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Proceedings of the 2nd International Symposium on Information Processing (ISIP 2009)

Huangshan, China, August 21-23, 2009

Editors: Fei Yu, Jian Shu, and Guangxue Yue

AP Catalog Number: AP-PROC-CS-09CN002

ISBN: 978-952-5726-02-2 (Print), 978-952-5726-03-9 (CD-ROM)

Page(s): 441-444

Distributed Software Interactive Behavior Analysis Based on Knowledge Fusion

        Junfeng Man, Xiangbing Wen, Zhibing Wang, and Guangbin Liu

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A novel online analysis method for software Interactive Behavior (IBs) is presented in the paper. Scenario-sensitive method is adopted to model complicated IBs among third party software entities. By fusing real-time self-experience and pervious experience based on knowledge, the creditability of interactive entities is computed automatically. Multi-Entity Bayesian Network (MEBN) tool is adopted to construct reusable domain “knowledge fragments”. If current scenario is similar to pervious one, then pervious one is reused; if there is no similar scenario, evidences gained from monitoring and pervious experience are fused to construct behavior model for this scenario. The combination of large and small granularity knowledge reuse improves analysis efficiency of IBs.

Index Terms

multi-entity Bayesian network, interactive behavior analysis, scenario, knowledge fusion

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