Discovering Causal Chains by Integrating Plan Recognition and Sequential Pattern Mining

نویسندگان

  • Shreeram Sahasrabudhe
  • Hector Muñoz-Avila
چکیده

In this paper we define the notion of causal chains. Causal chains are a particular kind of sequential patterns that reflect causality relations according to background knowledge. We also present an algorithm for mining causal chains from a collection of action traces. We run this algorithm on a realworld domain and observe that causal chains can be computed efficiently by quickly identifying inter-related actions.

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تاریخ انتشار 2004