Content creation and prioritization

A computerized system for automatically determining answers to a plurality of questions, the computerized system comprising:

• a question discovery engine for automatically discovering a plurality of questions by processing historical data related to prior customer interactions, the question discovery engine comprises:
• a question detection module configured to apply a linguistic analytical model on the data related to historical customer interactions to detect the plurality of questions;
• a question vectorization module configured to vectorize the plurality of questions to generate mathematical representations of the questions, wherein each mathematical representation preserves syntactic and sematic meaning of the corresponding question;
• and
• a question clustering module configured to group the plurality of questions into one or more clusters based on similarities of the questions as measured based on their mathematical representations, wherein each cluster is assigned a representative question;
• and
• an answer mining engine for automatically determining at least one probable answer to each of the representative questions using a content mining technique, the answer mining engine comprises:
• a data scraping module configured to mine pertinent data from one or more content sources;
• an index creation module configured to index the mined data based on key phrases extracted from the mined data;
• an index query module configured to query the indexed data using the representative question from each of the one or more clusters to determine one or more sections of the indexed data that match the representative question to within a predetermined degree of tolerance;
• and
• an extraction module configured to formulate the at least one probable answer for the representative question of each cluster by applying a supervised learning algorithm that predicts a degree of match between each of the one or more matched sections and the corresponding representative question.