Abstract
In recent years vast amount of biomedical literature is produced and published. Recent developments in biomedical text mining shows potential for supporting scientists in understanding new information from the existing biomedical literature because volume of electronically available biomedical literature are increasing massively. Automated literature mining offers one opportunity to discover different entities from literature. Web Technologies allow these entities to be stores and publish in the form to the further reuse by the researchers. Web technologies are used to share distributed data and resources. Semantic Web approaches have been used in order to describe resources by associating machine processable semantics to them. . The approach presented here includes text mining methodologies to automatically extract domain concepts. Using these domain concepts or Terms as representations of some context in literature we compare these concepts with already existed Seed/Ontological Terms concepts. The methodology has been evaluated in the bioinformatics domain. We have processed a large corpus of full-text articles from a bioinformatics journal. We have used many open source text mining tools and integrate them with our own constructed tool.
Publication: 2014 ICOSST