(2021). Visualizing and exploring big datasets based on semantic community detection. In Proceedings of the 24th International Conference on Extending Database Technology (EDBT 2021) (pp. 678–681). OpenProceedings.org. https://doi.org/10.5441/002/edbt.2021.82
Περίληψη
The extended use of the RDF model has made available many datasets from heterogeneous sources that are of interest to a wide audience. Their exploration, however, is a highly demanding task requiring extensive training and knowledge of the SPARQL language. In this demo, we present an innovative system, which supports the exploration of large RDF datasets without requiring any knowledge about the RDF or SPARQL. The system is based on a novel algorithm that detects semantically similar communities capitalizing on hyperbolic network embedding and a weighted similarity metric. The detected communities are visualized in a user-friendly way and presented to the user through a two level abstraction interface with a toolbox of exploration functionalities. © 2021 Copyright held by the owner/author(s).
- DOI
- 10.5441/002/edbt.2021.82
- Τύπος
- Άρθρο σε Πρακτικά Συνεδρίου
- Έτος
- 2021
Σύνδεσμοι
BibTeX
@inproceedings{krommyda2021visualizing2,
title = {Visualizing and exploring big datasets based on semantic community detection},
author = {Maria Krommyda and Konstantinos Tsitseklis and Verena Kantere and Vasileios Karyotis and Symeon Papavassiliou},
url = {https://doi.org/10.5441/002/edbt.2021.82},
doi = {10.5441/002/edbt.2021.82},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Proceedings of the 24th International Conference on Extending Database Technology (EDBT 2021)},
pages = {678--681},
publisher = {OpenProceedings.org},
abstract = {The extended use of the RDF model has made available many datasets from heterogeneous sources that are of interest to a wide audience. Their exploration, however, is a highly demanding task requiring extensive training and knowledge of the SPARQL language. In this demo, we present an innovative system, which supports the exploration of large RDF datasets without requiring any knowledge about the RDF or SPARQL. The system is based on a novel algorithm that detects semantically similar communities capitalizing on hyperbolic network embedding and a weighted similarity metric. The detected communities are visualized in a user-friendly way and presented to the user through a two level abstraction interface with a toolbox of exploration functionalities. © 2021 Copyright held by the owner/author(s).},
keywords = {Community detection; Heterogeneous sources; Hyperbolic networks; Innovative systems; Novel algorithm; RDF model; Similarity metrics; User friendly, Database systems; Large dataset; Semantics, Semantic Web},
pubstate = {published},
tppubtype = {inproceedings}
}