A Semantic Web Approach for Visualization-Based News Analytics

Maarten Jongmans; Viorel Milea; Flavius Frasincar

doi:10.1007/978-3-319-08618-7_20

A Semantic Web Approach for Visualization-Based News Analytics

Maarten Jongmans, Viorel Milea^*, Flavius Frasincar

^*Corresponding author for this work

Econometrics

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

1 Citation (Scopus)

Abstract

In order to understand news, dependency patterns between objects in (economic) news items have to be detected. We propose a framework which makes it possible to discover these patterns, and support the observations with statistical analysis. Based on these patterns, alerts can be generated based on emerging news. These alerts can then be used to manage (equity) portfolios. We test our framework based on historical data. The tests show statistically significant results supporting the idea that it is possible to discover such dependency patterns between objects in news items.

Original language	English
Title of host publication	Knowledge Management in Organizations
Subtitle of host publication	9th International Conference, KMO 2014, Proceedings
Publisher	Springer-Verlag
Pages	195-204
Number of pages	10
ISBN (Print)	9783319086170
DOIs	https://doi.org/10.1007/978-3-319-08618-7_20
Publication status	Published - 2014
Event	9th International Conference on Knowledge Management in Organizations, KMO 2014 - Santiago, Chile Duration: 2 Sept 2014 → 5 Sept 2014

Publication series

Series	Lecture Notes in Business Information Processing
Volume	185
ISSN	1865-1348

Conference

Conference	9th International Conference on Knowledge Management in Organizations, KMO 2014
Country/Territory	Chile
City	Santiago
Period	2/09/14 → 5/09/14

Research programs

EUR ESE 32

Access to Document

10.1007/978-3-319-08618-7_20

Cite this

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title = "A Semantic Web Approach for Visualization-Based News Analytics",

abstract = "In order to understand news, dependency patterns between objects in (economic) news items have to be detected. We propose a framework which makes it possible to discover these patterns, and support the observations with statistical analysis. Based on these patterns, alerts can be generated based on emerging news. These alerts can then be used to manage (equity) portfolios. We test our framework based on historical data. The tests show statistically significant results supporting the idea that it is possible to discover such dependency patterns between objects in news items.",

author = "Maarten Jongmans and Viorel Milea and Flavius Frasincar",

year = "2014",

doi = "10.1007/978-3-319-08618-7_20",

language = "English",

isbn = "9783319086170",

series = "Lecture Notes in Business Information Processing",

publisher = "Springer-Verlag",

pages = "195--204",

booktitle = "Knowledge Management in Organizations",

address = "Germany",

note = "9th International Conference on Knowledge Management in Organizations, KMO 2014 ; Conference date: 02-09-2014 Through 05-09-2014",

}

Jongmans, M, Milea, V & Frasincar, F 2014, A Semantic Web Approach for Visualization-Based News Analytics. in Knowledge Management in Organizations: 9th International Conference, KMO 2014, Proceedings. Springer-Verlag, Lecture Notes in Business Information Processing, vol. 185, pp. 195-204, 9th International Conference on Knowledge Management in Organizations, KMO 2014, Santiago, Chile, 2/09/14. https://doi.org/10.1007/978-3-319-08618-7_20

A Semantic Web Approach for Visualization-Based News Analytics. / Jongmans, Maarten; Milea, Viorel; Frasincar, Flavius.
Knowledge Management in Organizations: 9th International Conference, KMO 2014, Proceedings. Springer-Verlag, 2014. p. 195-204 (Lecture Notes in Business Information Processing, Vol. 185).

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

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AU - Milea, Viorel

AU - Frasincar, Flavius

PY - 2014

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N2 - In order to understand news, dependency patterns between objects in (economic) news items have to be detected. We propose a framework which makes it possible to discover these patterns, and support the observations with statistical analysis. Based on these patterns, alerts can be generated based on emerging news. These alerts can then be used to manage (equity) portfolios. We test our framework based on historical data. The tests show statistically significant results supporting the idea that it is possible to discover such dependency patterns between objects in news items.

AB - In order to understand news, dependency patterns between objects in (economic) news items have to be detected. We propose a framework which makes it possible to discover these patterns, and support the observations with statistical analysis. Based on these patterns, alerts can be generated based on emerging news. These alerts can then be used to manage (equity) portfolios. We test our framework based on historical data. The tests show statistically significant results supporting the idea that it is possible to discover such dependency patterns between objects in news items.

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DO - 10.1007/978-3-319-08618-7_20

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SN - 9783319086170

T3 - Lecture Notes in Business Information Processing

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A Semantic Web Approach for Visualization-Based News Analytics

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