Title :
XCLSC: Structure and content-based clustering of XML documents
Author :
Bessine, Karima ; Nehar, Attia ; Cherroun, Hadda ; Moussaoui, Abdelouahab
Author_Institution :
Laboratoire d´Informatique et Mathématiques Université Amar Télidji Laghouat, Algérie
Abstract :
This paper proposes a novel Clustering approach for XML documents that combines both their content and structure information using tree structural-content summaries in order to reduce the size of the document. This reduction has twofold purpose. First, it reduces the size of the XML tree by eliminating redundant nodes. Second, it gathers similaire content. The clustering is performed according to a similarity measure that takes into account the structure and the content between levels. Several experiments are performed to explore the effectiveness of using tree structural summaries and constrained content in the clustering process. Empirical analysis reveals that the designed clustering approach using content within structure and tree structural summaries gives a better solution for XML clustering while improving runtime. It is very suitable when we deal with big data sets.
Keywords :
Big data; Clustering algorithms; Data structures; Electronic mail; Entropy; Information services; XML; Clustering; Level Structure-Content; Structural Summary; XML documents;
Conference_Titel :
Programming and Systems (ISPS), 2015 12th International Symposium on
Conference_Location :
Algiers, Algeria
DOI :
10.1109/ISPS.2015.7244989