Skip to main content
Log in

A tetrahedral data model for unstructured data management

  • Research Papers
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

This paper proposes a tetrahedral data model for unstructured data management. The model defines the four components of unstructured data including: basic attributes, semantic characteristics, low-level features and raw data on its four facets, and the relations between these components. The internal implementation structure of the model and the data query language are designed and briefly introduced. This model provides a unified, integrated and associated description for different kinds of unstructured data, and supports intelligent data services such as associated retrieval and data mining. An example is given to demonstrate how to use the model for describing and manipulating data from a sample video base.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. OASIS. Unstructured Information Management Architecture (UIMA). Version 1.0, Working Draft 05, May 2008

  2. Oomoto E, Tanaka K. OVID: Design and implementation of a video object database system. IEEE Trans Knowl Data Eng, 1993, 5: 629–643

    Article  Google Scholar 

  3. Wu J K, Narasimhalu A D, Mehtre B M, et al. CORE: a content-based retrieval engine for multimedia information systems. Multimed Syst, 1995, 3: 25–41

    Article  Google Scholar 

  4. Aslandogan Y A, Their C, Yu C T, et al. Design, implementation and evaluation of SCORE (a system for content based retrieval of pictures). In: Proceedings of the Eleventh International Conference on Data Engineering (IDCE), Taipei, 1995. 280–287

  5. Gruber T. Towards principles for the design of ontologies used for knowledge sharing. Technical Report, KSL-93-04, Knowledge Systems Laboratory, Stanford University, 1993

  6. Chaudhry W R, Meziane F. Information extraction from heterogeneous sources using domain ontologies. In: Proc of IEEE International Conference on Emerging Technologies, Islamnabad, Pakistan, 2005. 511–516

  7. Town C P. Ontology based visual information processing. PhD Thesis, Cambridge: University of Cambridge, 2004

    Google Scholar 

  8. Flickner M, Sawhney H, Niblack W, et al. Query by image and video content: The QBIC system. IEEE Comput, 1995, 28: 23–32

    Google Scholar 

  9. Bach J R, Fuller C, Gupta A, et al. The virage image search engine: an open framework for image management. In: Procs of IS&T/SPIE Storage and Retrieval for Still Image and Video Databases IV, San Jose, USA, 1996

  10. Pentland A, Picard R W, Sclaroff S. Photobook: content-based manipulation in image databases. Int J Comput Vision, 1995, 18: 233–254

    Article  Google Scholar 

  11. Doan A, Naughton J F, Baid A, et al. The case for a structured approach to managing unstructured data. In: Procs of the Fourth Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, 2009

  12. Srivastava D, Velegrakis Y. Intentional associations between data and metadata. In: SIGMOD’07, Beijing, China, 2007

  13. Siadat M, Soltanian-Zadeh H, Fotoub I F, et al. Data modeling for content-based support environment (C-BASE): application on Epilepsy Data Mining. In: Proc of the 7th IEEE International Conference on Data Mining, Omaha, NE, USA, 2007. 181–186

  14. Chu E, Baid A, Chen T, et al. A relational approach to incrementally extracting and querying structure in unstructured data. In: Proc of VLDB’07, Vienna, Austria, 2007

  15. Marcus S, Subrahmanian V S. Foundations of multimedia database systems. J ACM, 1996, 43: 474–523

    Article  MATH  MathSciNet  Google Scholar 

  16. Amato G, Mainetto G, Savino P. An approach to a content-based retrieval of multimedia data. Multimed Tools Appl, 1998, 7: 9–36

    Article  Google Scholar 

  17. Codd E F. A relational model of data for large shared data banks. Commun ACM, 1970, 13: 377–387

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wei Li.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, W., Lang, B. A tetrahedral data model for unstructured data management. Sci. China Inf. Sci. 53, 1497–1510 (2010). https://doi.org/10.1007/s11432-010-4030-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-010-4030-9

Keywords

Navigation