METHODS AND SYSTEMS FOR USING MACHINE-LEARNING EXTRACTS AND SEMANTIC GRAPHS TO CREATE STRUCTURED DATA TO DRIVE SEARCH, RECOMMENDATION, AND DISCOVERY
Methods and systems for using a combination of semantic graphs and machine learning to automatically generate structured data, recognize important entities/keywords, and create weighted connections for more relevant search results and recommendations. For example, by inferring relevant entities, metadata results are richer and more meaningful, enabling faster decision-making for the consumer and stronger viewership for the content owner.
1 . A method of providing search, recommendation and discovery features, the method comprising:
gathering, by control circuitry, a data set;
performing, by the control circuitry, pronoun resolution across the data set;
performing, by the control circuitry, candidate identification across the data set;
creating, by the control circuitry, a semantic graph that identifies a plurality of key entities and a plurality of associations between the plurality of key entities;
receiving, by a user input interface, a user input;
processing the user input, by the control circuitry, using the semantic graph; and
generating, by the control circuitry, an output based on the processed user input.
2 . The method of claim 1 , wherein the semantic graph comprises a plurality of nodes, wherein each of the plurality of nodes corresponds to an entity from a dataset of entities.
3 . The method of claim 1 , wherein the data set is divided into a ratio of training data to validation data, wherein the training data is used to train the control circuitry on the semantic graph.
4 . The method of claim 1 , wherein performing the pronoun resolution comprises resolving the pronoun using coreference resolution.
5 . The method of claim 1 , wherein the candidate identification comprises grammatical tagging and word-category disambiguation.
6 . The method of claim 1 , wherein the user input is received directly from a user or from an electronic device.
7 . The method of claim 1 , wherein processing the user input comprises matching a plurality of candidates from the user input with a plurality of nodes in the semantic graph.
8 . The method of claim 1 , wherein a plurality of relationships between a plurality of candidates from the user input is identified by traversing a dependency tree.
9 . The method of claim 1 , wherein the output comprises a search result or a recommendation based on the user input.
10 . The method of claim 1 , wherein the semantic graph is a knowledge base that represents semantic relations between concepts in a network.
11 . A system of providing search, recommendation and discovery features, the system comprising:
memory; and
control circuitry configured to:
gather a data set;
perform pronoun resolution across the data set;
perform candidate identification across the data set;
create a semantic graph that identifies a plurality of key entities and a plurality of associations between the plurality of key entities;
receive a user input;
process the user input using the semantic graph; and
generate an output based on the processed user input.
12 . The system of claim 11 , wherein the semantic graph comprises a plurality of nodes, wherein each of the plurality of nodes corresponds to an entity from a dataset of entities.
13 . The system of claim 11 , wherein the data set is divided into a ratio of training data to validation data, wherein the training data is used to train the control circuitry on the semantic graph.
14 . The system of claim 11 , wherein performing the pronoun resolution comprises resolving the pronoun using coreference resolution.
15 . The system of claim 11 , wherein the candidate identification comprises grammatical tagging and word-category disambiguation.
16 . The system of claim 11 , wherein the user input is received directly from a user or from an electronic device.
17 . The system of claim 11 , wherein processing the user input comprises matching a plurality of candidates from the user input with a plurality of nodes in the semantic graph.
18 . The system of claim 11 , wherein a plurality of relationships between a plurality of candidates from the user input is identified by traversing a dependency tree.
19 . The system of claim 11 , wherein the output comprises a search result or a recommendation based on the user input.
20 . The system of claim 11 , wherein the semantic graph is a knowledge base that represents semantic relations between concepts in a network.
21 - 50 . (canceled)