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Explained Activity Recognition with Computational Assumption-based Argumentation


Authors: X. Fan, S. Liu, H. Zhang, C. Leung, and C. Miao
Title: Explained Activity Recognition with Computational Assumption-based Argumentation
Abstract: Activity recognition is a key problem in multi-sensor systems. In this work, we introduce Computational Assumption-based Argumentation, an argumentation approach that seamlessly combines sensor data processing with high-level inference. Our method gives classification results comparable to machine learning based approaches with reduced training time while also giving explanations.
Keywords: 
Conference Name: 22nd European Conference on Artificial Intelligence (ECAI'16)
Location: The Hague, Holland
Publisher: IOS Press
Year: 2016
Accepted PDF File: Explained_Activity_Recognition_with_Computational_Assumption-based_Argumentation_accepted.pdf
Permanent Link: http://dx.doi.org/10.3233/978-1-61499-672-9-1590
Reference: X. Fan, S. Liu, H. Zhang, C. Leung, and C. Miao, “Explained activity recognition with computational assumption-based argumentation,” in Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI’16). IOS Press, August–September 2016, pp. 1590–1591.
bibtex: 
@inproceedings{LILY-c100, 
    author	= {Fan, Xiuyi and Liu, Siyuan and Zhang, Huiguo and Leung, Cyril and Miao, Chunyan},
    title	= {Explained Activity Recognition with Computational Assumption-based Argumentation},  
    booktitle	= {Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI'16)}, 
    year		= {2016}, 
    month	= {August--September}, 
    pages	= {1590-1591}, 
    location	= {The Hague, Holland},
    publisher	= {IOS Press},
 }