title: Automatic extraction of microorganisms and their habitats from free text using text mining workflows.
abstract: In this paper we illustrate the usage of text mining workflows to automatically extract    instances of microorganisms and their habitats from free text; these entries can then be curated and added to different databases. To this end, we use a Conditional Random Field (CRF) based classifier, as part of the workflows, to extract the mention of microorganisms, habitats and the inter-relation between organisms and their habitats.    Results indicate a good performance for extraction of microorganisms and the relation extraction aspects of the task (with a precision of over 80%), while habitat recognition is only moderate (a precision of about 65%). We also conjecture that pdf-to-text conversion can be quite noisy and this implicitly affects any sentence-based relation extraction algorithms.
authors: National Centre for Text Mining, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK. kollurub@cs.man.ac.uk
authors: Balakrishna
authors: B
authors: Kolluru
authors: Sirintra
authors: S
authors: Nakjang
authors: Robert P
authors: RP
authors: Hirt
authors: Anil
authors: A
authors: Wipat
authors: Sophia
authors: S
authors: Ananiadou
mesh_terms: D000465:Algorithms; D001331:Automation; D001419:Bacteria / Q000145:classification*; D057225:Data Mining / Q000379:methods*; D017753:Ecosystem