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논문검색

Integrate Metadata by Semantic Recommendation : A Psychology Inspired Method

초록

영어

Complicated data structure can handicap the integration of systems in enterprises and universities. It is important to find an efficient way to deal with the mass documents of these heterogeneous and distributed systems to be integrated. In this paper, a three layered data scheme is introduced for data recommendation in software engineering process inspired by spreading activation theory. Metadata can be more efficiently managed with this scheme in integration and analysis.

목차

Abstract
 1. Introduction
 2. Related Work
  2.1. Spreading Activation Theory
  2.2. Knowledge Grid and Software Design
  2.3. Metadata and Data Integration
  2.4. E-R graph and Data Models
 3. Three Layered Data Scheme & Metadata Unification
  3.1. E-R graph and Data Models
  3.2. Unifying Meta Layer
  3.3. Generating Data View Layer
 4. Semantic Recommendation
  4.1. Spreading Activation on the E-R Graph
  4.2. Algorithm of Meta Structure Recommendation
 5. Implement and Results
  5.1. Implement Algorithms to Recommend Data Extraction
  5.2. Input XML Scheme
  5.3. Attribute Matching
  5.4. Recommendation as Data View
  5.5. Dividing and Combination of Views
  5.6. Result of Implementing
 6. Conclusion
 7. Discussion and Future Works
 Acknowledgements
 References

저자정보

  • Xixu Fu Institute of Information and Education Technology, Shanghai Ocean University
  • Yuan Ren School of Computer Science, Shanghai Dianji University

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