title: Chemical documents: machine understanding and automated information extraction.
abstract: Automatically extracting chemical information from documents is a challenging task, but an essential one for dealing with the vast quantity of data that is available. The task is least difficult for structured documents, such as chemistry department web pages or the output of computational chemistry programs, but requires increasingly sophisticated approaches for less structured documents, such as chemical papers. The identification of key units of information, such as chemical names, makes the extraction of useful information from unstructured documents possible.
authors.affiliation: Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
authors.forename: Joe A
authors.initials: JA
authors.lastname: Townsend
authors.forename: Sam E
authors.initials: SE
authors.lastname: Adams
authors.forename: Christopher A
authors.initials: CA
authors.lastname: Waudby
authors.forename: Vanessa K
authors.initials: VK
authors.lastname: de Souza
authors.forename: Jonathan M
authors.initials: JM
authors.lastname: Goodman
authors.forename: Peter
authors.initials: P
authors.lastname: Murray-Rust
mesh_terms: D002621:Chemistry / Q000379:methods*; D001330:Electronic Data Processing / Q000379:methods*; D020407:Internet; D012984:Software; D009626:Terminology as Topic