Rule-driven guidance and feedback system

• US 20020070956A1
• Filed: 11/27/2001
• Published: 06/13/2002
• Est. Priority Date: 11/30/2000
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Khuwaja, Ramzan A., Wang, Jin, Chan, Yumman, Tsang, Kwong
• Application Number:
  US09/995,239
• Publication Number:
  US 20020070956A1
• Time in Patent Office: Days
• US Class Current: 715/714
• CPC Class Codes: G06N 5/00 Computing arrangements using knowledge-based models
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A reasoning model for a guidance and feedback system includes a decision graph built by an author to reflect a defined knowledge base. The decision graph includes nodes having rules to define links or transitions to other nodes in the graph. Nodes may be question nodes, recommendation nodes, or cross-sell nodes. Question nodes determine system user characteristics by direct interrogation or by indirect access to information about the user. Recommendation nodes are associated with question nodes and may be either final or interim. Cross-sell nodes provide information to a user that is not directly related to the defined knowledge base. A rule engine traverses the graph and fires the rules defined in the nodes. Links to nodes are followed in a manner determined dynamically as a result of the user data obtained at question nodes.

Claims

1. A computer system reasoning model component for generating user recommendations for a defined knowledge base, the component comprising;

a component for storing, maintaining and representing a decision graph definable by an author, the decision graph comprising nodes and links between the nodes, the nodes comprising;

a set of decision nodes, and a set of feedback nodes, each of the nodes in the decision graph comprising rules defined by the author

to define links to other nodes in the graph, and

for a decision node, to request and obtain user information, and

for a feedback node, to provide feedback to users, and

a component to traverse the decision graph and fire the rules defined in the decision graph nodes.

2. The computer system component of claim 1 in which the decision nodes comprise question nodes and the feedback nodes comprise recommendation and promotion nodes.

3. The computer system component ofeclaim 2 in which promotional nodes comprise cross-sell and up-sell nodes.

6. The computer system component of claim 1 in which the decision graph comprises multiple entry points.

7. The computer system component of claim 1 in which the decision graph comprises nodes potentially chaining the decision graph to other decision systems.

8. The computer system of claim 1 in which the rules defining links between nodes in the decision graph utilize one or more of:

a) weighting systems,

b) fuzzy logic systems, and

c) probabilistic reasoning.

10. A computer program product for providing user recommendations, the computer program product comprising a computer usable medium having computer readable code means embodied in said medium, comprising computer readable program code means for implementing the system component of any of claims 1 to 10.

11. The computer program product of claim 10 wherein said computer readable code means comprises a computer readable signal and said medium comprises a computer readable signal-bearing medium.

12. The program product of claim 11 wherein said medium is a recordable data storage medium.

13. The product of claim 11 wherein said medium is a modulated carrier signal.

14. The product of claim 13 wherein said signal is a transmission over a network.

15. A computer program comprising computer program code means adapted to establish the components of claim 1 when said program is run on a computer system.

4. The computer system component of claim I in which the nodes contain no information relating to presentation of data to a user.

5. The computer system component of claim I in which the rules defining links to other nodes in the graph comprise rules accessing and evaluating one or more of:

a) personalization choices collected implicitly or explicitly from the user,

b) static data relating to the user,

c) a dynamically generated user model,

d) attributes of elements in the knowledge base, and

e) author-related goals.

9. A computer system reasoning model component for generating user recommendations for a defined knowledge base, the component comprising:

a component for storing, maintaining and representing a decision graph definable by an author, the decision graph comprising nodes and links between the nodes, the nodes comprising;

a set of decision nodes, and a set of feedback nodes, the decision nodes comprising;

question nodes and the feedback nodes comprising recommendation and promotion nodes, each of the nodes in the decision graph comprising rules defined by the

author to define links to other nodes in the graph, and

for a decision node, to request and obtain user information, and

for a feedback node, to provide feedback to users, the rules defining links to other nodes in the graph comprising rules accessing and lo;

i evaluating one or more of;

(f) personalization choices collected implicitly or explicitly from the user,

(g) static data relating to the user,

(h) a dynamically generated user model,

(i) attributes of elements in the knowledge base, and

(j) author-related goals; and

utilize one or more of;

(i) weighting systems,

(ii) fuzzy logic systems, and

(iii) probabilistic reasoning, and a component to traverse the decision graph and fire the rules defined in the graph nodes.