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Identifier 000446545
Title iSummary : workload-based, personalized summaries for RDF/S KBs
Alternative Title iSummary : workload-based , προσωποποιημένες συνόψεις για RDF/S KBs δεδομένα
Author Αλεβιζάκης, Φάνης Δ.
Thesis advisor Πλεξουσάκης, Δημήτρης
Reviewer Μαγκούτης, Κωνσταντίνος
Φλουρής, Γεώργιος
Abstract The explosion on the size and the complexity of the available RDF data has led to the need for efficient and effective methods for their understanding and exploration. To this direction, semantic summaries have been proposed for extracting compact information from the original RDF graph that many applications can exploit instead of the original RDF graph, offering a way to quickly explore and understand the contents of the various sources. In this thesis we present iSummary, a novel approach for constructing personalized summaries based on query workloads. The main idea behind our approach is to exploit knowledge captured in existing user queries for identifying the most interesting resources and to capitalize query workloads for constructing and presenting high quality personalized summaries. We demonstrate our approach using two real world datasets and the corresponding query workloads and we show the advantages of our approach.
Language English
Subject Semantic data
Shortest path algorithms
Αλγόριθμοι συντομότερων μοναπατιών
Σημασιολογικά δεδομένα
Issue date 2022-03-18
Collection   School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/a/5/9/metadata-dlib-1646997467-424056-20359.tkl Bookmark and Share
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