Paper Info
Title
Language games: solving the vocabulary problem in multi-case-base reasoning
Abstract
The problem of heterogeneous case representation poses a major obstacle to realising real-life multi-case-base reasoning (MCBR) systems. The knowledge overhead in developing and maintaining translation protocols between distributed case bases poses a serious challenge to CBR developers. In this paper, we situate CBR as a flexible problem-solving strategy that relies on several heterogeneous knowledge containers. We introduce a technique called language games to solve the interoperability issue. Our technique has two phases. The first is an eager learning phase where case bases communicate to build a shared indexing lexicon of similar cases in the distributed network. The second is the problem-solving phase where, using the distributed index, a case base can quickly consult external case bases if the local solution is insufficient. We provide a detailed description of our approach and demonstrate its effectiveness using an evaluation on a real data set from the tourism domain.
Year
DOI
Venue
2005
10.1007/11536406_6
ICCBR
Keywords
Field
DocType
heterogeneous knowledge container,multi-case-base reasoning,language game,external case base,knowledge overhead,case base,eager learning phase,cbr developer,vocabulary problem,similar case,flexible problem-solving strategy,problem-solving phase,heterogeneous case representation,case base reasoning,indexation
Computer science,Interoperability,Eager learning,Expert system,Search engine indexing,Lexicon,Artificial intelligence,Knowledge engineering,Case-based reasoning,Vocabulary,Machine learning
Conference
Volume
ISSN
ISBN
3620
0302-9743
3-540-28174-6
Citations 
PageRank 
References 
3
0.43
20
Authors
3
Name
Order
Citations
PageRank
Paolo Avesani1131189.56
Conor Hayes251646.86
Marco Cova3142571.19