Advertisement

Semantic Summarization of News from Heterogeneous Sources

  • Flora Amato
  • Antonio d’Acierno
  • Francesco Colace
  • Vinenzo MoscatoEmail author
  • Antonio Penta
  • Antonio Picariello
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 1)

Abstract

Summarization techniques are becoming an essential part of everyday life, basically because summaries allow users to spend less time making effective access to the desired information. In this paper, we present a general framework for retrieving relevant information from news articles and a novel summarization algorithm based on a deep semantic analysis of texts. In particular, a set of triples (subject, predicate, object) is extracted from each document and it is then used to build a summary through an unsupervised clustering algorithm exploiting the notion of semantic similarity. Finally, we leverage the centroids of clusters to determine the most significant summary sentences using some heuristics. Several experiments are carried out using the standard DUC methodology and ROUGE software and show how the proposed method outperforms several summarizer systems in terms of recall and readability.

Keywords

Semantic Similarity Resource Description Framework Name Entity Recognition Heterogeneous Source Terror Attack 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Leonard Barolli and Fatos Xhafa. Jxta-overlay: A p2p platform for distributed, collaborative, and ubiquitous computing. Industrial Electronics, IEEE Transactions on, 58(6):2163–2172, 2011.Google Scholar
  2. 2.
    Fatos Xhafa, Raul Fernandez, Thanasis Daradoumis, Leonard Barolli, and Santi Caballé. Improvement of jxta protocols for supporting reliable distributed applications in p2p systems. In Network-Based Information Systems, pages 345–354. Springer, 2007.Google Scholar
  3. 3.
    Leonard Barolli, Fatos Xhafa, Arjan Durresi, and Giuseppe De Marco. M3ps: a jxtabased multi-platform p2p system and its web application tools. International Journal of Web Information Systems, 2(3/4):187–196, 2007.Google Scholar
  4. 4.
    Mario Sicuranza, Angelo Esposito, and Mario Ciampi. An access control model to minimize the data exchange in the information retrieval. Journal of Ambient Intelligence and Humanized Computing, pages 1–12, 2015.Google Scholar
  5. 5.
    Aniello Minutolo, Massimo Esposito, and Giuseppe De Pietro. A fuzzy framework for encoding uncertainty in clinical decision-making. Knowledge-Based Systems, 98:95–116, 2016.Google Scholar
  6. 6.
    Aniello Minutolo, Massimo Esposito, and Giuseppe De Pietro. Design and validation of a light-weight reasoning system to support remote health monitoring applications. Engineering Applications of Artificial Intelligence, 41:232–248, 2015.Google Scholar
  7. 7.
    F. Amato, A.R. Fasolino, A. Mazzeo, V. Moscato, A. Picariello, S. Romano, and P. Tramontana. Ensuring semantic interoperability for e-health applications. pages 315–320, 2011.Google Scholar
  8. 8.
    F. Amato, A. Mazzeo, V. Moscato, and A. Picariello. A framework for semantic interoperability over the cloud. pages 1259–1264, 2013.Google Scholar
  9. 9.
    Tim French, Nik Bessis, Fatos Xhafa, and Carsten Maple. Towards a corporate governance trust agent scoring model for collaborative virtual organisations. International Journal of Grid and Utility Computing, 2(2):98–108, 2011.Google Scholar
  10. 10.
    Valentin Cristea, F. Pop, C. Stratan, A. Costan, C. Leordeanu, and E. Tirsa. A dependability layer for large-scale distributed systems. International Journal of Grid and Utility Computing, 2(2):109–118, 2011.Google Scholar
  11. 11.
    Soichi Sawamura, Admir Barolli, Ailixier Aikebaier, Makoto Takizawa, and Tomoya Enokido. Design and evaluation of algorithms for obtaining objective trustworthiness on acquaintances in p2p overlay networks. International Journal of Grid and Utility Computing, 2(3):196–203, 2011.Google Scholar
