Granted Patent B1

US 8,055,595 · App. 12/842,495 · Granted Nov 8, 2011

Abstract

Claims (43)

1. A computerized method comprising:

a) receiving a learning event;

b) sending said learning event to a model management component, wherein said model management component is configured to determine a machine learning model associated with said learning event;

c) using said machine learning model, accessing a synchronization policy associated with said model;

d) sending said learning event to a prototypical machine learning model determined from said synchronization policy;

e) updating said prototypical machine learning model according to said learning event to produce an updated prototypical machine learning model; and

f) propagating said updated prototypical machine learning model to a plurality of machine learning models comprising said machine learning model and at least one other machine learning model hosted remotely from said updated prototypical machine learning model and said machine learning model.

2. The method, as claimed in claim 1 , wherein said propagating step occurs in real-time.

3. A machine learning system comprising:

a computer comprising:

a) an application interface component configured to be accessible to application programs and to communicate a request received from an application program to a model management component;

b) the model management component, wherein the model management component comprises:

i) a model pool;

ii) a model pool manager; and

iii) a synchronization manager;

wherein a model is stored within said model pool and wherein a synchronization policy is associated with said model;

wherein said model pool manager is configured to create, retrieve, update and/or delete said model within the model pool based on said request received through said application interface component;

wherein said synchronization manager executes said synchronization policy associated with said model;

wherein said synchronization manager is configured to update a prototypical model only if said request contains an appropriate learning event;

wherein said appropriate learning event comprises that said model, associated with said request, and said prototypical model comprise an identical vendor, an identical algorithm structure, and a set of identical model parameter attribute types.

4. A method of utilizing a computerized machine learning solution, comprising a machine learning model, in a transaction processing system, the method comprising:

a) providing a classification method, in said transaction processing system, wherein said classification method is configured to send a message to a machine learning controller in response to a predefined event;

b) based on the message, requesting a model manager and an algorithm manager from said machine learning controller for an instance of an associated algorithm and an instance of an associated model; and

c) responding to the predefined event based on processing said instance of said associated algorithm, said instance of said associated model and an output from said classification method.

5. The method of claim 4 , wherein the method further comprises:

a) coding a learn method to be called when a second predefined event takes place;

b) passing a second predefined event message, regarding said second predefined event, to said machine learning controller as a learning event;

c) passing said learning event to an update method exposed by a synchronization policy interface of said instance of said associated model via said model manager;

d) sending said learning event to a prototypical model; and

e) creating an updated version of said prototypical model.

6. The method of claim 5 , wherein the method further comprises propagating said updated prototypical model to a plurality of distributed servers according to a propagation method exposed by said synchronization policy interface.

7. The method of claim 4 , wherein:

a) the predefined event comprises a customer visiting a web site; and

b) responding to the predefined event comprises determining a recommendation from a set of available products.

8. The method of claim 7 , wherein the second predefined event comprises a purchase taking place.

9. The method of claim 4 , wherein:

a) the predefined event comprises receiving a natural language input from a user; and

b) responding to the predefined event comprises performing at least one action taken from the set of actions consisting of:

i) classifying the natural language input; and

ii) determining a response by a computer in an automated dialog.

10. The method of claim 4 , wherein

a) the predefined even comprises receiving a call from a user; and

b) responding to the predefined event comprises making a routing determination for the call.

Assignments (9)