Biemann, Christian and Böhm, Karsten and Quasthoff, Uwe and Wolff, Christian
Automatic Discovery and Aggregation of Compound Names for the Use in Knowledge Representations.
J.UCS – Journal of Universal Computer Science 9 (6), pp. 530-541.
Other URL: http://www.jucs.org/jucs_9_6/automatic_discovery_and_aggregation
Automatic acquisition of information structures like Topic Maps or semantic networks from large document collections is an important issue in knowledge management. An inherent problem with automatic approaches is the treatment of multiword terms as single semantic entities. Taking company names as an example, we present a method for learning multiword terms from large text corpora exploiting their internal structure. Through the iteration of a search step and a verification step the single words typically forming company names are learnt. These name elements are used for recognizing compounds in order to use them for further processing. We give some evaluation of experiments on company name extraction and discuss some applications.
|Additional information (public):||Proc. I-Know03, Graz, Juli 2003|
|Institutions:|| Languages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Medieninformatik|
|Keywords:||corpora, knowledge management, named entity extraction, semantic relations, text mining, topic maps |
|Subjects:||400 Language > 400 Language, Linguistics|
000 Computer science, information & general works > 004 Computer science
|Refereed:||Yes, this version has been refereed|
|Created at the University of Regensburg:||Partially|
Prof. Dr. Christian Wolff
|Deposited On:||18 Sep 2009 10:33|
|Last Modified:||20 Jul 2011 21:27|