Abstract
The Internet presents a huge amount of biological data. It is difficult to extract relevant data from various sources. Therefore, the availability of robust, flexible Information Extraction (IE) systems and tool that transform the Web pages into program-friendly structures such as a relational database. This paper made a study on information extraction tools. Which can be used for Biological databases. The tools have been classified based on four categories such as tools for Manually constructed Information Extraction, Supervised Wrapper Induction System, Semi supervised Information Extraction Systems, Unsupervised Information extraction Systems. Finally we made a comparative study on the Information Extraction tools used for Biological database based on the technique used such as scan Pass, Extraction Rules Type, Features used, Learning Algorithm and Tokenization Schemes.
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