Skip to main content
SpringerLink
Log in

The Distiller Framework: Current State and Future Challenges

  • Conference paper
  • First Online:
Book cover Digital Libraries and Multimedia Archives (IRCDL 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 806))

Included in the following conference series:

Abstract

In 2015, we introduced a novel knowledge extraction framework called the Distiller Framework, with the goal of offering the research community a flexible, multilingual information extraction framework [3]. Two years later, the project has significantly evolved, by supporting more languages and many machine learning algorithms. In this paper we present the current design of the framework and some of its applications.

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

Access this chapter

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Institutional subscriptions

Notes

  1. 1.

    http://www.nzdl.org/Kea/download.html.

  2. 2.

    https://github.com/aneesha/RAKE.

  3. 3.

    https://github.com/boudinfl/pke.

  4. 4.

    https://github.com/zelandiya/maui.

  5. 5.

    http://opennlp.apache.org.

References

  1. Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., Zheng, X.: TensorFlow: Large-scale machine learning on heterogeneous systems (2015). http://tensorflow.org/

  2. Basaldella, M., Chiaradia, G., Tasso, C.: Evaluating anaphora and coreference resolution to improve automatic keyphrase extraction. In: COLING 2016, 26th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, Osaka, Japan, 11–16 December 2016, pp. 804–814 (2016)

    Google Scholar 

  3. Basaldella, M., De Nart, D., Tasso, C.: Introducing distiller: a unifying framework for knowledge extraction. In: Proceedings of 1st AI*IA Workshop on Intelligent Techniques At Libraries and Archives co-located with XIV Conference of the Italian Association for Artificial Intelligence (AI*IA 2015). Associazione Italiana per l’Intelligenza Artificiale (2015)

    Google Scholar 

  4. Basaldella, M., Furrer, L., Colic, N., Ellendorff, T., Tasso, C., Rinaldi, F.: Using a hybrid approach for entity recognition in the biomedical domain. In: Proceedings of the 7th International Symposium on Semantic Mining in Biomedicine, SMBM 2016, Potsdam, Germany, 4–5 August 2016, pp. 11–19 (2016)

    Google Scholar 

  5. Basaldella, M., Helmy, M., Antolli, E., Popescu, M.H., Serra, G., Tasso, C.: Exploiting and evaluating a supervised, multilanguage keyphrase extraction pipeline for under-resourced languages. In: Recent Advances in Natural Language Processing 2017 (RANLP 2017), Varna (Bulgaria), 4–6 September 2017

    Google Scholar 

  6. Bojar, O., Chatterjee, R., Federmann, C., Graham, Y., Haddow, B., Huck, M., Jimeno Yepes, A., Koehn, P., Logacheva, V., Monz, C., Negri, M., Neveol, A., Neves, M., Popel, M., Post, M., Rubino, R., Scarton, C., Specia, L., Turchi, M., Verspoor, K., Zampieri, M.: Findings of the 2016 conference on machine translation. In: Proceedings of the First Conference on Machine Translation, pp. 131–198. Association for Computational Linguistics, Berlin, August 2016

    Google Scholar 

  7. Bojar, O., Chatterjee, R., Federmann, C., Haddow, B., Huck, M., Hokamp, C., Koehn, P., Logacheva, V., Monz, C., Negri, M., Post, M., Scarton, C., Specia, L., Turchi, M.: Findings of the 2015 workshop on statistical machine translation. In: Proceedings of the Tenth Workshop on Statistical Machine Translation, pp. 1–46. Association for Computational Linguistics, Lisbon, September 2015

    Google Scholar 

  8. Boudin, F.: pke: an open source python-based keyphrase extraction toolkit. In: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations. pp. 69–73. The COLING 2016 Organizing Committee, Osaka, December 2016

    Google Scholar 

  9. Bougouin, A., Boudin, F., Daille, B.: Topicrank: graph-based topic ranking for keyphrase extraction. In: Sixth International Joint Conference on Natural Language Processing, IJCNLP 2013, Nagoya, Japan, 14–18 October 2013, pp. 543–551 (2013)

    Google Scholar 

  10. De Nart, D., Tasso, C.: A domain independent double layered approach to keyphrase generation. In: WEBIST 2014 - Proceedings of the 10th International Conference on Web Information Systems and Technologies, pp. 305–312. SciTePress (2014)

