Ranking Error-Correcting Output Codes for Class Retrieval

نویسندگان

  • Mehdi Mirza-Mohammadi
  • Francesco Ciompi
  • Sergio Escalera
  • Oriol Pujol
  • Petia Radeva
چکیده

Error-Correcting Output Codes (ECOC) is a general framework for combining binary classification in order to address the multi-class categorization problem. In this paper, we include contextual and semantic information in the decoding process of the ECOC framework, defining an ECOC-rank methodology. Altering the ECOC output values by means of the adjacency of classes based on features and class relations based on ontology, we defined a new methodology for class retrieval problems. Results over public data show performance improvement when using the new ECOC-rank in the retrieval process.

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تاریخ انتشار 2009