Data searching system and method

A method for use in searching data sources for specific criteria and automatically updating machine learning training sets and classifier, the method comprising:

• storing a machine learning algorithm and machine learning training sets, wherein the machine learning algorithm is configured to reference the machine learning training sets;
• a processor effectuating a recognition agent over one or more data sources;
• a processor effectuating an extractor that collects feature data from the one or more data sources using one or more predetermined classifiers stored in a classifier dictionary of predetermined classifiers, wherein the predetermined classifiers comprise one or more hashtags;
• an input device receiving specific criteria;
• a processor effectuating an updater that dynamically updates the machine learning training sets and the classifier dictionary based on the collected feature data from the one or more data sources and the specific criteria, enabling the machine learning algorithm to identify at least one feature data including the specific criteria from the collected feature data;
• and
• an output device transmitting the at least one feature data including the identified specific criteria;
• wherein the machine learning algorithm, the machine learning training sets, and the classifier dictionary, are continuously updated, using the updater, based on a plurality of received specific criteria and corresponding feature data collected from the extractor to improve performance of the machine learning algorithm over time, and
• wherein the machine learning algorithm is a deep learning algorithm.