Using Automatic Metadata Extraction to Build a Structured Syllabus Repository

  • Xiaoyan Yu
  • Manas Tungare
  • Weiguo Fan
  • Manuel Pérez-Quiñones
  • Edward A. Fox
  • William Cameron
  • Lillian Cassel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4822)

Abstract

Syllabi are important documents created by instructors for students. Gathering syllabi that are freely available, and creating useful services on top of the collection, will yield a digital library of value for the educational community. However, gathering and building a repository of syllabi is complicated by the unstructured nature of syllabus representation and the lack of a unified vocabulary for syllabus construction. In this paper, we propose an intelligent approach to automatically annotate freely-available syllabi from the Web to benefit the educational community through supporting services such as semantic search. We discuss our detailed process for converting unstructured syllabi to structured representations through entity recognition, segmentation, and association. Our evaluation results demonstrate the effectiveness of our extractor and also suggest improvements. We hope our work will benefit not only users of our services but also people who are interested in building other genre-specific repositories.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hodgins, W., Duval, E.: Draft standard for learning technology - Learning Object Metadata - ISO/IEC 11404. Technical report (2002)Google Scholar
  2. 2.
    Mccallum, A.: Information extraction: Distilling structured data from unstructured text. ACM Queue 3(9) (November 2005)Google Scholar
  3. 3.
    Thompson, C.A., Smarr, J., Nguyen, H., Manning, C.: Finding educational resources on the web: Exploiting automatic extraction of metadata. In: Proc. ECML Workshop on Adaptive Text Extraction and Mining (2003)Google Scholar
  4. 4.
    Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V.: Gate: A framework and graphical development environment for robust nlp tools and applications. In: Proceedings of the 40th Anniversary Meeting of the Association for Computational Linguistics (ACL 2002), Philadelphia (July 2002)Google Scholar
  5. 5.
    Dowman, M., Tablan, V., Cunningham, H., Popov, B.: Web-assisted annotation, semantic indexing and search of television and radio news. In: WWW 2005. Proceedings of the 14th international conference on World Wide Web, pp. 225–234. ACM Press, New York (2005)CrossRefGoogle Scholar
  6. 6.
    Choi, F.Y.Y.: Advances in domain independent linear text segmentation. In: Proceedings of the first conference on North American chapter of the Association for Computational Linguistics, pp. 26–33. Morgan Kaufmann, San Francisco (2000)Google Scholar
  7. 7.
    Kehagias, A., Nicolaou, A., Petridis, V., Fragkou, P.: Text segmentation by product partition models and dynamic programming. Mathematical and Computer 39(2-3), 209–217 (2004)MATHMathSciNetGoogle Scholar
  8. 8.
    Tungare, M., Yu, X., Cameron, W., Teng, G., Pérez-Quiñones, M., Fox, E., Fan, W., Cassel, L.: Towards a syllabus repository for computer science courses. In: SIGCSE 2007. Proceedings of the 38th Technical Symposium on Computer Science Education, vol. 39, pp. 55–59. ACM Press, New York, NY, USA (2007)CrossRefGoogle Scholar
  9. 9.
    Tungare, M., Yu, X., Teng, G., P érez Quiñones, M., Fox, E., Fan, W., Cassel, L.: Towards a standardized representation of syllabi to facilitate sharing and personalization of digital library content. In: Proceedings of the 4th International Workshop on Applications of Semantic Web Technologies for E-Learning (SW-EL) (2006)Google Scholar
  10. 10.
    Yu, X., Tungare, M., Fan, W., Pérez-Quiñones, M., Fox, E.A., Cameron, W., Teng, G., Cassel, L.: Automatic syllabus classification. In: Proceedings of the Seventh ACM/IEEE-CS Joint Conference on Digital Libraries - JCDL 2007, pp. 440–441 (2007)Google Scholar
  11. 11.
    de Larios-Heiman, L., Cracraft, C.: (SylViA: The Syllabus Viewer Application)Google Scholar
  12. 12.
    Dolog: Reasoning and ontologies for personalized e-learning. Educational Technology and Society (2004)Google Scholar
  13. 13.
    Han, H., Giles, C.L., Manavoglu, E., Zha, H., Zhang, Z., Fox, E.A.: Automatic document metadata extraction using support vector machines. In: JCDL 2003. Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital Libraries, Washington, DC, USA, pp. 37–48. IEEE Computer Society Press, Los Alamitos (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Xiaoyan Yu
    • 1
  • Manas Tungare
    • 1
  • Weiguo Fan
    • 1
  • Manuel Pérez-Quiñones
    • 1
  • Edward A. Fox
    • 1
  • William Cameron
    • 2
  • Lillian Cassel
    • 2
  1. 1.Virginia Tech, Blacksburg VA 24061USA
  2. 2.Villanova University, Villanova PA 19085USA

Personalised recommendations