Community building based on semantic time series

Bojan Božić; Werner Winiwarter

doi:10.1145/2428736.2428770

Community building based on semantic time series

Bojan Božić
, Werner Winiwarter

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

Abstract

In this paper, we present a new approach of time series enrichment with semantics, and the usage of this technology for building various kinds of communities interested in time series data. The paper shows the problem of assigning time series data to the right party of interest and why this problem could not be solved so far. We demonstrate a new way of processing semantic time series and the consequential ability of addressing and creating target communities. The combination of time series processing and Semantic Web technologies leads us to a new powerful method of data processing and data generation, which offers completely new opportunities to the expert user.

Original language	English
Title of host publication	14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 - Proceedings
Pages	213-222
Number of pages	10
DOIs	https://doi.org/10.1145/2428736.2428770
Publication status	Published - 2012
Event	14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 - Bali, Indonesia Duration: 3 Dec 2012 → 5 Dec 2012

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012
Country/Territory	Indonesia
City	Bali
Period	3/12/12 → 5/12/12

Keywords

community building
semantic web
time series processing

Access to Document

10.1145/2428736.2428770

Cite this

@inproceedings{ade35fa78fb0479695dce6127a5625fa,

title = "Community building based on semantic time series",

abstract = "In this paper, we present a new approach of time series enrichment with semantics, and the usage of this technology for building various kinds of communities interested in time series data. The paper shows the problem of assigning time series data to the right party of interest and why this problem could not be solved so far. We demonstrate a new way of processing semantic time series and the consequential ability of addressing and creating target communities. The combination of time series processing and Semantic Web technologies leads us to a new powerful method of data processing and data generation, which offers completely new opportunities to the expert user.",

keywords = "community building, semantic web, time series processing",

author = "Bojan Bo{\v z}i{\'c} and Werner Winiwarter",

year = "2012",

doi = "10.1145/2428736.2428770",

language = "English",

isbn = "9781450313063",

series = "ACM International Conference Proceeding Series",

pages = "213--222",

booktitle = "14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 - Proceedings",

note = "14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 ; Conference date: 03-12-2012 Through 05-12-2012",

}

Božić, B & Winiwarter, W 2012, Community building based on semantic time series. in 14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 - Proceedings. ACM International Conference Proceeding Series, pp. 213-222, 14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012, Bali, Indonesia, 3/12/12. https://doi.org/10.1145/2428736.2428770

Community building based on semantic time series. / Božić, Bojan; Winiwarter, Werner.
14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 - Proceedings. 2012. p. 213-222 (ACM International Conference Proceeding Series).

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

TY - GEN

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AU - Winiwarter, Werner

PY - 2012

Y1 - 2012

N2 - In this paper, we present a new approach of time series enrichment with semantics, and the usage of this technology for building various kinds of communities interested in time series data. The paper shows the problem of assigning time series data to the right party of interest and why this problem could not be solved so far. We demonstrate a new way of processing semantic time series and the consequential ability of addressing and creating target communities. The combination of time series processing and Semantic Web technologies leads us to a new powerful method of data processing and data generation, which offers completely new opportunities to the expert user.

AB - In this paper, we present a new approach of time series enrichment with semantics, and the usage of this technology for building various kinds of communities interested in time series data. The paper shows the problem of assigning time series data to the right party of interest and why this problem could not be solved so far. We demonstrate a new way of processing semantic time series and the consequential ability of addressing and creating target communities. The combination of time series processing and Semantic Web technologies leads us to a new powerful method of data processing and data generation, which offers completely new opportunities to the expert user.

KW - community building

KW - semantic web

KW - time series processing

UR - https://www.scopus.com/pages/publications/84873365913

U2 - 10.1145/2428736.2428770

DO - 10.1145/2428736.2428770

M3 - Conference contribution

AN - SCOPUS:84873365913

SN - 9781450313063

T3 - ACM International Conference Proceeding Series

SP - 213

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BT - 14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 - Proceedings

T2 - 14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012

Y2 - 3 December 2012 through 5 December 2012

ER -

Community building based on semantic time series

Abstract

Publication series

Conference

Keywords

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