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ABSTRACT

Since the XML format became a de facto standard for structured documents, the IT research and industry have developed a number of XML editors to help users produce structured documents in XML format. However, the manual generation of structured documents in XML format remains a tedious and time-consuming process because of the excessive verbosity and length of XML code. In this paper, we design a structural adviser for the XML document authoring. The adviser intervenes at any step of the authoring process to suggest one tag or entire tree-like pattern the user is most likely to use next. Adviser suggestions are based on finding analogies between the currently edited fragment and sample data being either previously generated documents in the collection or the history of the current document authoring. The adviser is beneficial in cases when no schema is provided for XML documents, or schema associated with the document is too general and sample data contain specific patterns not captured in the schema. We design the adviser architecture and develop a method for efficient indexing and retrieval of optimal suggestions at any step of the document authoring.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.7 DOCUMENT AND TEXT PROCESSING
      I.7.2 Document Preparation
          Subjects: Markup languages

Additional Classification:
  F. Theory of Computation
  F.2 ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY
      F.2.2 Nonnumerical Algorithms and Problems
          Subjects: Computations on discrete structures

General Terms:
Algorithms, Documentation, Measurement, Performance

Keywords:
XML markup, data mining, structural pattern, suggestion