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  • 标题:A Plan Recognition Method using Prefix Computation in Web Access Log Analysis
  • 本地全文:下载
  • 作者:Ryosuke Kojima ; Taisuke Sato
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2014
  • 卷号:29
  • 期号:3
  • 页码:301-310
  • DOI:10.1527/tjsai.29.301
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:In this paper we propose a new plan recognition method from observations of incomplete action sequences by regarding them as prefixes in a probabilistic context-free grammar (PCFG). In previous work that uses a PCFG for plan recognition, the PCFG receives a sentence, i.e. an observation of complete action sequences to recognize the plan behind it. However, when we deal with real plan recognition problems such as the Web access log analysis, we often cannot have complete sequences of actions and the traditional PCFG approach is not applicable. To overcome this difficulty, we extend the probability computation of PCFGs to prefix probability computation though it requires an infinite sum of probabilities. We applied the proposed method to infer the intended goals of Web site visitors from the online and partial observations of their actions. Also we compared the performance of plan recognition from observations of initial sequences of visitors' actions with that from full observations.
  • 关键词:plan recognition ; prefix ; PCFG ; Web access log
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