System and method of highlighting influential samples in sequential analysis

A computerized method for highlighting relative importance of portions of a conversation displayed on a graphical user interface, comprising:

• storing the conversation in text form in computerized memory connected to a computer processor that is configured to display conversation text on a graphical user interface, wherein a display of the conversation illustrates conversation data according to respective conversation participants' turns in providing conversation input;
• weighting respective turns of the conversation by providing the conversation input of the respective turns to a hierarchical attention network stored in the memory, wherein the hierarchical attention network uses the processor to calculate sequential long-short-term-memory cells (LSTM) in the memory;
• using later LSTM cell data to update weighting values for prior LSTM cell data in a sequence of turns of conversation input data;
• and
• displaying the conversation participants' turns on the graphical user interface with a visible indication of respective weighting values for each of the participants' turns.