Techniques are disclosed for detecting changes in a neuro-linguistic model. According to one embodiment, detecting changes in a neuro-linguistic model comprises receiving a first neuro-linguistic model, wherein the first neuro-linguistic model provides a set of statistical descriptions generated from a first set of input data received from one or more sensor devices during a first time period receiving a second neuro-linguistic model having a second set of statistical descriptions for second input data, wherein the second neuro-linguistic model provides a set of statistical descriptions of the second input data transmitted from the one or more sensor devices during a second time period, comparing the second set of statistical descriptions to the first set statistical descriptions to determine a set of matching statistical descriptions and generating a similarity score based on the matching statistical descriptions, and upon determining a trend change based on a comparison between the similarity score and a threshold, outputting an alert indication of trend change.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer implemented method for detecting changes in a neuro-linguistic model, comprising: receiving a first neuro-linguistic model, wherein the first neuro-linguistic model provides a set of statistical descriptions generated from a first set of input data received from one or more sensor devices during a first time period; receiving a second neuro-linguistic model having a second set of statistical descriptions for second input data, wherein the second neuro-linguistic model provides a set of statistical descriptions of the second input data transmitted from the one or more sensor devices during a second time period; comparing the second set of statistical descriptions to the first set statistical descriptions to determine a set of matching statistical descriptions; and generating a similarity score based on the matching statistical descriptions; and upon determining a trend change based on a comparison between the similarity score and a threshold, outputting an alert indication of trend change. 2. The method of claim 1, wherein the first time period precedes the second time period. 3. The method of claim 1, wherein the first and second neuro-linguistic models are generated either periodically based on a time interval or based on a number of operations. 4. The method of claim 1, wherein the neuro-linguistic models are statistically described probabilistic distributions. 5. The method of claim 1, wherein the similarity score is based on a comparison of mean values from the set of matching statistical descriptions and the variance of a statistical description of the first set of statistical descriptions within the set of matching statistical descriptions. 6. The method of claim 1, further comprising: merging the first neuro-linguistic model with a third neuro-linguistic model, the third neuro-linguistic model having a third set of statistical descriptions for third input data, wherein the second neuro-linguistic model provides a set of statistical descriptions of the third input data transmitted from the one or more sensor devices during a third time period, the third time period preceding the first and second time periods. 7. The method of claim 1, further comprising: updating the second neuro-linguistic model by merging the second neuro-linguistic model with the first neuro-linguistic model. 8. A computer-readable storage medium storing instructions, which, when executed on a processor, perform an operation for detecting changes in a neuro-linguistic model comprising: receiving a first neuro-linguistic model, wherein the first neuro-linguistic model provides a set of statistical descriptions generated from a first set of input data received from one or more sensor devices during a first time period; receiving a second neuro-linguistic model having a second set of statistical descriptions for second input data, wherein the second neuro-linguistic model provides a set of statistical descriptions of the second input data transmitted from the one or more sensor devices during a second time period; comparing the second set of statistical descriptions to the first set statistical descriptions to determine a set of matching statistical descriptions; and generating a similarity score based on the matching statistical descriptions; and upon determining a trend change based on a comparison between the similarity score and a threshold, outputting an alert indication of trend change. 9. The computer-readable storage medium of claim 8, wherein the first time period precedes the second time period. 10. The computer-readable storage medium of claim 8, wherein the first and second neuro-linguistic models are generated either periodically based on a time interval or based on a number of operations. 11. The computer-readable storage medium of claim 8, wherein the neuro-linguistic models are statistically described probabilistic distributions. 12. The computer-readable storage medium of claim 8, wherein the similarity score is based on a comparison of mean values from the set of matching statistical descriptions and the variance of a statistical description of the first set of statistical descriptions within the set of matching statistical descriptions. 13. The computer-readable storage medium of claim 8, further comprising: merging the first neuro-linguistic model with a third neuro-linguistic model, the third neuro-linguistic model having a third set of statistical descriptions for third input data, wherein the second neuro-linguistic model provides a set of statistical descriptions of the third input data transmitted from the one or more sensor devices during a third time period, the third time period preceding the first and second time periods. 14. The computer-readable storage medium of claim 8, further comprising: updating the second neuro-linguistic model by merging the second neuro-linguistic model with the first neuro-linguistic model. 15. A system, comprising: a processor; and memory storing code, which, when executed on a processor, perform an operation for detecting changes in a neuro-linguistic model comprising: receiving a first neuro-linguistic model, wherein the first neuro-linguistic model provides a set of statistical descriptions generated from a first set of input data received from one or more sensor devices during a first time period; receiving a second neuro-linguistic model having a second set of statistical descriptions for second input data, wherein the second neuro-linguistic model provides a set of statistical descriptions of the second input data transmitted from the one or more sensor devices during a second time period; comparing the second set of statistical descriptions to the first set statistical descriptions to determine a set of matching statistical descriptions; and generating a similarity score based on the matching statistical descriptions; and upon determining a trend change based on a comparison between the similarity score and a threshold, outputting an alert indication of trend change. 16. The system of claim 15, wherein the first time period precedes the second time period. 17. The system of claim 15, wherein the first and second neuro-linguistic models are generated either periodically based on a time interval or based on a number of operations. 18. The system of claim 15, wherein the neuro-linguistic models are statistically described probabilistic distributions. 19. The system of claim 15, wherein the similarity score is based on a comparison of mean values from the set of matching statistical descriptions and the variance of a statistical description of the first set of statistical descriptions within the set of matching statistical descriptions. 20. The system of claim 15, further comprising: merging the first neuro-linguistic model with a third neuro-linguistic model, the third neuro-linguistic model having a third set of statistical descriptions for third input data, wherein the second neuro-linguistic model provides a set of statistical descriptions of the third input data transmitted from the one or more sensor devices during a third time period, the third time period preceding the first and second time periods.