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A text‐mining perspective on the requirements for electronically annotated abstracts
Author(s) -
Leitner Florian,
Valencia Alfonso
Publication year - 2008
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1016/j.febslet.2008.02.072
Subject(s) - computer science , annotation , information retrieval , credibility , data curation , perspective (graphical) , categorization , task (project management) , biological database , text mining , world wide web , data science , data mining , bioinformatics , artificial intelligence , biology , management , political science , law , economics
We propose that the combination of human expertise and automatic text‐mining systems can be used to create a first generation of electronically annotated information (EAI) that can be added to journal abstracts and that is directly related to the information in the corresponding text. The first experiments have concentrated on the annotation of gene/protein names and those of organisms, as these are the best resolved problems. A second generation of systems could then attempt to address the problems of annotating protein interactions and protein/gene functions, a more difficult task for text‐mining systems. EAI will permit easier categorization of this information, it will help in the evaluation of papers for their curation in databases, and it will be invaluable for maintaining the links between the information in databases and the facts described in text. Additionally, it will contribute to the efforts towards completing database information and creating collections of annotated text that can be used to train new generations of text‐mining systems. The recent introduction of the first meta‐server for the annotation of biological text, with the possibility of collecting annotations from available text‐mining systems, adds credibility to the technical feasibility of this proposal.