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US 11,115,356 B2Granted
Emoji recommendation system and method
AssigneeWoofy, Inc.
InventorArjun Rai
Life of this patent
Estimating the term…
Abstract
A system includes a memory and at least one processor to receive text from a client computing device, the text received one character at a time, as each character of the text is received, determine a recommendation in real-time to be added to the text based on at least one of a list of rules, word embedding, an n-gram model, and a co-occurrence model, the recommendation comprising at least one of a word, a list of hashtags, a quotation, and a list of emojis, and send the recommendation to the client computing device.
Claims17
A system comprising:
- a memory;
- and
- at least one processor to:
- receive text from a client computing device, the text received one character at a time as part of a payload having a particular format by a web application programming interface (API) provided by a predictive linguistics engine, the payload having the text, a fanout level, and a depth value;
- as each character of the text is received, determine, by the predictive linguistics engine, a recommendation in real-time to be added to the text having a similarity score above a particular threshold based on at least one of a list of rules, word embedding, an n-gram model, and a co-occurrence model, the recommendation comprising at least one of a word, a list of hashtags, a quotation, and a list of emojis;
- determine that the text includes a uniform resource location (URL), parse content available at the URL, and determine the recommendation based on the content available at the URL, the recommendation comprising at least one of the quotation and the list of hashtags;
- and
- send, by the predictive linguistics engine, the recommendation to the client computing device.
5 more elements
A method comprising:
- receiving, by at least one processor, text from a client computing device, the text received one character at a time as part of a payload having a particular format by a web application programming interface (API) provided by a predictive linguistics engine, the payload having the text, a fanout level, and a depth value;
- as each character of the text is received, determining, by the predictive linguistics engine by the at least one processor, a recommendation in real-time to be added to the text having a similarity score above a particular threshold based on at least one of a list of rules, word embedding, an n-gram model, and a co-occurrence model, the recommendation comprising at least one of a word, a list of hashtags, a quotation, and a list of emojis;
- determining, by the at least one processor, that the text includes a uniform resource location (URL), parsing content available at the URL, and determining the recommendation based on the content available at the URL, the recommendation comprising at least one of the quotation and the list of hashtags;
- and
- sending, by the predictive linguistics engine by the at least one processor, the recommendation to the client computing device.
2 more elements
A non-transitory computer-readable storage medium, having instructions stored thereon that, when executed by a computing device cause the computing device to perform operations, the operations comprising:
- receiving text from a client computing device, the text received one character at a time as part of a payload having a particular format by a web application programming interface (API) provided by a predictive linguistics engine, the payload having the text, a fanout level, and a depth value;
- as each character of the text is received, determining, by the predictive linguistics engine, a recommendation in real-time to be added to the text having a similarity score above a particular threshold based on at least one of a list of rules, word embedding, an n-gram model, and a co-occurrence model, the recommendation comprising at least one of a word, a list of hashtags, a quotation, and a list of emojis;
- determining that the text includes a uniform resource location (URL), parsing content available at the URL, and determining the recommendation based on the content available at the URL, the recommendation comprising at least one of the quotation and the list of hashtags;
- and
- sending, by the predictive linguistics engine, the recommendation to the client computing device.
2 more elements
Dependencies are inferred from the claim text.