8 , further comprising:
receiving, with the one or more hardware processors, additional feedback associated with the results of the queries, wherein the feedback is based on one or both of (1) selection of one or more positive examples of the concept being learned from results of the queries, or (2) selection of one or more negative examples of the concept being learned from the results of the queries.
14 . The method of claim 8 , further comprising:
adjusting, with the one or more hardware processors, the trained concept based on the additional feedback and neural network representations of the results of the queries.