Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems - An Approach

Markus Jäger; Trong Nhan Phan; Christian Huber; Josef Küng

doi:10.1007/978-3-319-48057-2_1

Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems - An Approach

Markus Jäger
, Trong Nhan Phan
, Christian Huber
, Josef Küng

Institute for Application-oriented Knowledge Processing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

The origin of data (data provenance), should always be measured or categorized within the context of trusting the source of data. Can we be sure that the information we receive is trustworthy and reliable? Is the source trustable? Is the data certain? And how important is the received data the our current and next step of processing? We face these questions in the context of knowledge processing systems by developing a convenient approach to bring all these questions and values – trustability, certainty, importance – into a computable, measurable, and comparable way of expression. Not yet facing the question “How to compute trust or certainty?”, but how to incorporate and process their measured values in knowledge processing systems to receive a representative view on the whole environment and its output.

Original language	English
Title of host publication	Future Data and Security Engineering: Third International Conference, FDSE 2016, Can Tho City, Vietnam, November 23-25, 2016, Proceedings
Editors	Tran Khanh Dang, Nam Thoai, Roland Wagner, Josef Küng, Erich Neuhold, Makoto Takizawa
Place of Publication	Cham
Publisher	Springer International Publishing
Pages	3-19
Number of pages	17
Volume	3
ISBN (Print)	978-3-319-48057-2
DOIs	https://doi.org/10.1007/978-3-319-48057-2_1
Publication status	Published - Nov 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10018 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Fields of science

102001 Artificial intelligence
102006 Computer supported cooperative work (CSCW)
102010 Database systems
102014 Information design
102015 Information systems
102016 IT security
102022 Software development
102025 Distributed systems
102033 Data mining
502007 E-commerce
505002 Data protection
509018 Knowledge management

JKU Focus areas

Computation in Informatics and Mathematics

Access to Document

10.1007/978-3-319-48057-2_1

Cite this

Jäger, M., Phan, T. N., Huber, C., & Küng, J. (2016). Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems - An Approach. In T. K. Dang, N. Thoai, R. Wagner, J. Küng, E. Neuhold, & M. Takizawa (Eds.), Future Data and Security Engineering: Third International Conference, FDSE 2016, Can Tho City, Vietnam, November 23-25, 2016, Proceedings (Vol. 3, pp. 3-19). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10018 LNCS). Springer International Publishing. https://doi.org/10.1007/978-3-319-48057-2_1

Jäger, Markus ; Phan, Trong Nhan ; Huber, Christian et al. / Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems - An Approach. Future Data and Security Engineering: Third International Conference, FDSE 2016, Can Tho City, Vietnam, November 23-25, 2016, Proceedings. editor / Tran Khanh Dang ; Nam Thoai ; Roland Wagner ; Josef Küng ; Erich Neuhold ; Makoto Takizawa. Vol. 3 Cham : Springer International Publishing, 2016. pp. 3-19 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The origin of data (data provenance), should always be measured or categorized within the context of trusting the source of data. Can we be sure that the information we receive is trustworthy and reliable? Is the source trustable? Is the data certain? And how important is the received data the our current and next step of processing? We face these questions in the context of knowledge processing systems by developing a convenient approach to bring all these questions and values {\textendash} trustability, certainty, importance {\textendash} into a computable, measurable, and comparable way of expression. Not yet facing the question {\textquotedblleft}How to compute trust or certainty?{\textquotedblright}, but how to incorporate and process their measured values in knowledge processing systems to receive a representative view on the whole environment and its output.",

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year = "2016",

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Jäger, M, Phan, TN, Huber, C & Küng, J 2016, Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems - An Approach. in TK Dang, N Thoai, R Wagner, J Küng, E Neuhold & M Takizawa (eds), Future Data and Security Engineering: Third International Conference, FDSE 2016, Can Tho City, Vietnam, November 23-25, 2016, Proceedings. vol. 3, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10018 LNCS, Springer International Publishing, Cham, pp. 3-19. https://doi.org/10.1007/978-3-319-48057-2_1

Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems - An Approach. / Jäger, Markus; Phan, Trong Nhan; Huber, Christian et al.
Future Data and Security Engineering: Third International Conference, FDSE 2016, Can Tho City, Vietnam, November 23-25, 2016, Proceedings. ed. / Tran Khanh Dang; Nam Thoai; Roland Wagner; Josef Küng; Erich Neuhold; Makoto Takizawa. Vol. 3 Cham: Springer International Publishing, 2016. p. 3-19 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10018 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

TY - GEN

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AB - The origin of data (data provenance), should always be measured or categorized within the context of trusting the source of data. Can we be sure that the information we receive is trustworthy and reliable? Is the source trustable? Is the data certain? And how important is the received data the our current and next step of processing? We face these questions in the context of knowledge processing systems by developing a convenient approach to bring all these questions and values – trustability, certainty, importance – into a computable, measurable, and comparable way of expression. Not yet facing the question “How to compute trust or certainty?”, but how to incorporate and process their measured values in knowledge processing systems to receive a representative view on the whole environment and its output.

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Jäger M, Phan TN, Huber C, Küng J. Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems - An Approach. In Dang TK, Thoai N, Wagner R, Küng J, Neuhold E, Takizawa M, editors, Future Data and Security Engineering: Third International Conference, FDSE 2016, Can Tho City, Vietnam, November 23-25, 2016, Proceedings. Vol. 3. Cham: Springer International Publishing. 2016. p. 3-19. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-48057-2_1

Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems - An Approach

Abstract

Publication series

Fields of science

JKU Focus areas

Access to Document

Other files and links

CLAFIS - Crop, Livestock and Forests Integrated System for Intelligent Automation, Processing and Control

Cite this

Incorporating Trust, Certainty and Importance of Information into Knowledge Processing Systems - An Approach

Abstract

Publication series

Fields of science

JKU Focus areas

Access to Document

Other files and links

Projects

CLAFIS - Crop, Livestock and Forests Integrated System for Intelligent Automation, Processing and Control

Cite this