Similarity Function Recommender Service Using Incremental User Knowledge Acquisition

2011 ◽  
pp. 219-234 ◽  
Author(s):  
Seung Hwan Ryu ◽  
Boualem Benatallah ◽  
Hye-Young Paik ◽  
Yang Sok Kim ◽  
Paul Compton
Keyword(s):  
Knowledge Acquisition ◽  
Similarity Function ◽  
Recommender Service ◽  
User Knowledge

User Knowledge Acquisition Research for Automotive Design

2013 ◽  
Vol 712-715 ◽  
pp. 2956-2960 ◽  
Author(s):  
Xiang Yao ◽  
Hong Yan Hu ◽  
Jiang Yong Li
Keyword(s):  
Statistical Analysis ◽  
Knowledge Acquisition ◽  
Redundant Information ◽  
User Research ◽  
Automotive Design ◽  
User Knowledge

The paper makes automotive design as a carrier, and uses the methods of user research and statistical analysis; so as to reduce the dimension of automotive design image words and reduce redundant information interference, then obtains the representation of vocabulary and representative car samples of automotive-styling design, to make automotive design more effective.

Knowledge acquisition and refinement with end-user knowledge manipulation systems

1992 ◽  
Author(s):  
Stella M. O'Brien ◽  
Linda Candy ◽  
Ernest A. Edmonds ◽  
Trevor J. Foster
Keyword(s):  
Knowledge Acquisition ◽  
End User ◽  
User Knowledge

The Distinction between Linguistic and Conceptual Semantics in Medical Terminology and its Implication for NLP-Based Knowledge Acquisition

1998 ◽  
Vol 37 (04/05) ◽  
pp. 327-333 ◽  
Author(s):  
F. Buekens ◽  
G. De Moor ◽  
A. Waagmeester ◽  
W. Ceusters
Keyword(s):  
Natural Language ◽  
Knowledge Acquisition ◽  
Natural Language Understanding ◽  
Knowledge Bases ◽  
Linguistic Knowledge ◽  
Medical Terminology ◽  
Language Understanding ◽  
Conceptual Semantics

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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