Abstract
Entities and the concepts they instantiate evolve over time. For example, a corporate entity may have resulted from a series of mergers and splits, or a concept such as that of Whale may have evolved along with our understanding of the physical world. We propose a model for capturing and querying concept evolution. Our proposal extends an RDF-like model with temporal features and evolution operators. In addition, we provide a query language that exploits these extensions and supports historical queries. Moreover, we study how evolution information can be exploited to answer queries that are agnostic to evolution details (hence, evolution-unaware). For these, we propose dynamic programming algorithms and evaluate their efficiency and scalability by experimenting with both real and synthetic datasets.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.