Margin based ontology sparse vector learning algorithm and applied in biology science

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• 作者：Wei Gao^a ; ^{gaowei@ynnu.edu.cn} ; Abdul Qudair Baig^b ; Haidar Ali^b ; Wasim Sajjad^b ; Mohammad Reza Farahani^c
• 关键词：Ontology ; Similarity measure ; Sparse vector ; Margin
• 刊名：Saudi Journal of Biological Sciences
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：24
• 期：1
• 页码：132-138
• 全文大小：611 K
• 卷排序：24

文摘

In biology field, the ontology application relates to a large amount of genetic information and chemical information of molecular structure, which makes knowledge of ontology concepts convey much information. Therefore, in mathematical notation, the dimension of vector which corresponds to the ontology concept is often very large, and thus improves the higher requirements of ontology algorithm. Under this background, we consider the designing of ontology sparse vector algorithm and application in biology. In this paper, using knowledge of marginal likelihood and marginal distribution, the optimized strategy of marginal based ontology sparse vector learning algorithm is presented. Finally, the new algorithm is applied to gene ontology and plant ontology to verify its efficiency.