A Framework for Requirements Knowledge Acquisition Using UML and Conceptual Graphs

Author(s):  
Bingyang Wei ◽  
Harry S. Delugach
Author(s):  
Deane B. Cheatham ◽  
Sharolyn Converse Lane

The types of knowledge captured using three knowledge acquisition (KA) methods, conceptual graphs, backward thinking, and sorting tasks, were examined. One hundred and forty-four participants were assigned to one of four conditions: (a) procedural-spatial, (b) procedural-verbal, (c) declarative-spatial, and (d) declarative-verbal. Participants in procedural conditions learned a virtual environment's layout before performing one of three KA tasks. Participants in declarative conditions received a tutorial about McCune-Albright Syndrome before completing a KA task. The procedural and declarative information was presented either spatially or verbally, depending on the condition. The predictive validity of each KA method for each information type (procedural vs. declarative), task type (i.e., spatial vs. verbal), and combinations of information and task types was evaluated by comparing the accuracy of the knowledge depicted by KA methods to various performance measures. Findings indicated that both task type and information type affect the validity of KA methods for capturing knowledge structures.


1998 ◽  
Vol 37 (04/05) ◽  
pp. 327-333 ◽  
Author(s):  
F. Buekens ◽  
G. De Moor ◽  
A. Waagmeester ◽  
W. Ceusters

AbstractNatural language understanding systems have to exploit various kinds of knowledge in order to represent the meaning behind texts. Getting this knowledge in place is often such a huge enterprise that it is tempting to look for systems that can discover such knowledge automatically. We describe how the distinction between conceptual and linguistic semantics may assist in reaching this objective, provided that distinguishing between them is not done too rigorously. We present several examples to support this view and argue that in a multilingual environment, linguistic ontologies should be designed as interfaces between domain conceptualizations and linguistic knowledge bases.


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