Publikation:

Run-Time and Task-Based Performance of Event Detection Techniques for Twitter

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Weiler_0-300914.pdf
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2015

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http://nbn-resolving.de/urn:nbn:de:bsz:352-0-300914
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https://doi.org/10.1007/978-3-319-19069-3_3
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ZDRAVKOVIC, Jelena, ed. and others. Advanced Information Systems Engineering : 27th International Conference, CAiSE 2015, Stockholm, Sweden, June 8-12, 2015, Proceedings. Cham: Springer, 2015, pp. 35-49. Lecture Notes in Computer Science. 9097. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-319-19068-6. Available under: doi: 10.1007/978-3-319-19069-3_3

Zusammenfassung

Twitter’s increasing popularity as a source of up to date news and information about current events has spawned a body of research on event detection techniques for social media data streams. Although all proposed approaches provide some evidence as to the quality of the detected events, none relate this task-based performance to their run-time performance in terms of processing speed or data throughput. In particular, neither a quantitative nor a comparative evaluation of these aspects has been performed to date. In this paper, we study the run-time and task-based performance of several state-of-the-art event detection techniques for Twitter. In order to reproducibly compare run-time performance, our approach is based on a general-purpose data stream management system, whereas task-based performance is automatically assessed based on a series of novel measures.

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Fachgebiet (DDC)
004 Informatik

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Event detection, Performance evaluation, Twitter streams

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27th International Conference, CAiSE 2015, 8. Juni 2015 - 12. Juni 2015, Stockholm
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ISO 690WEILER, Andreas, Michael GROSSNIKLAUS, Marc H. SCHOLL, 2015. Run-Time and Task-Based Performance of Event Detection Techniques for Twitter. 27th International Conference, CAiSE 2015. Stockholm, 8. Juni 2015 - 12. Juni 2015. In: ZDRAVKOVIC, Jelena, ed. and others. Advanced Information Systems Engineering : 27th International Conference, CAiSE 2015, Stockholm, Sweden, June 8-12, 2015, Proceedings. Cham: Springer, 2015, pp. 35-49. Lecture Notes in Computer Science. 9097. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-319-19068-6. Available under: doi: 10.1007/978-3-319-19069-3_3
BibTex
@inproceedings{Weiler2015RunTi-31937,
  year={2015},
  doi={10.1007/978-3-319-19069-3_3},
  title={Run-Time and Task-Based Performance of Event Detection Techniques for Twitter},
  number={9097},
  isbn={978-3-319-19068-6},
  issn={0302-9743},
  publisher={Springer},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={Advanced Information Systems Engineering : 27th International Conference, CAiSE 2015, Stockholm, Sweden, June 8-12, 2015, Proceedings},
  pages={35--49},
  editor={Zdravkovic, Jelena},
  author={Weiler, Andreas and Grossniklaus, Michael and Scholl, Marc H.}
}
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