Name
Title | ||
|---|---|---|
A framework for semi-automatic identification, disambiguation and storage of protein-related abbreviations in scientific literature |
Abstract | ||
|---|---|---|
We propose a framework for identifying, disambiguating and storing protein-related abbreviations as found in the full texts of scientific papers, in order to build and maintain a publicly available abbreviation repository via a semi-automatic process. This process involves information extraction methods and techniques for acronym identification and resolution, based on lexical clues and syntactical, largely domain-independent criteria. A dictionary and an ontology for proteins provide the means for matching and disambiguating the biological entities. User feedback is gathered at the end of the process and the confirmed entries are then stored and made available to the scientific community for further reviewing. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICDEW.2011.5767646 | Data Engineering Workshops |
Keywords | DocType | ISBN |
protein-related abbreviation,full text,domain-independent criterion,scientific community,acronym identification,information extraction method,scientific literature,biological entity,scientific paper,semi-automatic process,semi-automatic identification,available abbreviation repository,lexical clue,information retrieval,data mining,natural language processing,ontology,dictionary,dictionaries,bioinformatics,proteins,information extraction | Conference | 978-1-4244-9194-0 |
Citations | PageRank | References |
9 | 0.61 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paolo Atzeni | 1 | 1833 | 742.95 |
| Fabio Polticelli | 2 | 68 | 8.97 |
| Daniele Toti | 3 | 105 | 13.86 |