Ontology population of Philippine medicinal plants
For years, medicinal plants have been used by people (mostly from developing countries) to meet their health requirements due to various reasons. Some people use these plants because of their cultural and historical reasons, while others rely on them because they prefer natural remedies over chemica...
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Main Authors: | , , , |
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Format: | text |
Language: | English |
Published: |
Animo Repository
2012
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Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/12122 |
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Institution: | De La Salle University |
Language: | English |
Summary: | For years, medicinal plants have been used by people (mostly from developing countries) to meet their health requirements due to various reasons. Some people use these plants because of their cultural and historical reasons, while others rely on them because they prefer natural remedies over chemical remedies. Others, however, choose to rely on these plants because they cannot afford pharmaceutical medicines. In the Philippines, the use of medicinal plants is also considered as a source of treatment, especially by Filipinos who have limited access to pharmaceutical medicines. Therefore, it will be beneficial for medicinal plants users if applications on Philippine medicinal plants will be made available. To facilitate this, an ontology of Philippine medicinal plants was populated through information extraction. In this research, information on texts regarding Philippine medicinal plants were extracted for the population of the ontology. Currently, the system developed for information extraction has 53.46% F-measure on medicinal plant articles while 18.39% is the F-measure on fruits and vegetables articles. Also, the populated ontology currently has 50 plant entries. The system performed better in extracting information from stuartxchange.org compared to other websites. Rules still need to be improved to accommodate articles from different types of sources. The resulting ontology can thus be used for the development of applications such as recommender systems and question-answering systems. |
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