AAAI Publications, Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence

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Contextual Commonsense Knowledge Acquisition from Social Content by Crowd-Sourcing Explanations
Yen-Ling Kuo, Jane Yung-jen Hsu, Fuming Shih

Last modified: 2012-07-15

Abstract


Contextual knowledge is essential in answering questions given specific observations. While recent approaches to building commonsense knowledge basesvia text mining and/or crowdsourcing are successful,contextual knowledge is largely missing. To addressthis gap, this paper presents SocialExplain, a novel approach to acquiring contextual commonsense knowledge from explanations of social content. The acquisition process is broken into two cognitively simple tasks:to identify contextual clues from the given social content, and to explain the content with the clues. An experiment was conducted to show that multiple piecesof contextual commonsense knowledge can be identi-fied from a small number of tweets. Online users verified that 92.45% of the acquired sentences are good,and 95.92% are new sentences compared with existingcrowd-sourced commonsense knowledge bases.

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