This paper presents the results based on the research from the integration of advanced methods formerly used in different disciplines and its practical implementation. The integration focusses on content description on the one hand and on computational methods on the other hand. The result of the integration enables advanced knowledge mining workflows, spanning the knowledge of many conceptual knowledge implementations. The integration includes classifications implementing conceptual knowledge, content and classification based verbal descriptions, and methods used with knowledge mining computation. Conceptual knowledge is a rich source of high quality if used appropriately. The value of conceptual knowledge references even increases when considering verbal descriptions, which are available for most implementations. The goal of this research is to integrate conceptual knowledge and associated verbal description in the knowledge mining process. In the context of complex knowledge resources, referencing to multi-disciplinary long-term knowledge, the exploitation can lead to much improved mining results and new insights. The integration goes along with challenges for the creation of resources and design of High End Computation (HEC) workflows.

1.
C.-P.
Rückemann
, “
Comparative Analysis of Data Entities: Knowledge Mining Objects
,” in
Proc. of The 7th INFOCOMP 2017
,
June 25–29, 2017
,
Venice, Italy
(
2017
), ISSN , ISBN 978-1-61208-567-8, http://www.thinkmind.org/index.php?view=instance&instance=INFOCOMP+2017.
2.
Project Gutenberg
,
2017
, http://www.gutenberg.org.
3.
C.-P.
Rückemann
, “
Integrated Computational and Conceptual Solutions for Complex Environmental Information Management
,” in
Proc. ICNAAM 2015
,
Rhodes, Greece
, Vol.
1738
(
AIP Press
,
2016
).
4.
UDCS, Multilingual Universal Decimal Classification Summary
,
2012
,
v. 1.1. The Hague: UDC Consortium (UDCC Publ. No. 088)
, http://www.udcc.org/udcsummary/php/index.php.
5.
Creative Commons Attribution Share Alike 3.0 license
,
2012
, http://creativecommons.org/licenses/by-sa/3.0/.
6.
H. P.
Luhn
,
Keyword-in-context index for technical literature (kwic index
),
American Documentation
,
11
(
4
):
288
295
(
1960
), ISSN: , DOI: .
7.
A.
Rajaraman
and
J. D.
Ullman
, “Chapter 1: Data mining,” in
Mining of Massive Datasets
(
Cambridge University Press
,
2011
), pp.
1
17
, ISBN: 9781139058452, DOI: .
8.
B. J.
Flood
,
Historical Note: The Start of a Stop List at Biological Abstracts
,
Journal of the American Society for Information Science
,
50
(
12
):
1066
(
1999
).
9.
The Perl Programming Language
,
2017
, https://www.perl.org/.
10.
C.
Davison
,
A Study of Recent Earthquakes
(
2008
) Project Gutenberg, EBook-No.: 25062, http://www.gutenberg.org/ebooks/25062, whttp://www.gutenberg.org/cache/epub/25062/pg25062.txt.
This content is only available via PDF.
You do not currently have access to this content.