Open AccessSemi-structured Documents Mining: A Review and Comparison
Author(s) -
Amina Madani,
Omar Boussaïd,
Djamel Eddine Zegour
Publication year - 2013
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2013.09.110
Subject(s) - computer science , information retrieval , data mining , data science
The number of semi-structured documents that is produced is steadily increasing. Thus, it will be essential for discovering new knowledge from them. In this survey paper, we review popular semi-structured documents mining approaches (structure alone and both structure and content). We provide a brief description of each technique as well as efficient algorithms for implementing the technique and comparing them using different comparison criteria
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