Mining HTML5 code: a view to how humans use emerging web standards

ABSTRACT

Currently, Web quality research term mainly refers to the quality of content of web pages. There are some research efforts on Javascript code and CSS code quality metrics, but none for measuring metrics of HTML5 code and estimating its quality and quantity. Towards this direction the aim of this work is to determine what characteristics of HTML5 code can be measured, to specify concrete metrics to measure those characteristics, to implement a tool for calculating them for a small set of representative web pages and finally evaluate experimentally the results based on statistical analysis and data mining techniques.

References

1. Halstead, Maurice H. (1977). Elements of Software Science. Amsterdam: Elsevier North-Holland, Inc. ISBN 0-444-00205-7.
2. Page, Lawrence and Brin, Sergey and Motwani, Rajeev and Winograd, Terry (1999) The PageRank Citation Ranking: Bringing Order to the Web. Technical Report. Stanford InfoLab.

Index Terms

• Applied computing

  • Document management and text processing

    • Document preparation

• Computing methodologies

  • Machine learning

    • Machine learning approaches

      • Neural networks

• Hardware

  • Emerging technologies

    • Circuit substrates

      • Cellular neural networks

• Information systems

  • Information systems applications

    • Data mining

• Theory of computation

  • Theory and algorithms for application domains

    • Machine learning theory