PROCEEDINGS OF 2019 14TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS (ICEMI)(2019)
Shandong Key Lab Hort Machinery & Equipment
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摘要
Aiming at the problems of poor retrieval intelligence and low recall rate of irrigation fertilization strategy in apple orchard, an intelligent retrieval algorithm of apple orchard irrigation fertilization strategy is proposed to realize the intelligent retrieval of irrigation fertilization strategy. Firstly, the retrieval of the user's irrigation fertilization strategy is divided into title retrieval and comprehensive retrieval, and the comprehensive retrieval is a compound search with the name of the heirloom, the upload time range and the evaluation value. Secondly, the semantic similarity retrieval algorithm based on ontology is proposed for the title retrieval of apple orchard irrigation fertilization strategy, and the domain ontology of apple orchard is constructed. Lastly, the semantic similarity between the retrieval statement and the title is calculated by using the concept similarity algorithm based on ontology and the sentence similarity algorithm, and the title of irrigation fertilization strategy is sorted according to the similarity degree. This paper compares the algorithm with the traditional keyword retrieval, and the experimental results show that the retrieval algorithm proposed in this paper has higher recall rate of irrigation fertilization strategy than the traditional keyword retrieval recall rate, and can realize the intelligent retrieval of the irrigation fertilization strategy of apple orchard.
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关键词
Apple orchard,Irrigation Fertilization strategy,Ontology,Semantic retrieval