About this paper

Appears in:
Pages: 3972-3977
Publication year: 2014
ISBN: 978-84-617-2484-0
ISSN: 2340-1095

Conference name: 7th International Conference of Education, Research and Innovation
Dates: 17-19 November, 2014
Location: Seville, Spain

PROKEX – INTEGRATED PLATFORM FOR PROCESS-BASED KNOWLEDGE EXTRACTION

G. Neusch, A. Gábor

Corvinno (HUNGARY)
Complex organisations use to model and manage their processes using business process management tools. These applications help to describe the organisational processes, together with the required information and other resources (amongst other human resources) needed to perform each activity.

Business processes are defined as sequence of activities. From the Human Resource Management view it is required to define unambiguously, who, where, when, with what competencies, and why is responsible for the execution of each activity in bridging the organisational model and the process model. BPM is the articulation of the hidden knowledge in the context of production, services, and organisational activities. The relevant and internalized knowledge is embedded and strongly related to the roles as the element of the organisational structure. In dynamic environment both the roles and required competencies are changing, therefore the knowledge elicitation, articulation cannot go independently from the permanently updated business process model; hence the business process model is one of the most important ingredients of the knowledge to be captured.
The ProKEX solution is to extract the knowledge from information stored in the process model in order to articulate, externalize and transfer (re-use). The expected impact is the preservation and efficient management of corporate intellectual capital, a better return on investment in human capital, that will lead to the more efficient execution of processes and consequently higher revenues.

The goal of the ProKEX project is to develop a solution to extract, organize and preserve knowledge embedded in organisational processes in order to:
(1) enrich organisational knowledge base in a systematic and controlled way
(2) support employees to easily acquire their job role specific knowledge,
(3) help to govern and plan the human capital investment.

In order to achieve this goal a complex IT solution and method is developed which integrates:
a) organisational process management tool,
b) learning management tool,
c) real-time data monitoring and processing tool and
d) data and text mining tools for developing knowledge base (domain ontology) and the interfaces which are responsible for the communication between these components.

On-the job training is put on the focus, since it increases productivity at the firm level and is also a source of innovation and therefore long-term competitiveness of firms.

The novelty is based on the connection between process model and corporate knowledge base, where the process structure is used for building up the knowledge structure. The main innovation lies in new algorithms for the extraction and integration of the static and dynamic process knowledge and a novel integration architecture that enables smoothly integration of the eLearning methods in the process execution models.
@InProceedings{NEUSCH2014PRO,
author = {Neusch, G. and G{\'{a}}bor, A.},
title = {PROKEX – INTEGRATED PLATFORM FOR PROCESS-BASED KNOWLEDGE EXTRACTION},
series = {7th International Conference of Education, Research and Innovation},
booktitle = {ICERI2014 Proceedings},
isbn = {978-84-617-2484-0},
issn = {2340-1095},
publisher = {IATED},
location = {Seville, Spain},
month = {17-19 November, 2014},
year = {2014},
pages = {3972-3977}}
TY - CONF
AU - G. Neusch AU - A. Gábor
TI - PROKEX – INTEGRATED PLATFORM FOR PROCESS-BASED KNOWLEDGE EXTRACTION
SN - 978-84-617-2484-0/2340-1095
PY - 2014
Y1 - 17-19 November, 2014
CI - Seville, Spain
JO - 7th International Conference of Education, Research and Innovation
JA - ICERI2014 Proceedings
SP - 3972
EP - 3977
ER -
G. Neusch, A. Gábor (2014) PROKEX – INTEGRATED PLATFORM FOR PROCESS-BASED KNOWLEDGE EXTRACTION, ICERI2014 Proceedings, pp. 3972-3977.
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