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中国农学通报

中国农学通报 ›› 2015, Vol. 31 ›› Issue (32): 253-260.doi: 10.11924/j.issn.1000-6850.casb15040080

所属专题： 现代农业发展与乡村振兴

• 农业科技信息 • 上一篇    下一篇

基于用户需求的多维农业信息分类模型研究

王晓乔1,2,廖桂平1,王 访1,李锦卫1,邱春荣1   

  1. (1湖南农业大学农业信息研究所,长沙410128；2湖南科技大学管理学院,湖南湘潭411201）
  • 收稿日期:2015-04-10 修回日期:2015-07-22 接受日期:2015-07-29 出版日期:2015-11-16 发布日期:2015-11-16
  • 通讯作者: 廖桂平
  • 基金资助:
    湖南省科技条件服务平台专项“湖南省现代农业特色产业技术集成与示范平台”(2014TP1001)；湖南省科技重大专项专题四“油茶产业科技信息化服务平台建设”(2013FJ1006-4)；湖南省战略性新兴产业科技攻关项目“黄籽高油分油菜品种选育及产业化关键技术研究”(2014GK1008)；湖南省哲学社会科学基金委托项目“基于信息链模型的企业网络定制模式、效率及机制研究”(13JD20)；湖南省自然科学基金项目“基于客户需求约束的产品多样化定制理论与优化研究”(2015JJ4025)。

Multidimensional Classification Model of Agricultural Information Based on Users’ Demand:

Wang Xiaoqiao1,2, Liao Guiping1, Wang Fang1, Li Jinwei1, Qiu Chunrong1   

  1. (1Institute of Agricultural Information, Hunan Agricultural University, Changsha 410128; 2Management Department, Hunan University of Science and Technology, Xiangtan Hunan 411201)
  • Received:2015-04-10 Revised:2015-07-22 Accepted:2015-07-29 Online:2015-11-16 Published:2015-11-16

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摘要： 为了帮助用户快速检索到所需农业信息，结合用户对农业信息需求的特征，提出了改进的农业信息多维分类模型，并从信息高效存储和处理的角度提出了基于OLAP的多维农业信息分类模型设计方案，最后以湖南油菜网络信息为例，进行实验数据采集与信息分类，实现多维农业分类信息的存储结构。结果表明：（1）随机采集获得的网络农业信息可以通过改进的多维农业信息分类模型来有效表达；（2）行业维度、时间维度、地域维度、形式维度具有客观性，信息属性维度、产业链维度、信息内容维度具有主观性；（3）某些信息在某些维度上没有数据或者无法确定取值时，用空值表示；（4）知识型信息大部分在时间维度和空间维度上没有数据。多维农业信息分类模型可以从每个维度查看数据，也可以抽取不同维度组合进行数据深度分析，为农业信息个性化推送服务奠定了重要基础。实验中实现了多维农业信息的存储结构，是后续农业信息的数据分析、维度优化等工作的必要前提和基础。

关键词: 广东紫珠, 广东紫珠, 体系优化, ISSR-PCR, 引物筛选

Abstract: In order to help users to quickly retrieve agricultural information, a multidimensional classification model of agricultural information was designed according to the new characteristics of the users’ demand for agricultural information. Then the multidimensional classification model scheme based on OLAP was also put forward from the perspective of information efficient storage and processing. Finally Hunan rape network information was taken as an example to collect experiment data and classify the correlative information to realize the storage structure of agricultural information classification based on OLAP. Experimental results showed that: (1) the improved multidimensional model of agricultural information classification could more effectively express the information collected randomly from agricultural network; (2) the dimensions of industry, time, region and form were objective, and the dimensions of information attribution, industrial chain and information content were subjective; (3) empty value “null” could be used to express the value when the information was not determined or there was no data in the dimension; (4) agricultural science and technology information had no data in time and space dimension. OLAP multidimensional agricultural information classification model designed in this paper could not only view relevant data from each dimension, but also extract data from different dimensions to analyze in depth, which laid an important foundation for personalized agricultural information push service. Realization of multidimensional agricultural information storage structure was necessary for data analysis and dimension optimization in follow-up agricultural information work.

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