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CEUR-WS-LOD: Conversion of CEUR-WS Workshops to Linked Data. / Kolchin, Maxim; Cherny, Eugene; Kozlov, Fedor; Shipilo, Alexander; Kovriguina, Liubov.

в: Communications in Computer and Information Science, Том 548, 2015, стр. 142-152.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

Harvard

Kolchin, M, Cherny, E, Kozlov, F, Shipilo, A & Kovriguina, L 2015, 'CEUR-WS-LOD: Conversion of CEUR-WS Workshops to Linked Data', Communications in Computer and Information Science, Том. 548, стр. 142-152. https://doi.org/10.1007/978-3-319-25518-7_12

APA

Kolchin, M., Cherny, E., Kozlov, F., Shipilo, A., & Kovriguina, L. (2015). CEUR-WS-LOD: Conversion of CEUR-WS Workshops to Linked Data. Communications in Computer and Information Science, 548, 142-152. https://doi.org/10.1007/978-3-319-25518-7_12

Vancouver

Kolchin M, Cherny E, Kozlov F, Shipilo A, Kovriguina L. CEUR-WS-LOD: Conversion of CEUR-WS Workshops to Linked Data. Communications in Computer and Information Science. 2015;548:142-152. https://doi.org/10.1007/978-3-319-25518-7_12

Author

Kolchin, Maxim ; Cherny, Eugene ; Kozlov, Fedor ; Shipilo, Alexander ; Kovriguina, Liubov. / CEUR-WS-LOD: Conversion of CEUR-WS Workshops to Linked Data. в: Communications in Computer and Information Science. 2015 ; Том 548. стр. 142-152.

BibTeX

@article{19a25a042e1a422b92abb1625c4e824e,
title = "CEUR-WS-LOD: Conversion of CEUR-WS Workshops to Linked Data",
abstract = "CEUR-WS.org is a well-known place for publishing proceedings of workshops and very popular among Computer Science community. Because of that it{\textquoteright}s an interesting source for different kinds of analytics, e.g. measurement of workshop series popularity or person{\textquoteright}s contribution to the field by organizing workshops and etc. For realizing an insightful and effective analytics one needs to combine information from different places that can supplement each other. And this brings a lot of challenges which can be mitigated by using Semantic Web technologies.",
keywords = "Information extraction RDF Semantic publishing Linked open data CEUR-WS",
author = "Maxim Kolchin and Eugene Cherny and Fedor Kozlov and Alexander Shipilo and Liubov Kovriguina",
year = "2015",
doi = "10.1007/978-3-319-25518-7_12",
language = "English",
volume = "548",
pages = "142--152",
journal = "Communications in Computer and Information Science",
issn = "1865-0929",
publisher = "Springer Nature",

}

RIS

TY - JOUR

T1 - CEUR-WS-LOD: Conversion of CEUR-WS Workshops to Linked Data

AU - Kolchin, Maxim

AU - Cherny, Eugene

AU - Kozlov, Fedor

AU - Shipilo, Alexander

AU - Kovriguina, Liubov

PY - 2015

Y1 - 2015

N2 - CEUR-WS.org is a well-known place for publishing proceedings of workshops and very popular among Computer Science community. Because of that it’s an interesting source for different kinds of analytics, e.g. measurement of workshop series popularity or person’s contribution to the field by organizing workshops and etc. For realizing an insightful and effective analytics one needs to combine information from different places that can supplement each other. And this brings a lot of challenges which can be mitigated by using Semantic Web technologies.

AB - CEUR-WS.org is a well-known place for publishing proceedings of workshops and very popular among Computer Science community. Because of that it’s an interesting source for different kinds of analytics, e.g. measurement of workshop series popularity or person’s contribution to the field by organizing workshops and etc. For realizing an insightful and effective analytics one needs to combine information from different places that can supplement each other. And this brings a lot of challenges which can be mitigated by using Semantic Web technologies.

KW - Information extraction RDF Semantic publishing Linked open data CEUR-WS

U2 - 10.1007/978-3-319-25518-7_12

DO - 10.1007/978-3-319-25518-7_12

M3 - Article

VL - 548

SP - 142

EP - 152

JO - Communications in Computer and Information Science

JF - Communications in Computer and Information Science

SN - 1865-0929

ER -

ID: 5818313