    Google Scholar 

  11. Degl’Innocenti, D., De Nart, D., Tasso, C.: A new multi-lingual knowledge-base approach to keyphrase extraction for the Italian language. In: Proceedings of the 6th International Conference on Knowledge Discovery and Information Retrieval, pp. 78–85. SciTePress (2014)

    Google Scholar 

  12. Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns: Elements of Reusable Object-oriented Software. Addison-Wesley Longman Publishing Co., Inc., Boston (1995)

    MATH  Google Scholar 

  13. Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press (2016). http://www.deeplearningbook.org

  14. Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S.J., McClosky, D.: The Stanford CoreNLP natural language processing toolkit. In: Association for Computational Linguistics (ACL) System Demonstrations, pp. 55–60 (2014)

    Google Scholar 

  15. Medelyan, O., Frank, E., Witten, I.H.: Human-competitive tagging using automatic keyphrase extraction. In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, EMNLP 2009, vol. 3, pp. 1318–1327. Association for Computational Linguistics, Stroudsburg (2009)

    Google Scholar 

  16. Nguyen, T.D., Luong, M.: WINGNUS: keyphrase extraction utilizing document logical structure. In: Proceedings of the 5th International Workshop on Semantic Evaluation, SemEval@ACL 2010, Uppsala University, Uppsala, Sweden, 15–16 July 2010, pp. 166–169 (2010). http://aclweb.org/anthology/S/S10/S10-1035.pdf

  17. Okazaki, N.: Crfsuite: a fast implementation of conditional random fields (crfs) (2007). http://www.chokkan.org/software/crfsuite/

  18. Porter, M.F.: An Algorithm for suffix stripping. In: Readings in Information Retrieval, pp. 313–316. Morgan Kaufmann Publishers Inc., San Francisco (1997)

    Google Scholar 

  19. Pudota, N., Dattolo, A., Baruzzo, A., Ferrara, F., Tasso, C.: Automatic keyphrase extraction and ontology mining for content-based tag recommendation. Int. J. Intell. Syst. 25(12), 1158–1186 (2010)

    Article  MATH  Google Scholar 

  20. Rinaldi, F.: The ontogene system: an advanced information extraction application for biological literature. EMBnet.journal 18(B) (2012)

    Google Scholar 

  21. Rose, S., Engel, D., Cramer, N., Cowley, W.: Automatic keyword extraction from individual documents. In: Text Mining, pp. 1–20 (2010)

    Google Scholar 

  22. Russell, I., Markov, Z.: An introduction to the weka data mining system (abstract only). In: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, Seattle, WA, USA, 8–11 March 2017, p. 742 (2017)

    Google Scholar 

  23. dos Santos, C., Guimarães, V.: Boosting named entity recognition with neural character embeddings. In: Proceedings of the Fifth Named Entity Workshop, pp. 25–33. Association for Computational Linguistics, Beijing, July 2015

    Google Scholar 

  24. Witten, I.H., Paynter, G.W., Frank, E., Gutwin, C., Nevill-Manning, C.G.: Kea: practical automatic keyphrase extraction. In: Proceedings of the Fourth ACM Conference on Digital Libraries, pp. 254–255. ACM (1999)

    Google Scholar 

  25. Zhang, Q., Wang, Y., Gong, Y., Huang, X.: Keyphrase extraction using deep recurrent neural networks on Twitter. In: Proceedings of Conference on Empirical Methods in Natural Language Processing (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Laboratorio di Intelligenza Artificiale, Università degli Studi di Udine, Via delle Scienze 208, Udine, Italy

    Marco Basaldella, Giuseppe Serra & Carlo Tasso

Authors
  1. Marco Basaldella
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Giuseppe Serra
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Carlo Tasso
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marco Basaldella .

Editor information

Editors and Affiliations

  1. University of Udine, Udine, Italy

    Giuseppe Serra

  2. University of Udine, Udine, Italy

    Carlo Tasso

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Basaldella, M., Serra, G., Tasso, C. (2018). The Distiller Framework: Current State and Future Challenges. In: Serra, G., Tasso, C. (eds) Digital Libraries and Multimedia Archives. IRCDL 2018. Communications in Computer and Information Science, vol 806. Springer, Cham. https://doi.org/10.1007/978-3-319-73165-0_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-73165-0_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73164-3

  • Online ISBN: 978-3-319-73165-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation