SPECTRa-T: Machine-Based Data Extraction and Semantic Searching of Chemistry e-Theses

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 iden...

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Bibliographic Details
Published inJournal of chemical information and modeling Vol. 50; no. 2; pp. 251 - 261
Main Authors Downing, Jim, Harvey, Matt J, Morgan, Peter B, Murray-Rust, Peter, Rzepa, Henry S, Stewart, Diana C, Tonge, Alan P, Townsend, Joe A
Format Journal Article
LanguageEnglish
Published Washington, DC American Chemical Society 22.02.2010
Subjects
Academic Dissertations as Topic
Applied sciences
Artificial intelligence
Automatic Data Processing
Chemical Information
Chemistry - education
Computer science; control theory; systems
Data Mining - methods
Databases, Factual
Exact sciences and technology
False Positive Reactions
Information systems. Data bases
Memory organisation. Data processing
Physical chemistry
Physical properties
Semantics
Software
Speech and sound recognition and synthesis. Linguistics
Electronic properties
Semantic analysis
Semantics
Spectral properties
Physical chemistry
Document structure
Metadata
Resource description framework
Text
Experimental study
Data mining
Physical properties
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Summary: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.
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ISSN:1549-9596
1549-960X
DOI:10.1021/ci9003688