Book chapter
TEXT MINING THE BIOMEDICAL LITERATURE FOR IDENTIFICATION OF POTENTIAL VIRUS/BACTERIUM AS BIO-TERRORISM WEAPONS
Terrorism Informatics, pp.385-406
Integrated Series in Information Systems, Springer Nature
01 Jan 2008
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
There are some viruses and bacteria that have been identified as bioterrorism weapons. However, there are a lot other viruses and bacteria that can be potential bioterrorism weapons. A system that can automatically suggest potential bioterrorism weapons will help laypeople to discover these suspicious viruses and bacteria. In this paper we apply instance-based learning & text mining approach to identify candidate viruses and bacteria as potential bio-terrorism weapons from biomedical literature. We first take text mining approach to identify topical terms of existed viruses (bacteria) from PubMed separately. Then, we apply a text mining method bridge these terms as instances with the remaining viruses (bacteria) and thus to discover how much these terms describe the remaining viruses (bacteria). In the end, we build an algorithm to rank all remaining viruses (bacteria). We suspect that the higher the ranking of the virus (bacterium) is, the more suspicious they will be potential bio-terrorism weapon. Our findings are intended as a guide to the virus and bacterium literature to support further studies that might then lead to appropriate defense and public health measures.
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Details
- Title
- TEXT MINING THE BIOMEDICAL LITERATURE FOR IDENTIFICATION OF POTENTIAL VIRUS/BACTERIUM AS BIO-TERRORISM WEAPONS
- Creators
- Xiaohua Hu - Drexel UniversityXiaodan ZhangDaniel WuXiaohua ZhouPeter Rumm - Drexel Univ, Sch Publ Hlth, Philadelphia, PA 19104 USA
- Contributors
- H Chen (Editor)E Reid (Editor)J Sinai (Editor)A Silke (Editor)B Ganor (Editor)
- Publication Details
- Terrorism Informatics, pp.385-406
- Series
- Integrated Series in Information Systems
- Publisher
- Springer Nature; NEW YORK
- Number of pages
- 22
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Identifiers
- 991019170595104721
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- Computer Science, Information Systems
- Computer Science, Interdisciplinary Applications
- Information Science & Library Science
- Political Science