大数据 ›› 2018, Vol. 4 ›› Issue (2): 72-85.doi: 10.11959/j.issn.2096-0271.2018020

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基于关联规则的气象服务智能推荐

赵文芳,刘亚楠,余东昌   

  1. 北京市气象信息中心,北京 100089
  • 出版日期:2018-03-15 发布日期:2018-04-10
  • 作者简介:赵文芳(1980-),女,北京市气象信息中心高级工程师、科长,主要研究方向为大数据技术在气象信息领域的应用、机器学习。|刘亚楠(1981-),男,北京市气象信息中心工程师,主要研究方向为计算机网络安全。|余东昌(1978-),男,北京市气象信息中心高级工程师、科长,主要研究方向为软件架构、高性能计算、并行计算。
  • 基金资助:
    中国气象局公益性行业科研专项基金资助项目(201206031)

Intelligent recommendation of meteorological service based on association rules

Wenfang ZHAO,Yanan LIU,Dongchang YU   

  1. Beijing Meteorological Information Center,Beijing 100089,China
  • Online:2018-03-15 Published:2018-04-10
  • Supported by:
    The Public Welfare Industry Research Funds of China Meteorological Bureau(201206031)

摘要:

针对气象公众服务存在的专业化程度不高、针对性不强等问题,提出了一种使用关联规则向用户推荐气象服务产品的方法。将用户访问的Web日志数据经过清洗、转换后进行关联规则挖掘,同时设计了一种基于气象产品浏览总次数计算产品相似度的算法,对挖掘出来的关联规则进行筛选。共进行了5组实验,并对用户浏览产品的行为进行了简单预测。实验结果表明,挖掘出的规则在降水天气和雾霾天气中的正确率比较高,结合气象服务产品的相似度能过滤掉10%的无效规则,从而提升规则的正确性。

关键词: 智能推荐, 关联规则, Web日志, 气象公众服务, 并行计算, 相似度, 协同过滤

Abstract:

To overcome the problem in which public meteorological services are rarely optimized for personalization,a recommendation method incorporating improved association rules and collaborative filtering was presented.First,FPGrowth algorithm was applied on pre-processed Web log data to generate association rules.Meanwhile,a customized collaborative filtering algorithm was used to calculate pairwise similarities between meteorological products based on users' browsing records.A total of five experiments were conducted.The experimental results show that the rules are relatively accurate for precipitation and haze weather,because pairwise similarities between meteorological products which are calculated by the proposed algorithm could reduce the total number of invalid or irrelevant association rules by 10%.

Key words: intelligent recommendation, association rule, Web log, public meteorological service, parallel computing, similarity, collaborative filtering

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