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Workshop on Mining Data for Financial Applications

International Workshop on Personal Analytics and Privacy

MIDAS 2018, PAP 2018: ECML PKDD 2018 Workshops pp 103–107Cite as

A Web Crawling Environment to Support Financial Strategies and Trend Correlation

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 11054)

Abstract

We provide an overview on the development and the integration in ENEAGRID of a web crawling tool to retrieve data from the Web, manage and display it, and extract relevant information. We collected all these instruments in a collaborative environment called Web Crawling Virtual Laboratory, offering a GUI to operate remotely. Finally, we describe an ongoing activity on semantic crawling and data analysis to discover trends and correlations in finance.

Keywords

  • Web crawling
  • Big data
  • Machine learning
  • Market trends

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Fig. 1.

Notes

  1. 1.

    http://www.afs.enea.it/project/webcrawl/.

  2. 2.

    https://github.com/apanimesh061/VaderSentimentJava.

References

  1. Boldi, P., Marino, A., Santini, M., Vigna, S.: BUbiNG: massive crawling for the masses. CoRR abs/1601.06919 (2016)

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  2. Ponti, G. et al.: The role of medium size facilities in the HPC ecosystem: the case of the new CRESCO4 cluster integrated in the ENEAGRID infrastructure, pp. 1030–1033 (2014)

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  3. Santomauro, G., et al.: A collaborative environment for web crawling and web data analysis in ENEAGRID. In: DATA 2017, 24–26 July 2017, Madrid, Spain, pp. 287–295 (2017)

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Acknowledgements

The computing resources and the related technical support used for this work have been provided by ENEAGRID/CRESCO High Performance Computing infrastructure and its staff [2]. ENEAGRID/CRESCO High Performance Computing infrastructure is funded by ENEA, the Italian National Agency for New Technologies, Energy and Sustainable Economic Development and by Italian and European research programmes, see http://www.cresco.enea.it/english for information.

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Authors and Affiliations

  1. ENEA - ICT Division - Portici Research Center (NA), Portici, Italy

    Giovanni Ponti, Giuseppe Santomauro, Fiorenzo Ambrosino, Giovanni Bracco, Matteo De Rosa, Agostino Funel, Dante Giammattei, Guido Guarnieri & Silvio Migliori

  2. Accenture Technology Solutions s.r.l. - Assago (MI), Milan, Italy

    Antonio Colavincenzo

Authors
  1. Giovanni Ponti
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  2. Giuseppe Santomauro
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  3. Fiorenzo Ambrosino
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  4. Giovanni Bracco
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  5. Antonio Colavincenzo
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  6. Matteo De Rosa
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  7. Agostino Funel
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  8. Dante Giammattei
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  9. Guido Guarnieri
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  10. Silvio Migliori
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Corresponding author

Correspondence to Giovanni Ponti .

Editor information

Editors and Affiliations

  1. IBM Research - Ireland, Dublin, Ireland

    Carlos Alzate

  2. KDD Lab, University of Pisa, Pisa, Italy

    Anna Monreale

  3. University of Turin, Turin, Italy

    Livio Bioglio

  4. R&D Department, UniCredit, Milan, Italy

    Valerio Bitetta

  5. R&D Department, UniCredit, Rome, Italy

    Dr. Ilaria Bordino

  6. IMT School for Advanced Studies Lucca, Lucca, Italy

    Guido Caldarelli

  7. R&D Department, UniCredit, Milan, Italy

    Andrea Ferretti

  8. KDD Lab, University of Pisa, Pisa, Italy

    Riccardo Guidotti

  9. R&D Department, UniCredit, Rome, Italy

    Francesco Gullo

  10. R&D Department, UniCredit, Milan, Italy

    Stefano Pascolutti

  11. Department of Computer Science, University of Turin, Turin, Italy

    Prof. Dr. Ruggero G. Pensa

  12. National Institute of Applied Science, Université de Lyon, Lyon, France

    Celine Robardet

  13. IMT School Advanced Studies Lucca, Lucca, Italy

    Dr. Tiziano Squartini

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Ponti, G. et al. (2019). A Web Crawling Environment to Support Financial Strategies and Trend Correlation. In: , et al. ECML PKDD 2018 Workshops. MIDAS PAP 2018 2018. Lecture Notes in Computer Science(), vol 11054. Springer, Cham. https://doi.org/10.1007/978-3-030-13463-1_8

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  • DOI: https://doi.org/10.1007/978-3-030-13463-1_8

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