Influence function in machine learning for interpretation of lengthy and noisy documents

A system comprising:

• a processor;
• a memory device coupled with the processor;
• the processor configured to at least:
• receive historical earnings call data;
• receive historical market data;
• train a neural network to predict a future indicator of a given entity based on the historical earnings call data and the historical market data;
• receive an earnings call transcript, from which to predict the future indicator;
• preprocess the earnings call transcript using a natural language processing (NLP) technique to select candidate sentences from the earnings call transcript;
• for a candidate sentence in the candidate sentences and using the trained neural network, determine a sentence gradient indicative of sensitivity of the trained neural network to the candidate sentence;
• and
• based on the determined sentence gradient associated with each of the candidate sentences, provide an explanation of the trained neural network's predicted future indicator.

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions readable by a device to cause the device to:

• receive historical earnings call data;
• receive historical market data;
• train a neural network to predict a future indicator of a given entity based on the historical earnings call data and the historical market data;
• receive an earnings call transcript, from which to predict the future indicator;
• preprocess the earnings call transcript using a natural language processing (NLP) technique to select candidate sentences from the earnings call transcript;
• for a candidate sentence in the candidate sentences and using the trained neural network,
• determine a sentence gradient indicative of sensitivity of the trained neural network to the candidate sentence;
• and
• based on the determined sentence gradient associated with each of the candidate sentences, provide an explanation of the trained neural network's predicted future indicator.