Skip to main content
SpringerLink
Log in

A New Domain Independent Keyphrase Extraction System

  • Conference paper
Digital Libraries (IRCDL 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 91))

Included in the following conference series:

Abstract

In this paper we present a keyphrase extraction system that can extract potential phrases from a single document in an unsupervised, domain-independent way. We extract word n-grams from input document. We incorporate linguistic knowledge (i.e., part-of-speech tags), and statistical information (i.e., frequency, position, lifespan) of each n-gram in defining candidate phrases and their respective feature sets. The proposed approach can be applied to any document, however, in order to know the effectiveness of the system for digital libraries, we have carried out the evaluation on a set of scientific documents, and compared our results with current keyphrase extraction systems.

The authors acknowledge the financial support of the Italian Ministry of Education, University and Research (MIUR) within the FIRB project number RBIN04M8S8.

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Barker, K., Cornacchia, N.: Using noun phrase heads to extract document keyphrases. In: Hamilton, H.J. (ed.) Canadian AI 2000. LNCS (LNAI), vol. 1822, pp. 40–52. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  2. Baruzzo, A., Dattolo, A., Pudota, N., Tasso, C.: A general framework for personalized text classification and annotation. In: Houben, G.-J., McCalla, G., Pianesi, F., Zancanaro, M. (eds.) UMAP 2009. LNCS, vol. 5535, pp. 31–39. Springer, Heidelberg (2009)

    Google Scholar 

  3. Baruzzo, A., Dattolo, A., Pudota, N., Tasso, C.: Recommending new tags using domain-ontologies. In: IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, vol. 3, pp. 409–412. IEEE, Milan (2009)

    Chapter  Google Scholar 

  4. Berger, A.L., Mittal, V.O.: Ocelot: a system for summarizing web pages. In: Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval, pp. 144–151. ACM, New York (2000)

    Google Scholar 

  5. Bracewell, D.B., Ren, F., Kuroiwa, S.: Multilingual single document keyword extraction for information retrieval. In: Proceedings of the 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, Wuhan, pp. 517–522 (2005)

    Google Scholar 

  6. Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks 30(1-7), 107–117 (1998)

    Google Scholar 

  7. Dattolo, A., Ferrara, F., Tasso, C.: Supporting personalized user concept spaces and recommendations for a publication sharing system. In: Houben, G.-J., McCalla, G., Pianesi, F., Zancanaro, M. (eds.) UMAP 2009. LNCS, vol. 5535, pp. 325–330. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  8. D’Avanzo, E., Magnini, B., Vallin, A.: Keyphrase extraction for summarization purposes: the lake system at duc2004. In: DUC Workshop, Human Language Technology conference/North American chapter of the Association for Computational Linguistics annual meeting, Boston, USA (2004)

    Google Scholar 

  9. Frank, E., Paynter, G.W., Witten, I.H., Gutwin, C., Nevill-Manning, C.G.: Domain-specific keyphrase extraction. In: Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, pp. 668–673. Morgan Kaufmann Publishers, San Francisco (1999)

    Google Scholar 

  10. Hammouda, K.M., Matute, D.N., Kamel, M.S.: Corephrase: Keyphrase extraction for document clustering. In: Perner, P., Imiya, A. (eds.) MLDM 2005. LNCS (LNAI), vol. 3587, pp. 265–274. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  11. Hulth, A.: Improved automatic keyword extraction given more linguistic knowledge. In: Proceedings of the 2003 conference on Empirical Methods in Natural Language Processing, pp. 216–223. Association for Computational Linguistics, Morristown (2003)

    Chapter  Google Scholar 

  12. Justeson, J., Katz, S.: Technical terminology: some linguistic properties and an algorithm for identification in text. Natural Language Engineering 1, 9–27 (1995)

    Article  Google Scholar 

  13. Kosovac, B., Vanier, D.J., Froese, T.M.: Use of keyphrase extraction software for creation of an AEC/FM thesaurus. Electronic Journal of Information Technology in Construction 5, 25–36 (2000)

    Google Scholar 

  14. Krulwich, B., Burkey, C.: Learning user information interests through the extraction of semantically significant phrases. In: Hearst, M., Hirsh, H. (eds.) AAAI 1996 Spring Symposium on Machine Learning in Information Access, pp. 110–112. AAAI Press, California (1996)

    Google Scholar 

  15. Kumar, N., Srinathan, K.: Automatic keyphrase extraction from scientific documents using n-gram filtration technique. In: Proceedings of the Eight ACM symposium on Document engineering, pp. 199–208. ACM, New York (2008)

    Chapter  Google Scholar 

  16. Litvak, M., Last, M.: Graph-based keyword extraction for single-document summarization. In: Proceedings of the Workshop on Multi-source Multilingual Information Extraction and Summarization, pp. 17–24. ACL, Morristown (2008)

    Chapter  Google Scholar 

  17. Liu, Z., Li, P., Zheng, Y., Sun, M.: Clustering to find exemplar terms for keyphrase extraction. In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, pp. 257–266. ACL, Singapore (2009)

    Google Scholar 

  18. 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, pp. 1318–1327. ACL, Singapore (2009)

    Google Scholar 

  19. Nguyen, T.D., Kan, M.Y.: Keyphrase extraction in scientific publications. In: Goh, D.H.L., Cao, T.H., Sølvberg, I., Rasmussen, E.M. (eds.) ICADL 2007. LNCS, vol. 4822, pp. 317–326. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  20. Porter, M.F.: An algorithm for suffix stripping. Readings in information retrieval, 313–316 (1997)

    Google Scholar 

  21. Song, M., Song, I.Y., Allen, R.B., Obradovic, Z.: Keyphrase extraction-based query expansion in digital libraries. In: Proceedings of the 6th ACM/IEEE-CS joint Conference on Digital libraries, pp. 202–209. ACM, New York (2006)

    Chapter  Google Scholar 

  22. Turney, P.D.: Learning algorithms for keyphrase extraction. Information Retrieval 2(4), 303–336 (2000)

    Article  Google Scholar 

  23. Wan, X., Xiao, J.: Single document keyphrase extraction using neighborhood knowledge. In: Proceedings of the 23rd National Confernce on Artificial Intelligence, pp. 855–860. AAAI Press, Chicago (2008)

    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, New York (1999)

    Chapter  Google Scholar 

  25. Wu, Y.F.B., Li, Q.: Document keyphrases as subject metadata: incorporating document key concepts in search results. Information Retrieval 11(3), 229–249 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Artificial Intelligence Lab, Department of Mathematics and Computer Science, University of Udine, Italy

    Nirmala Pudota, Antonina Dattolo, Andrea Baruzzo & Carlo Tasso

Authors
  1. Nirmala Pudota
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antonina Dattolo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andrea Baruzzo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Carlo Tasso
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Information Engineering, University of Padua, Via Gradenigo, 6/b, 35131, Padova, Italy

    Maristella Agosti

  2. Dipartimento di INformatics, Università di Bari, Via Orabona 4, 70126, Bari, Italy

    Floriana Esposito

  3. Consiglio Nazionale delle Richerche, Istituto di Scienza e Tecnologie dell’Informazione, Via Moruzzi, 1, 56124, Pisa, Italy

    Costantino Thanos

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pudota, N., Dattolo, A., Baruzzo, A., Tasso, C. (2010). A New Domain Independent Keyphrase Extraction System. In: Agosti, M., Esposito, F., Thanos, C. (eds) Digital Libraries. IRCDL 2010. Communications in Computer and Information Science, vol 91. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15850-6_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15850-6_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15849-0

  • Online ISBN: 978-3-642-15850-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation