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Identifying the business and social networks in the domain of production by merging the data from heterogeneous internet sources
ID
Kozjek, Dominik
(
Avtor
),
ID
Vrabič, Rok
(
Avtor
),
ID
Eržen, Gregor
(
Avtor
),
ID
Butala, Peter
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(10,20 MB)
MD5: A67DB703D83DB2CD0A1AA09715E84371
URL - Izvorni URL, za dostop obiščite
https://www.sciencedirect.com/science/article/pii/S0925527318301518
Galerija slik
Izvleček
People, companies, and institutions form networks as part of their technical, economic, and social activities. As a consequence, these networks have an influence on how companies conduct business. Recently, the Internet, professional, and scientific social networks have contributed to the ease and simplicity of the network forming process and the public availability of the corresponding data. We investigate whether useful information about the relationships between individuals, companies, and institutions for the domain of production can be extracted from publicly available, structured and unstructured data that is merged from various Internet sources. We demonstrate that relevant information about the structures of these networks can be obtained by merging publicly available data using a combination of advanced computational methods including web crawling, machine learning, and creating mash-ups of publicly available services. The feasibility and the applicability of the approach are shown for a case in the automotive domain. A potential use case of the resulting data is demonstrated, showing how the approach can be used to find specific skills and expertise for a scientific community consisting of people from industry and academia. The proposed approach can be used for the modelling and analysis of various forms of collaboration between and within businesses. As a tool, it could be used for the purposes of strategic networking, to facilitate the creation of project consortia, to identify competitors and other stakeholders in a certain domain, to pinpoint communication channels, to search for specific expertise, or to identify organisational and social structures within organisations.
Jezik:
Angleški jezik
Ključne besede:
production
,
network
,
network analysis
,
data analytics
,
skill profiling
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FS - Fakulteta za strojništvo
Leto izida:
2018
Št. strani:
Str. 181-191
Številčenje:
Vol. 200
PID:
20.500.12556/RUL-101582
UDK:
004.451.5(045)
ISSN pri članku:
0925-5273
DOI:
10.1016/j.ijpe.2018.03.026
COBISS.SI-ID:
15977243
Datum objave v RUL:
18.06.2018
Število ogledov:
2022
Število prenosov:
1196
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
International journal of production economics
Skrajšan naslov:
Int. j. prod. econ.
Založnik:
Elsevier
ISSN:
0925-5273
COBISS.SI-ID:
11488261
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
proizvodnja
,
mreže
,
analiza mrež
,
analitika podatkov
,
profiliranje kompetenc
Projekti
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P2-0270
Naslov:
Proizvodni sistemi, laserske tehnologije in spajanje materialov
Financer:
Drugi - Drug financer ali več financerjev
Program financ.:
Ministry of Higher Education, Science and Technology of the Republic of Slovenia
Številka projekta:
1000-15-0510
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