DocumentCode
3059622
Title
Bootstrapping algorithms for an application in the automotive domain
Author
Schierle, Martin ; Schulz, Sascha
Author_Institution
DaimlerChrysler AG, Ulm
fYear
2007
fDate
13-15 Dec. 2007
Firstpage
198
Lastpage
203
Abstract
Bootstrapping algorithms for information extraction gained a lot of attention in the scientific community over the past few years. Therefore the approaches used differ in major parts of the algorithms as well as in detail. This paper will give an overview of some variants and will evaluate their use in a real-world problem, the extraction of component names from automotive repair orders.
Keywords
automotive components; automotive engineering; data mining; learning (artificial intelligence); maintenance engineering; automotive repair order; bootstrapping algorithm; component name; information extraction; real-world problem; scientific community; Algorithm design and analysis; Automotive engineering; Data mining; Information analysis; Iterative algorithms; Knowledge management; Machine learning; Machine learning algorithms; Research and development; Scattering;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications, 2007. ICMLA 2007. Sixth International Conference on
Conference_Location
Cincinnati, OH
Print_ISBN
978-0-7695-3069-7
Type
conf
DOI
10.1109/ICMLA.2007.53
Filename
4457231
Link To Document