Method for matching user descriptions of technical problem manifestations with system-level problem descriptions

• US 7,493,325 B1
• Filed: 05/15/2008
• Issued: 02/17/2009
• Est. Priority Date: 05/15/2008
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: International Business Machines Corporation
• Inventors: Kundavaram, Anjan Reddy, Styles, David B., Schreiber, Elizabeth A., Bhatnagar, Radhika, Etgen, Michael P., Court, Barnaby L.
• Primary Examiner(s): Le; Debbie M
• Application Number:
  US12/120,829
• Time in Patent Office: 278 Days
• Field of Search: 707 1- 7, 707100-102, 705/1
• US Class Current: 1/1
• CPC Class Codes: G06F 16/30 of unstructured textual data document management systems G06F16/93
• CPC Class Codes: Y10S 707/99931 Database or file accessing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99937 Sorting
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

A computer implemented method of matching user descriptions of technical problem manifestations with system problem descriptions in which system-level symptoms for computer-related problems which map to problem descriptions and recommended fixes are broken into sub-phrases, and an index of association ratios between the system-level symptom sub-phrases and sub-phrases derived from text extracted from corpora related to computer problem symptoms is generated and prioritized. When user-entered text related to a computer-related problem is received, it is searched against the prioritized index, and matches are presented for the user in order of prioritization from which the user can select and run a recommended fix to which the selection is mapped.

Claims

1. A computer implemented method of matching user descriptions of technical problem manifestations with system problem descriptions, comprising:

a. receiving from a symptom database at least one system-level symptom for each of a plurality of computer-related problems which maps to a corresponding problem description and a recommended fix for said one of said computer-related problems;

b. breaking each of the system-level symptoms into system-level symptom sub-phrases based on a pre-selected breakdown methodology;

c. generating a list of association ratios between symptom sub-phrases derived from text extracted from corpora related to computer problem symptoms and the system-level symptom sub-phrases based upon a pre-selected association methodology, each of which derived sub-phrases is linked back to the corresponding problem description, said association ratios being based on a degree of closeness of matching relationship between the symptom sub-phrases derived from text extracted from corpora related to computer problem symptoms and the system-level symptom sub-phrases;

d. generating in a prioritized index of symptom association (PISA) database an index of prioritized association ratios between the derived symptom sub-phrases and the system-level symptom sub-phrases based on a pre-selected ranking methodology, said index of prioritized association ratios representing an arrangement of the association ratios in order of the degrees of closeness of matching relationships between respective symptom sub-phrases derived from text extracted from corpora related to computer problem symptoms and the system-level symptom sub-phrases;

e. receiving user-entered text related to a symptom of a computer-related problem;

f. searching the user-entered text against the prioritized index of symptom associations;

g. presenting a list of textual matches between the user-entered text and the derived and system-level symptom sub-phrases in order of prioritization;

h. receiving a user'"'"'s selection of a derived or system-level symptom sub-phrase from the list and running the recommended fix to which the selected symptom sub-phrase is mapped;

i. if the computer-related problem is fixed by running the recommended fix, adding the user-entered text to the index of prioritized symptom associations of the PISA database with a corresponding association ratio based on a matching relationship between the user-entered text and the selected system-level symptom sub-phrase; and

j. if the computer-related problem is not fixed by running the recommended fix, prompting the user to enter another selection of a derived or system-level symptom sub-phrase from the list.