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Named Entity Recognition in Biomedical Domain: A Survey
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 181 - Number 41 |
| Year of Publication: 2019 |
| Authors: T. M. Thiyagu, D. Manjula, Shruthi Shridhar |
10.5120/ijca2019918469
|
T. M. Thiyagu, D. Manjula, Shruthi Shridhar . Named Entity Recognition in Biomedical Domain: A Survey. International Journal of Computer Applications. 181, 41 ( Feb 2019), 30-37. DOI=10.5120/ijca2019918469
Abstract
Named Entity Recognition plays an important role in locating and classifying atomic elements into predefined categories such as person names, locations, organizations, expression of times, temporal expressions etc. Named entity recognition is also called as entity chunking, entity identification and entity extraction. It is a subtask of information extraction, where the structured text is extracted from unstructured text. Named Entity Recognition (NER) is one of the major tasks in Natural Language Processing (NLP). NER has been an active area of research for the past twenty years. An ability to automatically perform NER i.e., identify occurrences of NE in Web contents can have multiple benefits, such as improving the expressiveness of queries and also improving the quality of the search results. A number of factors make building highly accurate NER a challenging task. Though a lot of progress has been made in detecting named entities, NER still remains a big problem at large. In this paper, we explore various methods that are applied to solve NER in the biomedical domain.
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