S. Djoko et al., AN EMPIRICAL-STUDY OF DOMAIN KNOWLEDGE AND ITS BENEFITS TO SUBSTRUCTURE DISCOVERY, IEEE transactions on knowledge and data engineering, 9(4), 1997, pp. 575-586
Citations number
23
Categorie Soggetti
Information Science & Library Science","Computer Sciences, Special Topics","Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence","Computer Science Information Systems
Discovering repetitive, interesting, and functional substructures in a
structural database improves the ability to interpret and compress th
e data. However, scientists working with a database in their area of e
xpertise often search for predetermined types of structures or for str
uctures exhibiting characteristics specific to the domain. This paper
presents a method for guiding the discovery process with domain-specif
ic knowledge. In this paper, the SUBDUE discovery system is used to ev
aluate the benefits of using domain knowledge to guide the discovery p
rocess. Domain knowledge is incorporated into SUBDUE following a singl
e general methodology to guide the discovery process. Results show tha
t domain-specific knowledge improves the search for substructures that
are useful to the domain and leads to greater compression of the data
. To illustrate these benefits, examples and experiments from the comp
uter programming, computer-aided design circuit, and artificially gene
rated domains are presented.