Referential integrity is one of the integrity constraints for any data model. In relational data model, inclusion dependency (ID) and foreign key (FK) are well studied and are widely used. In last decade, with the gro...
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Referential integrity is one of the integrity constraints for any data model. In relational data model, inclusion dependency (ID) and foreign key (FK) are well studied and are widely used. In last decade, with the growing use of XML as data representation and exchange format over the web, the issue of integrity constraints in XML has received great importance to the database community. In this paper, we propose XML inclusion dependency (XID) and XML foreign key(XFK). When proposing, we show how both XID and XFK can be defined over the Document Type Definition (DTD) and are satisfied by the XML documents. We introduce a novel concept tuple that produces semantically correct values in the XML documents when satisfactions are checked. We also show that XFK is defined with the combination of XID and XML key.
The World Wide web (WWW) is becoming one of the most preferred and widespread mediums of learning. Unfortunately, most of the current web-based learning systems are still delivering the same educational resources in t...
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The World Wide web (WWW) is becoming one of the most preferred and widespread mediums of learning. Unfortunately, most of the current web-based learning systems are still delivering the same educational resources in the same way to learners with different profiles. A number of past efforts have dealt with e-learning personalization, generally, relying on explicit information. In this paper, we aim to compute on-line automatic recommendations to an active learner based on his/her recent navigation history, as well as exploiting similarities and dissimilarities among user preferences and among the contents of the learning resources. First we start by mining learner profiles using web usage mining techniques and content-based profiles using information retrieval techniques. Then, we use these profiles to compute relevant links to recommend for an active learner by applying a number of different recommendation strategies.
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