Systems and methods for content navigation with automated curation
First Claim
1. A method comprising:
- communicating, by a server system, at least a portion of a first content collection to a first client device, wherein the first content collection comprises a first plurality of pieces of content;
receiving, at the server system from the first client device, a first selection communication, the first selection communication identifying a first piece of content of the first plurality of pieces of content;
analyzing the first piece of content to identify a set of context values and one or more quality values for the first piece of content;
accessing a second content collection comprising pieces of content sharing at least a portion of the set of context values of the first piece of content, wherein the second content collection is selected in response to the first selection communication based on the portion of the set of context values of the first piece of content;
communicating at least a portion of the second content collection to the first client device; and
deleting a content message from a database based on a deletion trigger associated with the content message;
wherein the one or more quality values comprises an interestingness value based on predicting an expected user interest in the content message, where the interestingness value is generated using a neural network generated using a training set of content messages identified as interesting within the server system;
wherein the interestingness value is further generated based on rating inputs received at a curation tool integrated with the server system to provide operator selected training sets for the neural network; and
wherein the content message as received at the server system is associated with the deletion trigger.
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Accused Products
Abstract
Systems, devices, methods, media, and instructions for automated image processing and content curation are described. In one embodiment a server computer system communicates at least a portion of a first content collection to a first client device, and receives a first selection communication in response, the first selection communication identifying a first piece of content of the first plurality of pieces of content. The server analyzes analyzing the first piece of content to identify a set of context values for the first piece of content, and accesses accessing a second content collection comprising pieces of content sharing at least a portion of the set of context values of the first piece of content. In various embodiments, different content values, image processing operations, and content selection operations are used to curate the content collections.
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Citations
20 Claims
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1. A method comprising:
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communicating, by a server system, at least a portion of a first content collection to a first client device, wherein the first content collection comprises a first plurality of pieces of content; receiving, at the server system from the first client device, a first selection communication, the first selection communication identifying a first piece of content of the first plurality of pieces of content; analyzing the first piece of content to identify a set of context values and one or more quality values for the first piece of content; accessing a second content collection comprising pieces of content sharing at least a portion of the set of context values of the first piece of content, wherein the second content collection is selected in response to the first selection communication based on the portion of the set of context values of the first piece of content; communicating at least a portion of the second content collection to the first client device; and deleting a content message from a database based on a deletion trigger associated with the content message; wherein the one or more quality values comprises an interestingness value based on predicting an expected user interest in the content message, where the interestingness value is generated using a neural network generated using a training set of content messages identified as interesting within the server system; wherein the interestingness value is further generated based on rating inputs received at a curation tool integrated with the server system to provide operator selected training sets for the neural network; and wherein the content message as received at the server system is associated with the deletion trigger. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A server computer system comprising:
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a memory; and one or more processors coupled to the memory and configured to; communicate at least a portion of a first content collection to a first client device, wherein the first content collection comprises a first plurality of pieces of content; receive from the first client device, a first selection communication, the first selection communication identifying a first piece of content of the first plurality of pieces of content; analyze the first piece of content to identify a set of context values and one or more quality values for the first piece of content; access a second content collection comprising pieces of content sharing at least a portion of the set of context values of the first piece of content, wherein the second content collection is selected in response to the first selection communication based on the portion of the set of context values of the first piece of content; communicate at least a portion of the second content collection to the first client device; and delete a content message from a database based on a deletion trigger associated with the content message; wherein the one or more quality values comprises an interestingness value based on predicting an expected user interest in the content message, where the interestingness value is generated using a neural network generated using a training set of content messages identified as interesting within the server computer system; wherein the interestingness value is further generated based on rating inputs received at a curation tool integrated with the server computer system to provide operator selected training sets for the neural network; and wherein the content message as received at the server computer system is associated with the deletion trigger. - View Dependent Claims (11, 12, 13, 14)
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15. A non-transitory computer readable medium comprising instructions that, when executed by one or more processors, cause a server computer system to perform a method comprising:
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communicating at least a portion of a first content collection to a first client device, wherein the first content collection comprises a first plurality of pieces of content; receiving from the first client device, a first selection communication, the first selection communication identifying a first piece of content of the first plurality of pieces of content; analyzing the first piece of content to identify a set of context values and one or more quality values for the first piece of content; accessing a second content collection comprising pieces of content sharing at least a portion of the set of context values of the first piece of content, wherein the second content collection is selected in response to the first selection communication based on the portion of the set of context values of the first piece of content; communicating at least a portion of the second content collection to the first client device; and deleting a content message from a database based on a deletion trigger associated with the content message; wherein the one or more quality values comprises an interestingness value based on predicting an expected user interest in the content message, where the interestingness value is generated using a neural network generated using a training set of content messages identified as interesting within the server computer system; wherein the interestingness value is further generated based on rating inputs received at a curation tool integrated with the server computer system to provide operator selected training sets for the neural network; and wherein the content message as received at the server computer system is associated with the deletion trigger. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification