Name
Abstract | ||
|---|---|---|
Developing knowledge bases using knowledge-acquisition tools is difficult because each stage of development requires performing a distinct knowledge-acquisition task. This paper describes these different tasks and surveys current tools that perform them. It also addresses two issues confronting tools for start-to-finish development of knowledge bases. The first issue is how to support multiple stages of development. This paper describes Protos, a knowledge-acquisition tool that adjusts the training it expects and assistance it provides as its knowledge grows. The second issue is how to integrate new information into a large knowledge base. This issue is addressed in the description of a second tool, KI, that evaluates new information to determine its consequences for existing knowledge. |
Year | DOI | Venue |
|---|---|---|
1989 | 10.1007/BF00130714 | Machine Learning |
Keywords | Field | DocType |
knowledge-acquisition tools,knowledge-base refinement,knowledge-base development | Procedural knowledge,Data science,Knowledge integration,Domain knowledge,Personal knowledge management,Computer science,Knowledge-based systems,Knowledge engineering,Knowledge base,Open Knowledge Base Connectivity | Journal |
Volume | Issue | ISSN |
4 | 3-4 | 1573-0565 |
Citations | PageRank | References |
28 | 8.60 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ray Bareiss | 1 | 87 | 22.63 |
| Bruce W. Porter | 2 | 110 | 15.30 |
| Kenneth S. Murray | 3 | 78 | 13.86 |