The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based...The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author' s expression and the user' s understanding and expectation. User spacemodel was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the au-thors' proposed algorithm was efficient.展开更多
运用CiteSpace 5.0R1软件对国内外近20年来蛹虫草领域的研究文献进行可视化分析,旨在为快速掌握蛹虫草的研究现状和判断研究热点提供参考。选择中国知网(CNKI)和Web of Science数据库,通过文献计量学方法分析蛹虫草研究的发文量、机构...运用CiteSpace 5.0R1软件对国内外近20年来蛹虫草领域的研究文献进行可视化分析,旨在为快速掌握蛹虫草的研究现状和判断研究热点提供参考。选择中国知网(CNKI)和Web of Science数据库,通过文献计量学方法分析蛹虫草研究的发文量、机构等指标,利用CiteSpace可视化功能对蛹虫草关键词进行共现、聚类、突现分析。经过筛选最终获得中文文献1 100篇,英文文献1 019篇。蛹虫草研究发文量分析显示蛹虫草研究国内发文量下降,国际发文量持续增长,研究仍处于发展期但已进入国际化阶段。发文机构分析显示中国科学院和上海市农业科学院食用菌研究所分别是蛹虫草中文和英文文献发文量最多的研究机构,表明国内外蛹虫草研究仍以我国科研机构为主。中英文关键词分析显示,蛹虫草研究领域国内聚焦在人工栽培,活性成分的优化提取及功效作用。国际上关注蛹虫草活性成分结构表征及作用机理探索,其中固态发酵、信号通路等是目前研究前沿。通过文献计量学的分析,明确了蛹虫草研究领域的热点和研究前沿,为拓宽蛹虫草研究视野提供了科学的参考。展开更多
文摘The main thrust of this paper is application of a novel data mining approach on the log of user' s feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author' s expression and the user' s understanding and expectation. User spacemodel was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the au-thors' proposed algorithm was efficient.