Title :
Bootstrapping algorithms for an application in the automotive domain
Author :
Schierle, Martin ; Schulz, Sascha
Author_Institution :
DaimlerChrysler AG, Ulm
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;
Conference_Titel :
Machine Learning and Applications, 2007. ICMLA 2007. Sixth International Conference on
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-0-7695-3069-7
DOI :
10.1109/ICMLA.2007.53
