Method of automated discovery of new topics

A system comprising:

• a database source computer module configured to extract data associated with a plurality of co-occurring topics in a document corpus;
• and
• a synchronizing framework computer module configured to:
• extract a plurality of topic identifies from the plurality of co-occurring topics;
• create a master topic computer model for the document corpus from a first plurality of term vectors;
• create a periodic new topic computer model by comparing topic significance among the plurality of topic identifiers, the periodic new topic computer model including a second plurality of term vectors;
• and
• select one or more new topics by identifying one or more term vectors from the second plurality of term vectors in the periodic new topic computer model that have no correlation with the first plurality of term vectors in the master topic computer model.

A non-transitory computer readable medium having stored thereon computer executable instructions executed by a processor comprising:

• automatically extracting, by a processor executing a database source computer module, from a document corpus data associated with a plurality of co-occurring topics;
• in response to automatically extracting the plurality of co-occurring topics, extracting, by the processor executing a synchronizing framework computer module, a plurality of topic identifiers from the plurality of co-occurring topics;
• creating, by the processor executing the synchronizing framework computer, a master topic computer model for the document corpus from a first plurality of term vectors;
• creating, by the processor executing the synchronizing framework computer, a periodic new topic computer model by comparing topic significance among the plurality of topic identifiers, the periodic new topic computer model including a second plurality of term vectors;
• and
• selecting, by the processor executing the synchronizing framework computer, one or more new topics by identifying one or more term vectors from the second plurality of term vectors in the periodic new topic computer model that have no correlation with the first plurality of term vectors in the master topic computer model.