In this demo paper, we present ARCA, a visual-search based system that allows the semantic exploration of a bookstore. Navigating a domain-specific knowledge graph, students and researchers alike can start from any specific concept and reach any other related concept, discovering associated books and information. To achieve this paradigm of interaction we built a prototype system, flexible and adaptable to multiple contexts of use, that extracts semantic information from the contents of a books' corpus, building a dedicated knowledge graph that is linked to external knowledge bases. The web-based user interface of ARCA integrates text-based search, visual knowledge graph navigation, and linear visualization of filtered books (ordered according to multiple criteria) in a comprehensive coordinated view aimed at exploiting the underlying data while avoiding information overload and unnecessary cluttering. A proof-of-concept of ARCA is available online at http://arca.diag.uniroma1.it

ARCA. Semantic exploration of a bookstore

Ceriani M.;
2020-01-01

Abstract

In this demo paper, we present ARCA, a visual-search based system that allows the semantic exploration of a bookstore. Navigating a domain-specific knowledge graph, students and researchers alike can start from any specific concept and reach any other related concept, discovering associated books and information. To achieve this paradigm of interaction we built a prototype system, flexible and adaptable to multiple contexts of use, that extracts semantic information from the contents of a books' corpus, building a dedicated knowledge graph that is linked to external knowledge bases. The web-based user interface of ARCA integrates text-based search, visual knowledge graph navigation, and linear visualization of filtered books (ordered according to multiple criteria) in a comprehensive coordinated view aimed at exploiting the underlying data while avoiding information overload and unnecessary cluttering. A proof-of-concept of ARCA is available online at http://arca.diag.uniroma1.it
9781450375351
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/359714
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