Multirelational data mining methods discover patterns across multiple interlinked tables (relations) in a relational database. In many large organizations, such a multi-relational ...
The rapid growth of available data arises the need for more sophisticated techniques for semantic access to information. It has been proved that using conceptual model or ontology...
—With the increasing development of real applications using Semantic Web Technologies, it is necessary to provide scalable and efficient ontology querying and reasoning systems....
One of the most ubiquitous elements of modern computing is the relational database. Very few modern applications are created without some sort of database backend. Unfortunately, r...
Real-world automated reasoning systems must contend with inconsistencies and the vast amount of information stored in relational databases. In this paper, we introduce compilation...
Timothy L. Hinrichs, Jui-Yi Kao, Michael R. Genese...
This proposal explores the promotion of existing relational databases to Semantic Web Endpoints. It presents the benefits of ontologybased read and write access to existing relati...
— Keyword search on relational databases provides users with insights that they can not easily observe using the traditional RDBMS techniques. Here, an l-keyword query is speci...
We introduce a client-server toolkit called Sync Kit that demonstrates how client-side database storage can improve the performance of data intensive websites. Sync Kit is designe...
Edward Benson, Adam Marcus 0002, David R. Karger, ...
Research in relational data mining has two major directions: finding global models of a relational database and the discovery of local relational patterns within a database. While...
In this paper, we present the ArchIS system that achieves full-functionality transaction-time databases without requiring temporal extensions in XML or database standards. ArchIS&...