Social network message categorization systems and methods
AssigneeCitizenNet Inc.
InventorsMichael Aaron Hall, Daniel Benyamin, Aaron Chu
Life of this patent
Estimating the term…
Abstract
Systems and methods of identifying and categorizing social network messages that are relevant to selected categories and text terms are provided. The frequency of text terms appearing in social network messages are calculated for multiple categories. Based on the calculated text term frequency, social network messages can be identified and/or categorized that match a provided set of text terms. Selecting and/or associating text terms and categories are determined by repeatedly analyzing social network messages.
Claims20
A method of textual categorization of social network messages, the method comprising:
- scoring one or more messages from one or more social network messaging services based on one or more text terms for a determined category by a message server, where a category comprises a set of keywords and a set of associated normalized keyword frequency calculations associated with the set of keywords;
- matching the one or more scored messages to one or more text terms from a query;
- and
- returning one or more messages having a final score that equals or exceeds a threshold value for the determined category, the final score being based on scores of the scored messages and match values of the matched messages.
A message categorizer, comprising:
- memory configured to store a textual categorization application and one or more messages;
- and
- a processor;
- wherein the textual categorization application configures the processor to:
- score one or more messages from one or more social network messaging services based on one or more text terms for a determined category, where a category comprises a set of keywords and a set of associated normalized keyword frequency calculations associated with the set of keywords;
- match the one or more scored messages to one or more text terms from a query;
- and
- return one or more messages having a final score that equals or exceeds a threshold value for the determined category, the final score being based on scores of the scored messages and match values of the matched messages.
Dependencies are inferred from the claim text.