计算机科学 ›› 2013, Vol. 40 ›› Issue (4): 169-171.

• 软件与数据库技术 • 上一篇    下一篇

基于相关反馈的微博相似主题时序查询

包红云,李秋丹,宋双永,高珩   

  1. 中国科学院自动化研究所复杂系统管理与控制国家重点实验室北京100190;中国科学院自动化研究所复杂系统管理与控制国家重点实验室北京100190;中国科学院自动化研究所复杂系统管理与控制国家重点实验室北京100190;中国科学院自动化研究所复杂系统管理与控制国家重点实验室北京100190
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(61172106),北京市自然科学基金(4112062)资助

Relevance Feedback-based Search of Topic Time Series Similarity in Micro-blogging

BAO Hong-yun,LI Qiu-dan,SONG Shuang-yong and GAO Heng   

  • Online:2018-11-16 Published:2018-11-16

摘要: 提出了一种基于相关反馈的微博相似主题时序查询方法。该方法通过考虑用户对不同查询结果是否满意的反馈情况,建立修改度量系数的目标函数,从而实现微博中体现用户兴趣的主题时序相似性计算,为用户提供更满意的相似主题时序查询结果。基于该方法设计了一个可视化的微博相似主题时序查询系统,在微博代表性网站-Twitter数据集上进行的实验,表明了该方法在微博背景下的相似主题时序查询中的有效性。

关键词: 微博客,主题时序,相似查询,相关反馈

Abstract: A new approach based on relevance feedback was proposed for the topic time series similarity search in micro-blogging.By considering whether the user is satisfied with the returned time series,we established an objective function for learning the coefficient of the unique metric,which reflects the user’s accurate interest.Therefore,the approach can provide the user with more satisfying topic time series in micro-blogging.We also developed a topic time series similarity search system in micro-blogging based on the new approach.Experiment results on Twitter data show the effectiveness of our proposed approach.

Key words: Micro-blogging,Topic time series,Similarity search,Relevance feedback

[1] He Y,Su W,Tian Y,et al.Summarizing microblogs on network hot topics[C]∥iTAP:the 2011International Conference on Internet Technology and Applications.2011:1-4
[2] Yang J,Leskovec J.Patterns of temporal variation in onlinemedia[C]∥WSDM’11:Proceedings of the Fourth ACM International Conference on Web Search and Data Mining.2011:177-186
[3] Song S,Li Q,Bao H.Detecting dynamic association among twitter topics[C]∥WWW 2012:Proceedings of the 2012ACM Conference on the World Wide Web.2012:605-606
[4] Keogh E J,Pazzani M J.Relevance feedback retrieval of time series data[C]∥SIGIR 1999:the 22nd Annual ACM Conference on Special Interest Group on Information Retrieval.1999:183-190
[5] 郑斌祥,席裕庚,杜秀华.利用反馈的时序模式挖掘算法研究[J].控制与决策,2002,17(5):527-531
[6] 秦吉胜,王淑静,宋瀚涛.基于小波变换和反馈的时间序列相似模式搜索算法[J].北京理工大学学报,2004,24(12):1069-1073
[7] Pawling A,Madey G.Feature Clustering for Data Steering inDynamic Data Driven Application Systems[C]∥ICCS 2009,Part II,Lecture Notes in Computer Science.Volume 5545,2009:460-469
[8] Meij E,Weerkamp W,Rijke M D.Adding Semantics to Micro-blog Posts[C]∥WSDM’12:Proceedings of the fourth ACM international conference on Web search and data mining.2012:563-572
[9] Griery C,Thomas K,Paxsony V,et al.@spam:The Under-ground on 140Characters or Less[C]∥CCS’10:Proceedings of the 17th ACM Conference on Computer and Communications Security.2010:27-37

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