article

On big wisdom

Authors:

Minghui Wu,

Xindong WuAuthors Info & Claims

Knowledge and Information Systems, Volume 58, Issue 1

Pages 1 - 8

https://doi.org/10.1007/s10115-018-1282-y

Published: 01 January 2019 Publication History

Abstract

This paper defines big wisdom with a HAO/BIBLE framework, which integrates human intelligence (HI), artificial intelligence (AI), and organizational/business intelligence (O/BL) with Bigdata analytics in Large Environments, for industrial intelligence in organizational activities. Big wisdom starts with Bigdata, discovers big knowledge, and facilitates human and machine synergism for complex problem solving. When the HAO/BIBLE framework is applied to a regular (non-Bigdata) environment, it becomes the well-known PEAS agent structure, and when the knowledge graph in HAO/BIBLE relies on domain expertise (rather than big knowledge), HAO/BIBLE serves as an expert system. This paper compares and contrasts Bigdata, big knowledge, and big wisdom and instantiates HAO/BIBLE with a case study for intelligent catering services to illustrate synergized HAO intelligence (HI?+?AI?+?OI) for big wisdom.

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Cited By

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Zou RLiu SLuo YLiu YFeng JWei MSun JWooldridge MDy JNatarajan S(2024)Balancing humans and machinesProceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v38i16.29714(17628-17636)Online publication date: 20-Feb-2024
https://dl.acm.org/doi/10.1609/aaai.v38i16.29714
Zhong LWu JLi QPeng HWu X(2023)A Comprehensive Survey on Automatic Knowledge Graph ConstructionACM Computing Surveys10.1145/361829556:4(1-62)Online publication date: 5-Sep-2023
https://dl.acm.org/doi/10.1145/3618295
Li YYu LLiu JGuo LWu YWu X(2022)NetDPO: (delta, gamma)-approximate pattern matching with gap constraints under one-off conditionApplied Intelligence10.1007/s10489-021-03000-252:11(12155-12174)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1007/s10489-021-03000-2
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On big wisdom
1. Information systems
  1. Information systems applications
    1. Decision support systems

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Published In

Knowledge and Information Systems Volume 58, Issue 1

January 2019

245 pages

ISSN:0219-1377

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Springer-Verlag

Berlin, Heidelberg

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Published: 01 January 2019

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Zou RLiu SLuo YLiu YFeng JWei MSun JWooldridge MDy JNatarajan S(2024)Balancing humans and machinesProceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v38i16.29714(17628-17636)Online publication date: 20-Feb-2024
https://dl.acm.org/doi/10.1609/aaai.v38i16.29714
Zhong LWu JLi QPeng HWu X(2023)A Comprehensive Survey on Automatic Knowledge Graph ConstructionACM Computing Surveys10.1145/361829556:4(1-62)Online publication date: 5-Sep-2023
https://dl.acm.org/doi/10.1145/3618295
Li YYu LLiu JGuo LWu YWu X(2022)NetDPO: (delta, gamma)-approximate pattern matching with gap constraints under one-off conditionApplied Intelligence10.1007/s10489-021-03000-252:11(12155-12174)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1007/s10489-021-03000-2
Li YZhang SGuo LLiu JWu YWu X(2022)NetNMSP: Nonoverlapping maximal sequential pattern miningApplied Intelligence10.1007/s10489-021-02912-352:9(9861-9884)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1007/s10489-021-02912-3
Wang YWu YLi YYao FFournier-Viger PWu X(2022)Self-adaptive nonoverlapping sequential pattern miningApplied Intelligence10.1007/s10489-021-02763-y52:6(6646-6661)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1007/s10489-021-02763-y
Bu *Yu XHong YJiang T(2021)Low-Quality Error Detection for Noisy Knowledge GraphsJournal of Database Management10.4018/JDM.202110010432:4(48-64)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.4018/JDM.2021100104
Ji SBu CLi LWu X(2021)Local Graph Edge PartitioningACM Transactions on Intelligent Systems and Technology10.1145/346668512:5(1-25)Online publication date: 23-Sep-2021
https://dl.acm.org/doi/10.1145/3466685
Jie FHuang YBai QWu XDemartini GZuccon GCulpepper JHuang ZTong H(2021)HAO UnityProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481991(4725-4729)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3481991
Xue XJiang JZhang WHuang YWu XDemartini GZuccon GCulpepper JHuang ZTong H(2021)A Chinese Knowledge Base Question Answering SystemProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481970(4813-4816)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3481970
Wang HDing SLi YLi XZhang Y(2020)Hierarchical Physician Recommendation via Diversity-enhanced Matrix FactorizationACM Transactions on Knowledge Discovery from Data10.1145/341822715:1(1-17)Online publication date: 7-Dec-2020
https://dl.acm.org/doi/10.1145/3418227
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Cited By

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Intelligence Metasynthesis in Building Business Intelligence Systems

Bringing AI to BI: Enabling Visual Analytics of Unstructured Data in a Modern Business Intelligence Platform

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