Master defect record retrieval using network-based feature association

Andrew Rodriguez, W. Art Chaovalitwongse, Liang Zhe, Harsh Singhal, Hoang Pham

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


As electronic records (e.g., medical records and technical defect records) accumulate, the retrieval of a record from a past instance with the same or similar circumstances, has become extremely valuable. This is because a past record may contain the correct diagnosis or correct solution to the current circumstance. We refer to the two records of the same or similar circumstances as master and duplicate records. Current record retrieval techniques are lacking when applied to this special master defect record retrieval problem. In this study, we propose a new paradigm for master defect record retrieval using network-based feature association (NBFA). We train the master record retrieval process by constructing feature associations to limit the search space. The retrieval paradigm was employed and tested on a real-world large-scale defect record database from a telecommunications company. The empirical results suggest that the NBFA was able to significantly improve the performance of master record retrieval, and should be implemented in practice. This paper presents an overview of technical aspects of the master defect record retrieval problem, describes general methodologies for retrieval of master defect records, proposes a new feature association paradigm, provides performance assessments on real data from a telecommunications company, and highlights difficulties and challenges in this line of research that should be addressed in the future.

Original languageEnglish (US)
Article number5406165
Pages (from-to)319-329
Number of pages11
JournalIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
Issue number3
StatePublished - May 2010

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


  • Information retrieval (IR)
  • Keyword library
  • Keyword weighting
  • Query
  • Text mining
  • Vector space model (VSM)

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