Advertisement

Toward Ontology Representation and Reasoning for News

  • Xubo Wen
  • Xiaoli Ma
  • Juanzi Li
  • Jeff Z. Pan
  • Jiayu Xie
Part of the Communications in Computer and Information Science book series (CCIS, volume 406)

Abstract

Most research work on news mining nowadays covers phrase and topic level. A few works conducted on logical level mainly focus on personalized news service and no special efforts are put on the applications of ontology techniques on deep news mining. In this paper, we demonstrate a whole strategy for deeply understanding event-focused news taking the advantage of ontology representation and ontology reasoning. We propose an ontology-enriched news deep understanding framework ONDU which addresses the following problems: (1) how to transfer parsed news content into logical triples by using domain ontology. (2) The application of ONDU based on the reasoning results from the ontology reasoner TrOWL over the RDF data expressing the news. Through this whole strategy we can detect the inconsistence among multiple news articles and compare the different information implied in different news. We can even integrate a set of news content through merging the RDF data. The empirical experiment conducted on news from several portals shows the effectiveness and usefulness of our method.

Keywords

Ontology reasoning news mining text understanding TrOWL 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Li, L., Wang, D., Li, T., Knox, D., Padmanabhan, B.: Scene: a scalable two-stage personalized news recommendation system. In: SIGIR 2011, pp. 125–134 (2011)Google Scholar
  2. 2.
    Wayne, C.L.: Multiligual topic detection and tracking: successful research enabled by corpora and evaluation. In: Conference: Language Resources and Evaluation - LREC (2000)Google Scholar
  3. 3.
    Conlan, O., O’Keeffe, I., Tallon, S.: Combining Adaptive Hypermedia Techniques and Ontology Reasoning to Produce Dynamic Personalized News Services. In: Wade, V.P., Ashman, H., Smyth, B. (eds.) AH 2006. LNCS, vol. 4018, pp. 81–90. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    Leskovec, J., Backstrom, L., Kleinberg, J.M.: Meme-tracking and the dynamics of the news cycle. In: SIGKDD 2009, pp. 457–466 (2009)Google Scholar
  5. 5.
    Kanhabua, N., Blanco, R., Matthews, M.: Ranking related news prediction. In: SIGIR 2011, pp. 755–764 (2011)Google Scholar
  6. 6.
    Pouliquen, B., Steinberger, R., Deguernel, O.: Story tracking: linking similar news over time and across languages. In: Colling 2008 MMIES Workshop, pp. 49–56 (2008)Google Scholar
  7. 7.
    Shan, D., Zhao, W.X., Chen, R., Shu, B., Wang, Z., Yao, J., Yan, H., Li, X.: Eventsearch: a system for event discovery and retrieval on multi-type historical data. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1564–1567 (2012)Google Scholar
  8. 8.
    Leskovec, J., Grobelnik, M., Milic-Franling, N.: Learning sub-structures of document semantic graphs for document summarization. In: Proceedings of the 7th International Multi-Conference Information Society (2004)Google Scholar
  9. 9.
    Kalfoglou, Y., Kalfoglou, Y., Domingue, J., Domingue, J., Motta, E., Motta, E., Vargas-Vera, M., Vargas-vera, M., Shum, S.B., Shum, S.B.: myPlanet: an ontology-driven Web-based personalized news service. In: Proceedings of the IJCAI 2001 Workshop on Ontologies and Information Sharing (2001)Google Scholar
  10. 10.
    Hou, L., Li, J.Z., Tang, J., Liu, Y.K., Zheng, Q.: Newsminer: multifaceted news analysis for event search. To be Appeared in ACM Transactions on Information System 9(4) (2012)Google Scholar
  11. 11.
    Brank, J., Grobelnik, M., Mladenić, D.: A survey of ontology evaluation techniques. In: Proceedings of the Conference on Data Mining and Data Warehouses, SiKDD 2005 (2005)Google Scholar
  12. 12.
    Subhashini, R., Akilandeswari, J.: A survey on ontology construction methodologies. International Journal of Enterprise Computing and Business Systems 1(1), 60–72 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Xubo Wen
    • 1
    • 2
  • Xiaoli Ma
    • 2
  • Juanzi Li
    • 2
  • Jeff Z. Pan
    • 3
  • Jiayu Xie
    • 1
  1. 1.Information Engineering Institute of Technology, Naval Academy of ArmamentP.R. China
  2. 2.Department of Computer Science and TechnologyTsinghua UniversityBeijingP.R. China
  3. 3.Department of Computer ScienceUniversity of AberdeenUK

Personalised recommendations