title: SPECTRa-T: machine-based data extraction and semantic searching of chemistry e-theses.
abstract: The SPECTRa-T project has developed text-mining tools to extract named chemical entities (NCEs), such as chemical names and terms, and chemical objects (COs), e.g., experimental spectral assignments and physical chemistry properties, from electronic theses (e-theses). Although NCEs were readily identified within the two major document formats studied, only the use of structured documents enabled identification of chemical objects and their association with the relevant chemical entity (e.g., systematic chemical name). A corpus of theses was analyzed and it is shown that a high degree of semantic information can be extracted from structured documents. This integrated information has been deposited in a persistent Resource Description Framework (RDF) triple-store that allows users to conduct semantic searches. The strength and weaknesses of several document formats are reviewed.
authors.affiliation: Unilever Centre for Molecular Informatics, Department of Chemistry, Lensfield Rd., Cambridge CB2 1EW, UK.
authors.forename: Jim
authors.initials: J
authors.lastname: Downing
authors.forename: Matt J
authors.initials: MJ
authors.lastname: Harvey
authors.forename: Peter B
authors.initials: PB
authors.lastname: Morgan
authors.forename: Peter
authors.initials: P
authors.lastname: Murray-Rust
authors.forename: Henry S
authors.initials: HS
authors.lastname: Rzepa
authors.forename: Diana C
authors.initials: DC
authors.lastname: Stewart
authors.forename: Alan P
authors.initials: AP
authors.lastname: Tonge
authors.forename: Joe A
authors.initials: JA
authors.lastname: Townsend
mesh_terms: D004212:Academic Dissertations as Topic; D002621:Chemistry / Q000193:education*; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D001330:Electronic Data Processing; D005189:False Positive Reactions; D012984:Software