A New Time-sensitive Model of Linguistic Knowledge for Graph Databases

Pierpaolo Basile; Pierluigi Cassotti; Stefano Ferilli; Barbara McGillivray

A New Time-sensitive Model of Linguistic Knowledge for Graph Databases

Pierpaolo Basile, Pierluigi Cassotti, Stefano Ferilli, Barbara McGillivray

Digital Humanities

Università di Bari

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

Graph databases are a straightforward technology for storing knowledge graphs. However, they are schema-less. We apply the GraphBRAIN Schema (GBS) format to describe Time-sensitive Linguistic Knowledge in a graph database (Neo4j). Our schema can model relations between concepts and words, information about word occurrences, and diachronic information about concepts and words. This paper
introduces GraphBRAIN technology and describes our model for time-sensitive linguistic data. Moreover, we provide an example of usage and show the potential of this model for humanities and cultural heritage research.

Original language	English
Title of host publication	Proceedings of the 1st Workshop on Artificial Intelligence for Cultural Heritage co-located with the 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022)
Publisher	CEUR Workshop Proceedings
Pages	69
Number of pages	80
Publication status	Published - 28 Nov 2022

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Basile, P., Cassotti, P., Ferilli, S., & McGillivray, B. (2022). A New Time-sensitive Model of Linguistic Knowledge for Graph Databases. In Proceedings of the 1st Workshop on Artificial Intelligence for Cultural Heritage co-located with the 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022) (pp. 69). CEUR Workshop Proceedings. https://ceur-ws.org/Vol-3286/08_paper.pdf

Basile, Pierpaolo ; Cassotti, Pierluigi ; Ferilli, Stefano et al. / A New Time-sensitive Model of Linguistic Knowledge for Graph Databases. Proceedings of the 1st Workshop on Artificial Intelligence for Cultural Heritage co-located with the 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022). CEUR Workshop Proceedings, 2022. pp. 69

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abstract = "Graph databases are a straightforward technology for storing knowledge graphs. However, they are schema-less. We apply the GraphBRAIN Schema (GBS) format to describe Time-sensitive Linguistic Knowledge in a graph database (Neo4j). Our schema can model relations between concepts and words, information about word occurrences, and diachronic information about concepts and words. This paperintroduces GraphBRAIN technology and describes our model for time-sensitive linguistic data. Moreover, we provide an example of usage and show the potential of this model for humanities and cultural heritage research.",

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Basile, P, Cassotti, P, Ferilli, S & McGillivray, B 2022, A New Time-sensitive Model of Linguistic Knowledge for Graph Databases. in Proceedings of the 1st Workshop on Artificial Intelligence for Cultural Heritage co-located with the 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022). CEUR Workshop Proceedings, pp. 69. <https://ceur-ws.org/Vol-3286/08_paper.pdf>

A New Time-sensitive Model of Linguistic Knowledge for Graph Databases. / Basile, Pierpaolo; Cassotti, Pierluigi; Ferilli, Stefano et al.
Proceedings of the 1st Workshop on Artificial Intelligence for Cultural Heritage co-located with the 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022). CEUR Workshop Proceedings, 2022. p. 69.

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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AB - Graph databases are a straightforward technology for storing knowledge graphs. However, they are schema-less. We apply the GraphBRAIN Schema (GBS) format to describe Time-sensitive Linguistic Knowledge in a graph database (Neo4j). Our schema can model relations between concepts and words, information about word occurrences, and diachronic information about concepts and words. This paperintroduces GraphBRAIN technology and describes our model for time-sensitive linguistic data. Moreover, we provide an example of usage and show the potential of this model for humanities and cultural heritage research.

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BT - Proceedings of the 1st Workshop on Artificial Intelligence for Cultural Heritage co-located with the 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022)

PB - CEUR Workshop Proceedings

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A New Time-sensitive Model of Linguistic Knowledge for Graph Databases

Abstract

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