Varying types of input features were employed lexical

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Unformatted text preview: ext mining system in its news production workflow. 4.3 Bioinformatics Bio-entity recognition aims to identify and classify technical terms in the domain of molecular biology that correspond to instances of concepts that are of interest to biologists. Examples of such entities include the names of proteins, genes and their locations of activity such as cells or organism names. Entity recognition is becoming increasingly important with the massive increase in reported results due to high throughput experimental methods. It can be used in several higher level information access tasks such as relation extraction, summarization and question answering. Recently the GENIA corpus was provided as a benchmark data set to compare different entity extraction approaches (Kim et al. 2004). It contains 2,000 abstracts from the MEDLINE database which were hand annotated with 36 54 LDV-FORUM A Brief Survey of Text Mining types of biological entities. The following sentence is an example: “We have shown that <protein> interleukin-1 </protein> (<protein> IL-1 </protein>) and <protein> IL-2 &l...
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