
pmid: 16580973
Scientific progress is increasingly based on knowledge and information. Knowledge is now recognized as the driver of productivity and economic growth, leading to a new focus on the role of information in the decision-making process. Most scientific knowledge is registered in publications and other unstructured representations that make it difficult to use and to integrate the information with other sources (e.g. biological databases). Making a computer understand human language has proven to be a complex achievement, but there are techniques capable of detecting, distinguishing and extracting a limited number of different classes of facts. In the biomedical field, extracting information has specific problems: complex and ever-changing nomenclature (especially genes and proteins) and the limited representation of domain knowledge.
Biomedical Research, Abstracting and Indexing, Dictionaries as Topic, Information Storage and Retrieval, Databases, Bibliographic, Pattern Recognition, Automated, Semantics, Vocabulary, Controlled, Terminology as Topic, Humans, Periodicals as Topic, Language, Natural Language Processing
Biomedical Research, Abstracting and Indexing, Dictionaries as Topic, Information Storage and Retrieval, Databases, Bibliographic, Pattern Recognition, Automated, Semantics, Vocabulary, Controlled, Terminology as Topic, Humans, Periodicals as Topic, Language, Natural Language Processing
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 90 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
