Patent Document ID: 9483462
Application ID: 14820995

Base Claim:
1. A nontransitory, computer readable storage medium having computer readable instruction stored thereon that, when executed by a computer, implement method for automatically generating training data for disambiguation of an entity in electronic messages, the entity comprising a word or word string related to a topic to be analyzed, the method comprising: communicating, by a processor, with a message server via an application programming interface of the message server; acquiring, in real-time, by the processor, from the message server, a plurality of electronic messages each including at least one entity from a set of entities related to the topic to be analyzed; identifying, by the processor, a user that sent each of the electronic messages based on metadata of the respective electronic messages and associating the electronic messages with respective sets from a plurality of sets of messages, each of the sets containing electronic messages sent by a respective user; identifying, by the processor, from the sets of messages, a set of messages that includes a number of entities greater than or equal to a first threshold value, the first threshold value being a positive integer greater than one in number, and identifying the user corresponding to the identifies set of messages as a hot user; receiving, by the processor, an instruction indicating an object entity to be disambiguated, the object entity being an entity from the set of entities, and disambiguating the object entity comprises identifying a use of the object entity in association with the topic to be analyzed; determining, by the processor, likelihood of co-occurrence of a keyword and the object entity in a single electronic message from the set of messages sent by the hot user, the keyword being one of a plurality of terms included in the electronic messages that is sent by the hot user and the includes the object entity; and generating, by the processor, training data for the object entity on the basis of the likelihood of co-occurrence of the keyword and the object entity in a single electronic message sent by the hot user, wherein the training data identifies that co-occurrence of the keyword and the object entity in a single electronic message is indicative of a use of the object entity in relation to the topic to be analyzed.

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Claim 13:
13. The storage medium of claim 1 , wherein the method further comprises training a Bayesian classifier using the training data to filter the electronic messages that are related to the topic to be analyzed.