Skip to main content
SpringerLink
Log in
Book cover

European Conference on Information Retrieval

ECIR 2018: Advances in Information Retrieval pp 801–805Cite as

A Micromodule Approach for Building Real-Time Systems with Python-Based Models: Application to Early Risk Detection of Depression on Social Media

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10772))

Abstract

In this work we introduce Catenae, a new library whose main goal is to provide an easy-to-use solution for scalable real-time deployments with Python micromodules. To demonstrate its potential, we have developed an application that processes social media data and alerts about early signs of depression. The architecture has the following modules: (1) a crawler for extracting users and content, (2) a classifier pipeline that processes new user contents, (3) an HTTP API for alert management and access to users’ submissions, and (4) a web interface.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    https://kafka.apache.org/.

  2. 2.

    https://www.aerospike.com.

  3. 3.

    http://scikit-learn.org.

References

  1. Losada, D.E., Crestani, F.: A test collection for research on depression and language use. In: Fuhr, N., Quaresma, P., Gonçalves, T., Larsen, B., Balog, K., Macdonald, C., Cappellato, L., Ferro, N. (eds.) CLEF 2016. LNCS, vol. 9822, pp. 28–39. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-44564-9_3

    Chapter  Google Scholar 

  2. Losada, D.E., Crestani, F., Parapar, J.: eRISK 2017: CLEF Lab on early risk prediction on the Internet: experimental foundations. In: Jones, G.J.F., Lawless, S., Gonzalo, J., Kelly, L., Goeuriot, L., Mandl, T., Cappellato, L., Ferro, N. (eds.) CLEF 2017. LNCS, vol. 10456, pp. 346–360. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65813-1_30

    Chapter  Google Scholar 

Download references

Acknowledgements

This work has been supported by MINECO (TIN2014-54565-JIN, TIN2015-64282-R), Xunta de Galicia (ED431G/08) and European Regional Development Fund.

Author information

Authors and Affiliations

  1. Centro de Investigación en Tecnoloxías da Información (CiTIUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Rodrigo Martínez-Castaño, Juan C. Pichel & David E. Losada

  2. Faculty of Informatics, Università della Svizzera Italiana (USI), Lugano, Switzerland

    Fabio Crestani

Authors
  1. Rodrigo Martínez-Castaño
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juan C. Pichel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David E. Losada
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fabio Crestani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rodrigo Martínez-Castaño .

Editor information

Editors and Affiliations

  1. Department of Informatics, Systems, and Communication, University of Milano-Bicocca, Milan, Italy

    Gabriella Pasi

  2. LIP6 – UPMC/CNRS, University Pierre et Marie Curie, Paris, France

    Benjamin Piwowarski

  3. University of Glasgow, Glasgow, United Kingdom

    Leif Azzopardi

  4. Technical University of Vienna, Vienna, Austria

    Allan Hanbury

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Martínez-Castaño, R., Pichel, J.C., Losada, D.E., Crestani, F. (2018). A Micromodule Approach for Building Real-Time Systems with Python-Based Models: Application to Early Risk Detection of Depression on Social Media. In: Pasi, G., Piwowarski, B., Azzopardi, L., Hanbury, A. (eds) Advances in Information Retrieval. ECIR 2018. Lecture Notes in Computer Science(), vol 10772. Springer, Cham. https://doi.org/10.1007/978-3-319-76941-7_79

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-76941-7_79

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76940-0

  • Online ISBN: 978-3-319-76941-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation