A manual experiment on commonsense knowledge acquisition from web corpora

Acquiring commonsense knowledge from text is an important but challenging problem. In this paper, we described a three-subject experiment on commonsense knowledge acquisition from Chinese sentences extracted from a web corpus, aiming to investigate how people acquire commonsensical assertions from g...

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Bibliographic Details
Published in2008 International Conference on Machine Learning and Cybernetics Vol. 3; pp. 1564 - 1569
Main Authors Yao Zhu, Liang-Jun Zang, Dong-Sheng Wang, Cun-Gen Cao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Agreement Test
Basic Level Category
Co-occurrence Frequency
Commonsense Knowledge Acquisition
Concordance Test
Cybernetics
Divergence Test
Knowledge acquisition
Knowledge engineering
Machine learning
Manual Experiment
Manuals
Neck
Web Corpora
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Summary:Acquiring commonsense knowledge from text is an important but challenging problem. In this paper, we described a three-subject experiment on commonsense knowledge acquisition from Chinese sentences extracted from a web corpus, aiming to investigate how people acquire commonsensical assertions from given sentences. We analyzed the experiment results from the perspectives of agreement test, concordance test, and divergence test. An important conclusion of our experiment is that sentences are different in their suitability, i.e. difficulty grade, for commonsense knowledge acquisition. And this difficulty grade also affects the number of commonsensical assertions acquired from a sentence, as well as the difference among the acquisition performances of different human subjects. We also discussed the problem of characterizing the difficulty grade by co-occurrence frequency of words and basic level category words.
ISBN:1424420954
9781424420957
ISSN:2160-133X
DOI:10.1109/ICMLC.2008.4620655