<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Larbi GUEZOULI</style></author><author><style face="normal" font="default" size="100%">Essafi, Hassane</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CAS-based information retrieval in semi-structured documents: CASISS model</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Innovation in Digital EcosystemsJournal of Innovation in Digital Ecosystems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">155-162</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&amp;nbsp; This paper aims to address the assessment the similarity between documents or pieces of documents. For this purpose we have developed CASISS (CAlculation of SImilarity of Semi-Structured documents) method to quantify how two given texts are similar. The method can be employed in wide area of applications including content reuse detection which is a hot and challenging topic. It can be also used to increase the accuracy of the information&amp;nbsp;retrieval process&amp;nbsp;by taking into account not only the presence of query terms in the given document (Content Only search — CO) but also the topology (position continuity) of these terms (based on Content And Structure Search — CAS). Tracking the origin of the information in social media, copy right management,&amp;nbsp;plagiarism detection, social media mining and monitoring,&amp;nbsp;digital forensic&amp;nbsp;are among other applications require tools such as CASISS to measure, with a high accuracy, the content overlap between two documents. CASISS identify elements of semi-structured documents using elements descriptors. Each semi-structured document is pre-processed before the extraction of a set of elements descriptors, which characterize the content of the elements. &amp;nbsp;</style></abstract></record></records></xml>