Searching in a library or book catalog is a recurrent task for researchers and common users alike. Thanks to semantic enrichment techniques, such as named-entity recognition and linking, texts may be automatically associated with entities in some reference knowledge graph(s). The association of a corpus of texts with a knowledge graph opens up the way to searching/exploring using novel paradigms. We present a pipeline that uses semantic enrichment and knowledge graph visualization techniques to enable the semantic exploration of an existing text corpus. The pipeline is meant to be ready for use and consists of existing free software tools and free software code contributed by us. We are developing and testing the pipeline on the field, by using it to access the catalog of a bookstore specialized in ancient Rome history.
A Streamlined Pipeline to Enable the Semantic Exploration of a Bookstore
Ceriani M.
Primo
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2020
Abstract
Searching in a library or book catalog is a recurrent task for researchers and common users alike. Thanks to semantic enrichment techniques, such as named-entity recognition and linking, texts may be automatically associated with entities in some reference knowledge graph(s). The association of a corpus of texts with a knowledge graph opens up the way to searching/exploring using novel paradigms. We present a pipeline that uses semantic enrichment and knowledge graph visualization techniques to enable the semantic exploration of an existing text corpus. The pipeline is meant to be ready for use and consists of existing free software tools and free software code contributed by us. We are developing and testing the pipeline on the field, by using it to access the catalog of a bookstore specialized in ancient Rome history.| File | Dimensione | Formato | |
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978-3-030-39905-4_8.pdf
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Descrizione: Ceriani, M., Bernasconi, E., Mecella, M. (2020). A Streamlined Pipeline to Enable the Semantic Exploration of a Bookstore. In: Ceci, M., Ferilli, S., Poggi, A. (eds) Digital Libraries: The Era of Big Data and Data Science. IRCDL 2020. Communications in Computer and Information Science, vol 1177. Springer, Cham. https://doi.org/10.1007/978-3-030-39905-4_8
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