DocumentCode :
622700
Title :
Building a commonsense knowledge base for context-awareness inference
Author :
Li Zhang ; Shijian Li ; Gang Pan
Author_Institution :
Dept. of Comput. Sci., Zhejiang Univ., Hangzhou, China
fYear :
2013
fDate :
12-14 June 2013
Firstpage :
430
Lastpage :
435
Abstract :
Current context-aware systems often model rigid inference rules for limited user contexts, which constrain their effectiveness in real world usage. In order to achieve flexible context-aware inference, a commonsense knowledge base is essential. But such knowledge base is hard to construct manually. This paper proposes some automatic algorithms to extract commonsense directly from text corpuses. We evaluate the extraction algorithms with comparison with human annotators. We also evaluate the effectiveness of the knowledge base in practical context-awareness inference.
Keywords :
inference mechanisms; knowledge based systems; ubiquitous computing; commonsense knowledge base; context-aware systems; context-awareness inference; inference rules; Computational modeling; Context; Context modeling; Inference algorithms; Knowledge based systems; Semantics; Syntactics; Commonsense Knowledge; Context-awareness; Knowledge Extraction; Knowledge Modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Automation (ICCA), 2013 10th IEEE International Conference on
Conference_Location :
Hangzhou
ISSN :
1948-3449
Print_ISBN :
978-1-4673-4707-5
Type :
conf
DOI :
10.1109/ICCA.2013.6565173
Filename :
6565173
Link To Document :
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