.png){kind=icon}
.png){kind=icon}
Return
A self-improving helpdesk service system using case-based reasoning techniques
.png){kind=icon}
PRE
AI
DOI：10.1016/0166-3615(96)00033-4.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Case-Based Reasoning (CBR) is the process of solving a given problem based on the knowledge gained from solving precedents. It is an effective technique in the area of customer services or helpdesks. That is, a CBR system is used to solve most of the commonly occurring customer problems. While the implementation techniques may vary, most CBR systems include the following five steps: case representation and storage, precedent matching and retrieval, adaptation of the retrieved solution, validation of the solution, and finally, casebase update to include the information gained from the new problem. This paper details the various implementation techniques for these five steps, while focusing on a particular helpdesk system, namely SmartUSA, developed for the Union Camp Corporation. This system solves a customer's problem by filtering the problem description through an alias table to generate a brief description and then matching the brief description with the cases in the database. It has proved to be an effective and user-friendly system that has successfully handled different descriptions of the same problem and allowed for the casebase to be built in free-format (plain) text. This system has significantly reduced the workload and the response time in the customer services department of the Union Camp Corporation.
Keywords:
case-based reasoning
machine learning
expert system
artificial intelligence
helpdesk service automation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
9.1
Papers:
2.9K
Citations:
1.1W
Organization
No organization information available