  12. 12.
    Evjola Spaho, Gjergji Mino, Leonard Barolli, and Fatos Xhafa. Goodput and pdr analysis of aodv, olsr and dymo protocols for vehicular networks using cavenet. International Journal of Grid and Utility Computing, 2(2):130–138, 2011.Google Scholar
  13. 13.
    H. Takamura and M. Okumura. Text summarization model based on maximum coverage problem and its variant. In Proceedings of the 12th Conference of the European Chapter of the AC, pages 781–789, 2009.Google Scholar
  14. 14.
    Dan Gillick and Benoit Favre. A scalable global model for summarization. In Proceedings of the Workshop on Integer Linear Programming for Natural Language Processing, ILP ’09, pages 10–18. Association for Computational Linguistics, 2009.Google Scholar
  15. 15.
    Salvatore Cuomo, Pasquale De Michele, Ardelio Galletti, and Giovanni Ponti. Intelligent Interactive Multimedia Systems and Services 2016, volume 55 of Smart Innovation, Systems and Technologies, chapter Influence of Some Parameters on Visiting Style Classification in a Cultural Heritage Case Study, pages 567–576. Springer International Publishing, 2016.Google Scholar
  16. 16.
    Salvatore Cuomo, Pasquale De Michele, Ardelio Galletti, and Giovanni Ponti. Data Management Technologies and Applications: 4th International Conference, DATA 2015, Colmar, France, July 20-22, 2015, Revised Selected Papers, volume 584 of Communications in Computer and Information Science, chapter Classify Visitor Behaviours in a Cultural Heritage Exhibition, pages 17–28. Springer International Publishing, 2016.Google Scholar
  17. 17.
    Oren Etzioni, Anthony Fader, Janara Christensen, Stephen Soderland, and Mausam Mausam. Open information extraction: The second generation. In IJCAI, volume 11, pages 3–10, 2011.Google Scholar
  18. 18.
    ZhibiaoWu and Martha Palmer. Verb semantics and lexical selection. In 32nd. Annual Meeting of the Association for Computational Linguistics, pages 133 –138, 1994.Google Scholar
  19. 19.
    A. D’Acierno, V. Moscato, F. Persia, A. Picariello, and A. Penta. iwin: A summarizer system based on a semantic analysis of web documents. pages 162–169, 2012.Google Scholar
  20. 20.
    G. Sannino, I. De Falco, and G. De Pietro. An automatic rules extraction approach to support osa events detection in an mhealth system. IEEE Journal of Biomedical and Health Informatics, 18(5):1518–1524, 2014.Google Scholar
  21. 21.
    Angelo Chianese, Fiammetta Marulli, Francesco Piccialli, Paolo Benedusi, and Jai E Jung. An associative engines based approach supporting collaborative analytics in the internet of cultural things. Future Generation Computer Systems, 2016.Google Scholar
  22. 22.
    A. Chianese, F. Piccialli, and I. Valente. Smart environments and cultural heritage: a novel approach to create intelligent cultural spaces. Journal of Location Based Services, 9:209–234, 2015.Google Scholar
  23. 23.
    Giuseppe Caggianese, Luigi Gallo, and Giuseppe De Pietro. Design and preliminary evaluation of a touchless interface for manipulating virtual heritage artefacts. In Signal-Image Technology and Internet-Based Systems (SITIS), 2014 Tenth International Conference on, pages 493–500. IEEE, 2014.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Flora Amato
    • 1
  • Antonio d’Acierno
    • 2
  • Francesco Colace
    • 4
  • Vinenzo Moscato
    • 1
    Email author
  • Antonio Penta
    • 3
  • Antonio Picariello
    • 1
  1. 1.DIETI - University of NaplesNaplesItaly
  2. 2.ISA - Consiglio Nazionale delle Ricerche (CNR)AvellinoItaly
  3. 3.Department of Computer ScienceUniversity of TurinTorinoItaly
  4. 4.Dipartimento di Ingegneria dell’Informazione, Ingegneria Elettrica e Matematica ApplicataUniversity of SalernoFiscianoItaly

Personalised recommendations