Paper Info
Title
AUSMS : un environnement pour l'extraction de sous-structures fréquentes dans une collection d'objets semi-structurés
Abstract
Mining knowledge from structured data has been extensively addressed in the few past years. However, most proposed approaches are interested in flat structures. With the growing popularity of the Web, the number of semi-structured documents available fastly increases. Structure of these objects is irregular and it is clever to think that a query on documents structure is almost as important as a query on data. Moreover, manipulated data is not static because new updates are constantly realised. Problem of maintaining such sub- structures is then prior on researching them because, every time data is updated, found sub-structures could become invalid. In this paper we propose a system, called A.U.S.M.S. (Automatic Update Schema Mining System), allowing data retrieval, researching frequent sub-structures and maintaining extracted knowledge after sources evolutions.
Year
Venue
Keywords
2003
EGC
semi-structured data,données semi-structurées,web-mining.,web mining. key words: frequent sub-structures mining,mots-cles : découverte de sous- structures fréquentes,web mining,semi structured data,document structure,data retrieval,structured data
Field
DocType
Citations 
Humanities,Art,Art history
Conference
0
PageRank 
References 
Authors
0.34
17
2
Name
Order
Citations
PageRank
Pierre-alain Laur1214.66
Pascal Poncelet2768126.47