基于组合模型的农业信息情景感知推荐系统研究
发布时间：2018-08-13 10:55
【摘要】：在大数据环境下,农户在互联网中获取指导农业生产的信息更加困难,随着"一带一路"国家发展战略的全面展开,广大农民对农业信息服务的需求有增无减。针对传统推荐系统不能反映用户兴趣迁移、推荐精度不高等问题,提出来基于组合模型的农业信息推荐系统,提高农业信息推荐的自适应性和准确性。系统结合云计算技术提出一种基于Hadoop+Nutch的全网农业信息数据仓库构建方法,通过纳入时间权重、情景变更和兴趣迁移的优化向量空间模型构建了自适应性的用户兴趣模型,以及借助组合神经网络提高推荐精度提出了组合推荐算法。最后通过评价召回率、准确率等指标表明,基于组合模型的推荐系统可大幅提高推荐准确性和鲁棒性。
[Abstract]:Under the environment of big data, it is more difficult for farmers to obtain the information to guide agricultural production on the Internet. With the development of the "Belt and Road" national development strategy, the farmers' demand for agricultural information services is increasing. Aiming at the problems that the traditional recommendation system can not reflect the user's interest transfer and the recommendation accuracy is not high, the agricultural information recommendation system based on the combination model is put forward to improve the adaptability and accuracy of the agricultural information recommendation. Combined with cloud computing technology, the system proposes a method of constructing agricultural information data warehouse based on Hadoop Nutch. An adaptive user interest model is constructed by taking into account the time weight, scenario change and interest transfer optimization vector space model. A combined recommendation algorithm is proposed to improve the accuracy of recommendation by means of combinatorial neural networks. Finally, by evaluating the recall rate and the accuracy rate, it is shown that the recommendation system based on the combination model can greatly improve the accuracy and robustness of the recommendation.
【作者单位】： 中国农业科学院农业经济与发展研究所;中国农业科学院农业环境与可持续发展研究所;
【基金】：中国农业科学院科技创新工程(编号:ASTIP-IAED-2016-03) 农业水生产力与水环境创新团队项目
【分类号】：S126;TP391.3
本文编号：2180764
[Abstract]:Under the environment of big data, it is more difficult for farmers to obtain the information to guide agricultural production on the Internet. With the development of the "Belt and Road" national development strategy, the farmers' demand for agricultural information services is increasing. Aiming at the problems that the traditional recommendation system can not reflect the user's interest transfer and the recommendation accuracy is not high, the agricultural information recommendation system based on the combination model is put forward to improve the adaptability and accuracy of the agricultural information recommendation. Combined with cloud computing technology, the system proposes a method of constructing agricultural information data warehouse based on Hadoop Nutch. An adaptive user interest model is constructed by taking into account the time weight, scenario change and interest transfer optimization vector space model. A combined recommendation algorithm is proposed to improve the accuracy of recommendation by means of combinatorial neural networks. Finally, by evaluating the recall rate and the accuracy rate, it is shown that the recommendation system based on the combination model can greatly improve the accuracy and robustness of the recommendation.
【作者单位】： 中国农业科学院农业经济与发展研究所;中国农业科学院农业环境与可持续发展研究所;
【基金】：中国农业科学院科技创新工程(编号:ASTIP-IAED-2016-03) 农业水生产力与水环境创新团队项目
【分类号】：S126;TP391.3
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，本文编号：2180764
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