Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/427637
Title: | Enrichment of a medicinal plant ontology using IE from biomedical literature |
Researcher: | Niyati Kumari Behera |
Guide(s): | Mahalakshmi, G S |
Keywords: | Engineering and Technology Engineering Engineering Biomedical Medicinal plants Therapeutic plants Restorative plants |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | Currently, extracting and analysing information about medicinal plants has become a core interest for people, as many are trying to switch from allopathy to naturopathy. The tribes and provincial individuals in India have gigantic information of therapeutic plants and their utilize in treating diverse maladies. Parts of the plants such as leaves, bark, roots, flowers and fruits are used for various medicinal preparations. Apart from having a wealthy source of supplements, antioxidant and anti-bacterial properties, treatment utilizing restorative plants hold a solid ground since these plants are considered to be secure and have no side impacts. newlineRecent time has also seen a significant use of medicinal plants in allopathy as crude ingredient for a few vital drugs. As the days cruised by, this tacit knowledge is fading away with the experts. But fortunately, the World Wide Web has voluminous information regarding medicinal plants available online. For the reason of preservation, domestication and maintainble utilization of therapeutic plants, there is a desperate require for advancement of a computer supported framework for these precious plant user community. newlineOwing to the numerous benefits of medicinal plants, in this work a knowledge discovery framework has been proposed to retrieve information about them from online web resources. Here, an attempt has been made to combine text mining techniques with machine learning algorithm to cover two crucial research aspects in Medicinal Plant Domain (MPD). newline |
Pagination: | xi,118p. |
URI: | http://hdl.handle.net/10603/427637 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 24.49 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.78 MB | Adobe PDF | View/Open | |
03_content.pdf | 12.75 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 56.18 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 196.6 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 110.84 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 450.53 kB | Adobe PDF | View/Open | |
08_chapte r4.pdf | 1.61 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 362.93 kB | Adobe PDF | View/Open | |
10_annexure.pdf | 140.57 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 61.96 kB | Adobe PDF | View/Open |
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