Automatic Discovery and Aggregation of Compound Names for the Use in Knowledge Representations
Christian Biemann (University of Leipzig, Germany)
Uwe Quasthoff (University of Leipzig, Germany)
Karsten Böhm (University of Leipzig, Germany)
Christian Wolff (Chemnitz University of Technology, Germany)
Abstract: 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.
Keywords: corpora, knowledge management, named entity extraction, semantic relations, text mining, topic maps
Categories: H.3.3, H.5.3, I.2.6, I.2.7, I.7