Method and system for analyzing entities. Jonathan William Mugan, Laura HITT, Jimmie Goode, Russ Gregory, & Yuan Qu .
Method and system for analyzing entities [link]Paper  abstract   bibtex   
A recurrent neural network (RNN) method implemented on a computer system is used to produce summaries of unstructured text generated by multiple networks of individuals interacting over time by encoding the unstructured text into intermediate representations and decoding the intermediate representations into summaries of each network. Parameter data for the RNN is obtained by using multiple different versions of the same source texts to train the computer system. The method and computer system can be used to identify which of the networks match a query by determining which network generates the query with low or lowest cost.
@patent{jonathan_william_mugan_method_nodate,
	title = {Method and system for analyzing entities},
	url = {https://patents.google.com/patent/US10445356B1/en},
	abstract = {A recurrent neural network (RNN) method implemented on a computer system is used to produce summaries of unstructured text generated by multiple networks of individuals interacting over time by encoding the unstructured text into intermediate representations and decoding the intermediate representations into summaries of each network. Parameter data for the RNN is obtained by using multiple different versions of the same source texts to train the computer system. The method and computer system can be used to identify which of the networks match a query by determining which network generates the query with low or lowest cost.},
	nationality = {United States of America},
	assignee = {Pulselight Holdings Inc},
	number = {US10445356B1},
	author = {{Jonathan William Mugan} and {Laura HITT} and {Jimmie Goode} and {Russ Gregory} and {Yuan Qu}},
	keywords = {Artificial inteligence, Machine Learning, Neural networks, mentions sympy},
	pages = {22}
}

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