Name
Abstract | ||
|---|---|---|
Knowledge Acquisition (KA) is important throughout systems development for gathering expert domain knowledge that is incorporated into the requirements and design of a system. There are problems ensuring that accurate and useful knowledge is captured initially, refined as needed, and transferred to later development efforts in a usable format. We present a method, called tagging, for addressing these problems without undue burden on the KA practitioners, along with initial studies to examine the feasibility of real-time tagging and to inform the design of a tool called TAGGER. TAGGER operates by permitting KA discussions to be "tagged" as they happen with concepts and groupings relevant to software development. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1142/S0218194004001543 | INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING |
Keywords | Field | DocType |
knowledge acquisition, knowledge management, knowledge capture | USable,Data science,Data mining,Domain knowledge,Computer science,Personal knowledge management,Knowledge engineering,Knowledge extraction,Traceability,Software development,Knowledge acquisition | Conference |
Volume | Issue | ISSN |
14 | 1 | 0218-1940 |
Citations | PageRank | References |
1 | 0.37 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heather Richter | 1 | 84 | 5.56 |
| Gregory D. Abowd | 2 | 11979 | 1503.13 |
| Christopher A. Miller | 3 | 334 | 46.70 |
| Harry Funk | 4 | 11 | 1.74 |