conTEXT – Lightweight Text Analytics Using Linked Data

  • Ali Khalili
  • Sören Auer
  • Axel-Cyrille Ngonga Ngomo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8465)

Abstract

The Web democratized publishing – everybody can easily publish information on a Website, Blog, in social networks or microblogging systems. The more the amount of published information grows, the more important are technologies for accessing, analysing, summarising and visualising information. While substantial progress has been made in the last years in each of these areas individually, we argue, that only the intelligent combination of approaches will make this progress truly useful and leverage further synergies between techniques. In this paper we develop a text analytics architecture of participation, which allows ordinary people to use sophisticated NLP techniques for analysing and visualizing their content, be it a Blog, Twitter feed, Website or article collection. The architecture comprises interfaces for information access, natural language processing and visualization. Different exchangeable components can be plugged into this architecture, making it easy to tailor for individual needs. We evaluate the usefulness of our approach by comparing both the effectiveness and efficiency of end users within a task-solving setting. Moreover, we evaluate the usability of our approach using a questionnaire-driven approach. Both evaluations suggest that ordinary Web users are empowered to analyse their data and perform tasks, which were previously out of reach.

Keywords

#eswc2014Khalili 

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References

  1. 1.
    Solution brief: Ibm content analytics with enterprise search, version 3.0, http://www-03.ibm.com/software/products/us/en/contentanalyticssearch
  2. 2.
    Bizer, C., Eckert, K., Meusel, R., Mühleisen, H., Schuhmacher, M., Völker, J.: Deployment of rDFa, microdata, and microformats on the web – A quantitative analysis. In: Alani, H., et al. (eds.) ISWC 2013, Part II. LNCS, vol. 8219, pp. 17–32. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  3. 3.
    Bostock, M., Ogievetsky, V., Heer, J.: D3 data-driven documents. IEEE Transactions on Visualization and Computer Graphics 17(12), 2301–2309 (2011)CrossRefGoogle Scholar
  4. 4.
    Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V., Aswani, N., Roberts, I., Gorrell, G., Funk, A., Roberts, A., Damljanovic, D., Heitz, T., Greenwood, M.A., Saggion, H., Petrak, J., Li, Y., Peters, W.: Text Processing with GATE (Version 6) (2011), http://tinyurl.com/gatebook
  5. 5.
    Dadzie, A.S., Rowe, M.: Approaches to visualising linked data. Semantic Web 2(2), 89–124 (2011)Google Scholar
  6. 6.
    Ennals, R., Brewer, E.A., Garofalakis, M.N., Shadle, M., Gandhi, P.: Intel mash maker: join the web. SIGMOD Record 36(4), 27–33 (2007)CrossRefGoogle Scholar
  7. 7.
    Ferrucci, D., Lally, A.: Uima: an architectural approach to unstructured information processing in the corporate research environment. Nat. Lang. Eng. 10(3-4), 327–348 (2004), http://dx.doi.org/10.1017/S1351324904003523 CrossRefGoogle Scholar
  8. 8.
    Gerber, D., Ngonga Ngomo, A.C.: Bootstrapping the linked data web. In: 1st Workshop on Web Scale Knowledge Extraction @ ISWC 2011 (2011)Google Scholar
  9. 9.
    Goetz, T.: Harnessing the power of feedback loops. WIRED Magazine (2011), http://www.wired.com/magazine/2011/06/ff_feedbackloop/
  10. 10.
    Hellmann, S., Lehmann, J., Auer, S., Brümmer, M.: Integrating NLP using linked data. In: Alani, H., et al. (eds.) ISWC 2013, Part II. LNCS, vol. 8219, pp. 98–113. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  11. 11.
    Huynh, D.F., Karger, D.R., Miller, R.C.: Exhibit: lightweight structured data publishing. In: WWW 2007, pp. 737–746. ACM, New York (2007)Google Scholar
  12. 12.
    Jungermann, F.: Information Extraction with RapidMiner, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.151.5586
  13. 13.
    Kandel, S., Paepcke, A., Hellerstein, J., Heer, J.: Wrangler: interactive visual specification of data transformation scripts. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2011, pp. 3363–3372. ACM (2011)Google Scholar
  14. 14.
    Khalili, A., Auer, S.: Wysiwym authoring of structured content based on schema.org. In: Lin, X., Manolopoulos, Y., Srivastava, D., Huang, G. (eds.) WISE 2013, Part II. LNCS, vol. 8181, pp. 425–438. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  15. 15.
    Khalili, A., Auer, S., Hladky, D.: The rdfa content editor. In: IEEE COMPSAC 2012, pp. 531–540. IEEE Computer Society (2012)Google Scholar
  16. 16.
    Lewis, J., Sauro, J.: The Factor Structure of the System Usability Scale. In: Kurosu, M. (ed.) HCD 2009. LNCS, vol. 5619, pp. 94–103. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  17. 17.
    Mendes, P.N., Jakob, M., García-Silva, A., Bizer, C.: Dbpedia spotlight: shedding light on the web of documents. In: Proceedings of the 7th International Conference on Semantic Systems, I-Semantics 2011, pp. 1–8. ACM, New York (2011)Google Scholar
  18. 18.
    Ngonga Ngomo, A.-C., Heino, N., Lyko, K., Speck, R., Kaltenböck, M.: SCMS – semantifying content management systems. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part II. LNCS, vol. 7032, pp. 189–204. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  19. 19.
    Preotiuc-Pietro, D., Samangooei, S., Cohn, T., Gibbins, N., Niranjan, M.: Trendminer: an architecture for real time analysis of social media text (June 2012)Google Scholar
  20. 20.
    Yang, H., Pupons-Wickham, D., Chiticariu, L., Li, Y., Nguyen, B., Carreno-Fuentes, A.: I can do text analytics!: designing development tools for novice developers. In: CHI 2013, pp. 1599–1608. ACM, New York (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ali Khalili
    • 1
  • Sören Auer
    • 2
  • Axel-Cyrille Ngonga Ngomo
    • 1
  1. 1.AKSW, Institute of Computer ScienceUniversity of LeipzigLeipzigGermany
  2. 2.Institute of Computer ScienceUniversity of Bonn and Fraunhofer IAISBonnGermany

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