Name
Abstract | ||
|---|---|---|
Inference and domain knowledge are the foundation of a Knowledge-based System (KBS). Inference knowledge describes the steps or rules used to perform a task inference; making reference to the domain knowledge that is used. The inference knowledge is typically acquired from the domain experts and communicated to the system developers to be implemented in a KBS. The explicit representation of inference knowledge eases the maintenance of the evolving knowledge. However, the involvements of the knowledge engineers and software developers during the maintenance phase give cause to several problems during the system's life-cycle. In this paper, we provide a possible way of using rule templates to abstract away the inference knowledge to higher conceptual categories that are amenable to domain experts. Backed by a rule editing user-interface that is designed to instantiate the rule templates, the responsibility to maintain the inference knowledge can be assigned to the domain experts, i.e., the originators of the knowledge. The paper demonstrates the feasibility of the idea by making a case of inference knowledge applied to assessment task such as triage decision making. Five rule templates to represent the inference knowledge of assessment tasks are proposed. We validated the rule templates through case studies in several domains and task, as well as through usability testing. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICITCS.2015.7292974 | 2015 5th International Conference on IT Convergence and Security (ICITCS) |
Keywords | Field | DocType |
domain expert maintainable inference knowledge,assessment task,domain knowledge,knowledge-based system,KBS,task inference,system developer,knowledge engineering,software development,system life-cycle,conceptual category,rule editing user-interface,triage decision making,usability testing | Procedural knowledge,Domain knowledge,Computer science,Inference,Knowledge-based systems,Knowledge engineering,Artificial intelligence,Inference engine,Knowledge base,Machine learning,Legal expert system | Conference |
ISSN | Citations | PageRank |
2473-0122 | 0 | 0.34 |
References | Authors | |
14 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shamimi A. Halim | 1 | 4 | 1.49 |
| Muthukkaruppan Annamalai | 2 | 41 | 5.67 |
| Mohd Sharifuddin Ahmad | 3 | 189 | 34.38 |
| Rashidi Ahmad | 4 | 4 | 1.49 |