• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2013, Vol. 35 ›› Issue (5): 154-160.

• 论文 • 上一篇    下一篇

基于复合关键词向量空间的林产品贸易网站用户兴趣模型

王梓1,高金萍2,陈钊1   

  1. (1.北京林业大学信息学院,北京 100083;2.国家林业局调查规划设计院,北京 100714)
  • 收稿日期:2012-03-06 修回日期:2012-10-21 出版日期:2013-05-25 发布日期:2013-05-25
  • 基金资助:

    中央高校基本科研业务费专项资金资助项目(BLX200928)

Compound keywords vector space based user interest
model for forest products trading information website  

WANG Zi1,GAO Jinping2,CHEN Zhao1   

  1. (1.College of Information,Beijing Forestry University,Beijing 100083;2.National Forestry Bureau Survey Planning and Design Institute,Beijing 100714,China)
  • Received:2012-03-06 Revised:2012-10-21 Online:2013-05-25 Published:2013-05-25

摘要:

根据林产品贸易信息的特点,利用一种复合关键词向量空间模型来表示林产品贸易信息网站的用户兴趣模型:向量空间中的每一个复合关键词包括供求分类、林产品名称和产地三个关键词以及林产品的规格、价格范围和公司名称集合等信息,每一个复合关键词均拥有一个用户的感兴趣度值。利用用户的浏览、注册、发布信息等行为以及引入兴趣度值的遗忘因子,为用户兴趣模型提供了学习和更新方法。通过引入用户的短期兴趣集合,使得兴趣模型得以体现用户的长期兴趣和短期兴趣。最后,基于此用户兴趣模型给出了基于内容的推荐算法,并通过对比实验阐明了其优势。

关键词: 林产品, 贸易信息网站, 用户兴趣建模, 复合关键词, 向量空间模型

Abstract:

Based on the features of the forest products trading information, a compound keywords vector space model was utilized to represent the user interest model of the forest products trading information website. Every compound keyword in the vector space consists of three keywords, which are supply and demand classification, the name of the forest product and the production place, and some information about the specifications, price and the company name of the forest products. Every compound keyword has a user interest value. The learning and updating of the user interest model were realized through the browsing, registering and releasing behaviors of the users and introducing the forgetting factors for the interest values, respectively. The persistent interests and the temporary interests of the users were distinguished by introducing a temporary interests group. Finally, the recommendation algorithms based on the contents filtering were proposed based on our user interest model, and its advantage was demonstrated by comparison experiments.

Key words: forest product;trading information website;user interest model;compound keywords;vector space model