Artificial intelligence-based system and method for dynamically predicting and suggesting emojis for messages

A system for dynamically predicting and suggesting digital pictorial images on a quick access pictorial image interface, the system comprising:

• an electronic device comprising an input device, at least one processor, a memory unit operably and communicatively coupled to the processor, and a display unit;
• a sensing unit comprising one or more of a plurality of sensors and operably coupled to the processor of the electronic device;
• and
• an A.I. engine operably coupled to the sensing unit, the processor, and a messaging application deployed on the electronic device, wherein the A.I. engine is configured to:
• identify a plurality of elements of an input message of a user on the messaging application;
• determine a context of the input message for each of the identified plurality of elements of the input message;
• analyze a plurality of factors associated with the input message for each of the identified plurality elements;
• and
• dynamically generate a prediction of an emoji based on the determined context and the analyzed plurality of factors associated with the input message, and wherein said factors include a location of the input message, an intent of the input message, and positions of any emojis present in the input message;
• and
• wherein the A.I. engine is configured to:
• positionally collapse or filter the emojis present in the input message to facilitate subsequent context extraction associated with each of said emojis:
• maintain a positional grouping of said emojis and store indices representative of said positional grouping in an array, and map the context of the input message to each of said emojis present in the input message and map text of the input message to each of said emojis present within said positional grouping;
• learn and predict different emojis applicable for the input message or the text of the input message, based on an understanding that same text is mapped to said different emojis, indicative of use of said different emojis to express same emotion;
• cluster sentences within a similarity of a pre-configured threshold and above, and map said cluster to most frequently used emojis present in said cluster, and represent said most frequently used emojis as an emoji vector:
• map the context of clustered sentences to said emoji vector;
• said A.I. engine further configured to map said context of said clustered statements to each of the emojis present in said emoji cluster as different labels, thereby enabling multi-label classification wherein each statement is mapped to a single emoji or multiple emojis.