Leveraging natural language processing
A system, computer program product, and method are provided to automate a natural language processing system to facilitate an artificial intelligence platform defining a relationship between dialogue and post dialogue activity. Dialogue is detected and analyzed, including identification of key words and phrases within the dialogue. Post dialogue actions, including physical actuation of a hardware device and an associated temporal proximity of the action and the dialogue, are monitored. The hardware device receives an instruction from a processing unit that relates to the analyzed dialogue and the hardware device changes states and/or actuates another hardware device. The system constructs a hypothesis, i.e., a relationship from the identified key phrase drawn from the analyzed dialogue and the monitored post action dialogue. A dialogue tree containing identified terms and associated post dialogue actions is dynamically modified with one or more new identified terms and the associated post dialogue actions.
1. A computer system comprising:
a processing unit operatively coupled to memory;
an artificial intelligence (AI) platform, in communication with the processing unit and memory, the AI platform comprising:
a natural language processing (NLP) dialogue monitor to detect dialogue data and analyze the detected dialogue data, including identification of a term within the detected dialogue data;
a dialogue engine operatively coupled to the NLP dialogue monitor, the dialogue engine to monitor a post dialogue action, including physical actuation of a hardware device and proximity of the actuation to the detected dialogue data;
an analysis engine operatively coupled to the dialogue engine and the NLP dialogue monitor, the analysis engine to construct a relationship from an identified key phrase drawn from the analyzed dialogue data and the monitored post dialogue action;
the analysis engine to evaluate a re-occurrence of the identified term in a first dialogue and a second dialogue, and to apply a weight to the identified term, wherein the weight reflects prominence of the identified term; and
a search engine, operatively coupled to the analysis engine, to dynamically modify a dialogue tree responsive to the applied weight, including addition of a new entry into the dialogue tree, the new entry including the identified term and the post dialogue action; and
the hardware device operatively coupled to the dialogue engine, the hardware device to receive an instruction related to the analyzed dialogue data, wherein receipt of the instruction causes a physical action comprising the hardware device to change states, actuation of a second hardware device, or combinations thereof.
2. The system of claim 1 , further comprising the dialogue engine to detect non-verbal data and apply the detected non-verbal data to the identified term and post dialogue action.
3. The system of claim 2 , further comprising the NLP dialogue monitor to evaluate proximity of occurrence of the identified term to the detected non-verbal data.
4. The system of claim 2 , further comprising the dialogue engine to detect a response to the post dialogue action, and to classify the detected response with the new entry in the dialogue tree.
5. The system of claim 1 , wherein the dynamic modification of the dialogue tree is a confirmation of an association between the identified term and the post dialogue action.
6. A computer program product to process natural language (NL), the computer program product comprising a computer readable storage device having program code embodied therewith, the program code executable by a processing unit to:
leverage a natural language processing (NLP) dialogue monitor to detect dialogue data and analyze the detected dialogue data, including identification of a term within the detected dialogue data;
monitor a post dialogue action, including physical actuation of a hardware device and proximity of the actuation to the detected dialogue data;
construct a hypothesis from an identified key phrase drawn from the analyzed dialogue data and the monitored post dialogue action;
evaluate a re-occurrence of the identified term in a first dialogue and a second dialogue, and apply a weight to the identified term, wherein the weight reflects prominence of the identified term;
dynamically modify a dialogue tree responsive to the applied weight, including addition of a new entry into the dialogue tree, the new entry including the identified term and the post dialogue action; and
the hardware device operatively coupled to the processing unit, the hardware device to receive an instruction related to the analyzed dialogue data, wherein receipt of the instruction causes a physical action comprising the hardware device to change states, actuation of a second hardware device, or combinations thereof.
7. The computer program product of claim 6 , further comprising program code to detect non-verbal data and apply the detected non-verbal data to the identified term and post dialogue action.
8. The computer program product of claim 7 , further comprising program code to evaluate proximity of occurrence of the identified term to the detected non-verbal data.
9. The computer program product of claim 7 , further comprising program code to detect a response to the post dialogue action, and to classify the detected response with the new entry in the dialogue tree.
10. The computer program product of claim 6 , wherein the dynamic modification of the dialogue tree is a confirmation of an association between the identified term and the post dialogue action.
11. A method for processing natural language (NL), comprising:
detecting dialogue data and analyzing the detected dialogue data, including identification of a term within the detected dialogue data;
monitoring a post dialogue action, including physical actuation of a hardware device and proximity of the actuation to the detected dialogue data;
constructing a hypothesis from an identified key phrase drawn from the analyzed dialogue and the monitored post dialogue action;
evaluating a re-occurrence of the identified term in a first dialogue and a second dialogue, and applying a weight to the identified term, wherein the weight reflects prominence of the identified term;
dynamically modifying a dialogue tree responsive to the applied weight, including addition of a new entry into the dialogue tree, the new entry including the identified term and the post dialogue action; and
a hardware device operatively coupled to the processing unit, the hardware device to receiving an instruction related to the analyzed dialogue data, wherein receipt of the instruction causing a physical action comprising the hardware device to change states, actuation of a second hardware device, or combinations thereof.
12. The method of claim 11 , further comprising detecting non-verbal data and applying the detected non-verbal data to the identified term and post dialogue action.
13. The method of claim 12 , further comprising evaluating proximity of occurrence of the identified term to the detected non-verbal data.
14. The method of claim 12 , further comprising detecting a response to the post dialogue action, and classifying the detected response with the new entry in the dialogue tree.
15. The method of claim 11 , wherein the dynamic modification of the dialogue tree is a confirmation of an association between the identified term and the post dialogue action.