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A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set
Joint Authors
Qamar, Usman
Muzaffar, Abdul Wahab
Azam, Farooque
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-10
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The information extraction from unstructured text segments is a complex task.
Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size.
Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining.
Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades.
A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques.
In the last decade, the focus has changed to hybrid approaches showing better results.
This research presents a hybrid feature set for classification of relations between biomedical entities.
The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS) and a ranking algorithm.
Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations.
Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001.
Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus.
American Psychological Association (APA)
Muzaffar, Abdul Wahab& Azam, Farooque& Qamar, Usman. 2015. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1058034
Modern Language Association (MLA)
Muzaffar, Abdul Wahab…[et al.]. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1058034
American Medical Association (AMA)
Muzaffar, Abdul Wahab& Azam, Farooque& Qamar, Usman. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1058034
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1058034