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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (1): 37-46    DOI: 10.11925/infotech.2096-3467.2017.01.05
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Extracting Semantic Knowledge from Plant Species Diversity Collections
Jianhua Liu1,2(),Ying Wang1,Zhixiong Zhang1,Chuanxi Li3
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China
2University of Chinese Academy of Sciences, Beijing 100049, China
3China Great Wall Asset Management Co., Ltd, Beijing 100045, China
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[Objective]This paper aims to extract semantic knowledge from the biodiversity studies. [Methods] We proposed a new knowledge extraction framework focusing on species. It included various entities as well as the relationship among them. The new method was then examined with various specialized databases. [Results] The species-oriented knowledge extraction framework, could successfully retrieve semantic information from the target entities and the relations among them. This method expanded the scope of knowledge extraction practice in the biodiversity field. [Limitations] The recall and precision ratio of the new method was effected by the dictionaries and rules. More studies are needed to examine the semantic relationship among the named entities beyond co-occurrence, hierarchical and simple syntactic relations. [Conclusions] The proposed method expands the contents and methods of knowledge extraction in biodiversity research. It supports the semantic information retrieval and computation.

Key wordsPlant Species Diversity      Plant Species      Knowledge Extraction      Relation Extraction     
Received: 14 April 2016      Published: 22 February 2017

Cite this article:

Jianhua Liu,Ying Wang,Zhixiong Zhang,Chuanxi Li. Extracting Semantic Knowledge from Plant Species Diversity Collections. Data Analysis and Knowledge Discovery, 2017, 1(1): 37-46.

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