Case-based reasoning system and method with a search engine...

Details Case-based reasoning system and method with a search engine... Case-based reasoning system and method with a search engine...

1997-12-30

2003-05-27

Channavajjala, Srirama (Department: 2777)

Data processing: database and file management or data structures

Database design

Data structure types

C707S793000, C707S793000, C707S793000, C707S793000, C707S793000, C706S045000, C706S046000, C706S047000

Reexamination Certificate

active

06571251

ABSTRACT:

CROSS-REFERENCE TO RELATED APPLICATION
This application is related to application Ser. No. 09/001,083, which was filed on even date herewith and entitled “Case-Based Reasoning System And Method For Scoring Cases In A Case Database”.
BACKGROUND OF THE INVENTION
1. Technical Field
The present invention relates in general to expert systems and, in particular, to case-based reasoning systems. Still more particularly, the present invention relates to a case-based reasoning system that compresses selected data within a case database into a tokenized view in order to improve the efficiency of the case database search engine.
2. Description of the Related Art
A case-based reasoning (CBR) system generally refers to a computer system that identifies a solution to a current problem by examining descriptions of similar, previously encountered problems and their associated solutions, matching the current problem with one or more similar previously encountered problems, and using the associated solutions of the matching previously encountered problems to suggest a solution to the current problem. In response to receipt of a description of a current problem, a conventional CBR system retrieves the closest matching cases from a case database using a search engine and iteratively prompts the user for additional descriptive information until the retrieved case or cases identified by the search engine are sufficiently similar to the current problem to be considered as possible solutions. If a new solution (not previously stored in the case database) is subsequently validated, the validated solution can be entered into the case database and utilized to solve future problems.
Of course, the ability of a CBR system to provide solutions to input problems is limited, in part, by the number of cases stored within the case database and the number of attributes utilized to describe each case. Thus, the quality of solutions produced by a CBR system will typically improve as more cases representing additional experience are stored within the case database and as the number of attributes that may be associated with each case increases. Because a relatively well-developed case database can include several hundreds or thousands of unique cases, which may each include, for example, fifty different attributes, the technique utilized to search the case database for cases that closely match the current problem must be efficient if the CBR system is to achieve high performance while accurately identifying the best matching case for the current problem.
As should thus be apparent, it would be desirable from a performance standpoint to provide an improved method and system for searching the case database of a CBR system.
SUMMARY OF THE INVENTION
It is therefore one object of the present invention to provide an improved expert system.
It is another object of the present invention to provide an improved case-based reasoning system.
It is yet another object of the present invention to provide a case-based reasoning system that compresses selected data within a case database into a tokenized view in order to improve the efficiency of the case database search engine.
The foregoing objects are achieved as is now described. A case-based reasoning system is equipped with a case database capable of storing a plurality of cases that each include one or more attributes. A view generator in the case-based reasoning system generates a view of the case database by representing each case within at least a selected subset of the plurality of cases within the case database with one or more uniform-length view tokens. An input parser in the case-based reasoning system provides a tokenized representation of an input incident that includes one or more input tokens. The case-based reasoning system further includes a search engine that compares the input tokens with the view tokens to identify one or more closely matching cases within the view. By searching the view rather than directly searching the case database, cases that closely match the input are efficiently identified.
The above as well as additional objects, features, and advantages of the present invention will become apparent in the following detailed written description.


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