𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Portal-based Knowledge Environment for Collaborative Science

✍ Scribed by Karen Schuchardt; Carmen Pancerella; Larry A. Rahn; Brett Didier; Deepti Kodeboyina; David Leahy; James D. Myers; Oluwayemisi O. Oluwole; William Pitz; Branko Ruscic; Jing Song; Gregor von Laszewski; Christine Yang


Publisher
John Wiley and Sons
Year
2007
Tongue
English
Weight
229 KB
Volume
19
Category
Article
ISSN
1532-0626

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


An exploratory study of the knowledge ba
✍ Fouad Abd-El-Khalick; Saouma BouJaoude πŸ“‚ Article πŸ“… 1997 πŸ› John Wiley and Sons 🌐 English βš– 264 KB πŸ‘ 2 views

The purpose of this study was to describe the knowledge base of a group of science teachers in terms of their knowledge of the structure, function, and development of their disciplines, and their understanding of the nature of science. The study also aimed to relate the teachers' knowledge base to t

A system architecture for knowledge-base
✍ ANNELI EDMAN; ANDREAS HAMFELT πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 292 KB

Hypermedia systems and knowledge systems can be viewed as #ip-sides of the same coin. The former are designed to convey information and the latter to solve problems; developments beyond the basic techniques of each system type requires techniques from the other type. In this paper, we introduce the

Evaluation of verification tools for kno
✍ ALUN D. PREECE; STΓ‰PHANE TALBOT; LAURENCE VIGNOLLET πŸ“‚ Article πŸ“… 1997 πŸ› Elsevier Science 🌐 English βš– 330 KB

Validation has emerged as a significant problem in the development of knowledgebased systems (KBS). Verification of KBS correctness and completeness has been cited as one of the most difficult aspects of validation. A number of software tools have been developed to perform such verification, but non

A context model for knowledge-intensive
✍ PINAR Γ–ZTÜRK; AGNAR AAMODT πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 436 KB

Decision-support systems that help solving problems in open and weak theory domains, i.e. hard problems, need improved methods to ground their models in real-world situations. Models that attempt to capture domain knowledge in terms of, e.g. rules or deeper relational networks, tend either to become