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Authors: Ying Zhao 1 ; Charles Zhou 2 and Jennie K. Bellonio 1

Affiliations: 1 Naval Postgraduate School, Monterey, CA and U.S.A. ; 2 Quantum Intelligence, Inc., Cupertino, CA and U.S.A.

ISBN: 978-989-758-330-8

ISSN: 2184-3228

Keyword(s): Lexical Link Analysis, Crowd-Sourcing, Game Theory, Big Data, Unsupervised Learning, Nash Equilibrium, Social Welfare, Pareto Superior, Pareto Efficient

Related Ontology Subjects/Areas/Topics: Applications and Case-studies ; Artificial Intelligence ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Health Engineering and Technology Applications ; Knowledge Engineering and Ontology Development ; Knowledge Representation ; Knowledge-Based Systems ; Symbolic Systems

Abstract: We demonstrated a machine learning and artificial intelligence method, i.e., lexical link analysis (LLA) to discover innovative ideas from big data. LLA is an unsupervised machine learning paradigm that does not require manually labeled training data. New value metrics are defined based on LLA and game theory. In this paper, we show the value metrics generated from LLA in a use case of an internet game and crowd-sourcing. We show the results from LLA are validated and correlated with the ground truth. The LLA value metrics can be used to select high-value information for a wide range of applications.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Zhao, Y.; Zhou, C. and Bellonio, J. (2018). New Value Metrics using Unsupervised Machine Learning, Lexical Link Analysis and Game Theory for Discovering Innovation from Big Data and Crowd-sourcing. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD, ISBN 978-989-758-330-8; ISSN 2184-3228, pages 327-334. DOI: 10.5220/0006959403270334

@conference{keod18,
author={Ying Zhao. and Charles Zhou. and Jennie K. Bellonio.},
title={New Value Metrics using Unsupervised Machine Learning, Lexical Link Analysis and Game Theory for Discovering Innovation from Big Data and Crowd-sourcing},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD,},
year={2018},
pages={327-334},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006959403270334},
isbn={978-989-758-330-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD,
TI - New Value Metrics using Unsupervised Machine Learning, Lexical Link Analysis and Game Theory for Discovering Innovation from Big Data and Crowd-sourcing
SN - 978-989-758-330-8
IS - 2184-3228
AU - Zhao, Y.
AU - Zhou, C.
AU - Bellonio, J.
PY - 2018
SP - 327
EP - 334
DO - 10.5220/0006959403270334

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