UCSY's Research Repository

Clustering XML Documents using Structural Similarity

Show simple item record

dc.contributor.author Lwin, Moet Moet
dc.contributor.author Htoon, Ei Chaw
dc.date.accessioned 2019-07-12T07:53:42Z
dc.date.available 2019-07-12T07:53:42Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/882
dc.description.abstract Extensible Mark-up Language (XML) is increasingly important in data exchange and information management. The automatic processing and management of XML-based data are ever more popular research issues due to the increasing abundant use of XML, especially on the web. Clustering is also helpful for categorizing web documents. Clustering, which means the physical arrangement of objects, can be an important factor in improving the performance in the storage model. Clustering XML documents using structural similarity based on Progressively Clustering XML by Structural Similarity (PCXSS) method is presented in this paper. The PCXSS method intends to deal with the heterogeneous XML schemas to cluster XML documents by considering only the structural similarity. The efficiency of PCXSS methodology has been analysed with the real datasets which are ACM SIGMOD record, DBLP, XML Repository and Wisconsin’s XML data bank. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.subject Clustering en_US
dc.subject PCXSS Methodology en_US
dc.title Clustering XML Documents using Structural Similarity en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Repository



Browse

My Account