Overview of biomedical relations extraction using hybrid rule-based approaches.
Unstructured text documents are the major source of knowledge in biomedical fields. These huge amounts of information cause very difficult task of extraction or classification.Therefore, there is a need for knowledge discovery and text mining tools in this field. A lot of works have been done on re...
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Main Authors: | , |
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Format: | Article |
Language: | English English |
Published: |
Engineering and Technology Publishing
2013
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Online Access: | http://psasir.upm.edu.my/id/eprint/30653/1/Overview%20of%20biomedical%20relations%20extraction%20using%20hybrid%20rule.pdf http://psasir.upm.edu.my/id/eprint/30653/ http://www.jiii.org/index.php?m=content&c=index&a=lists&catid=35 |
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Institution: | Universiti Putra Malaysia |
Language: | English English |
Summary: | Unstructured text documents are the major source of knowledge in biomedical fields. These huge amounts of information cause very difficult task of extraction or classification.Therefore, there is a need for knowledge discovery and text mining tools in this field. A lot
of works have been done on relation extraction in
biomedical field. However, each of them was implemented in
three major types of techniques separately i.e.co-occurrence,kernel based and rule based methods. There are many variants of these algorithms have been developed but the combination of it has not been verified yet. In this paper we will compare each of those three methods and propose a new combination of relation extraction method between medical and biological entities from biomedical documents.Furthermore, a lot of researches have been done on
biomedical binary relation such as protein-protein and
gene-protein relations and few researches were on complex
relations such as metabolic pathways. However, in this work
we will discuss the overview a combination of three methods
called as hybrid rule-based to extract complex and simple
relations. |
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