Faceted interfaces are omnipresent on the web to support data ex- ploration and ltering. A facet is a triple: a domain (e.g., Book), a property (e.g., author,lanдuaдe), and a set of property values (e.g., {Austen,Beauvoir,Coelho,Dostoevsky,Eco,Kerouac,Suskind,...}, {French,Enдlish,German,Italian,Portuдuese,Russian,...}). Given a property (e.g., lanдuaдe), selecting one or more of its values (Enдlish and Italian) returns the domain entities (of type Book) that match the given values (the books that are written in English or Italian). To implement faceted interfaces in a way that is scalable to very large datasets, it is necessary to automate facet extraction. Prior work associates a facet domain with a set of homogeneous values, but does not annotate the facet property. In this paper, we annotate the facet property with a predicate from a reference Knowledge Base (KB) so as to maximize the semantic similarity between the property and the predicate. We define semantic similarity in terms of three new metrics: specificity, coverage, and frequency. Our experimental evaluation uses the DBpedia and YAGO K Bs and shows that for the facet annotation problem, we obtain better results than a state-of-the-art approach for the annotation of web tables as modified to annotate a set of values

Porrini, R., Palmonari, M., Cruz, I. (2018). Facet Annotation Using Reference Knowledge Bases. In WEB CONFERENCE 2018: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW2018) (pp.1215-1224). ACM [10.1145/3178876.3186020].

Facet Annotation Using Reference Knowledge Bases

Riccardo Porrini
Primo
;
Matteo Palmonari
Secondo
;
2018

Abstract

Faceted interfaces are omnipresent on the web to support data ex- ploration and ltering. A facet is a triple: a domain (e.g., Book), a property (e.g., author,lanдuaдe), and a set of property values (e.g., {Austen,Beauvoir,Coelho,Dostoevsky,Eco,Kerouac,Suskind,...}, {French,Enдlish,German,Italian,Portuдuese,Russian,...}). Given a property (e.g., lanдuaдe), selecting one or more of its values (Enдlish and Italian) returns the domain entities (of type Book) that match the given values (the books that are written in English or Italian). To implement faceted interfaces in a way that is scalable to very large datasets, it is necessary to automate facet extraction. Prior work associates a facet domain with a set of homogeneous values, but does not annotate the facet property. In this paper, we annotate the facet property with a predicate from a reference Knowledge Base (KB) so as to maximize the semantic similarity between the property and the predicate. We define semantic similarity in terms of three new metrics: specificity, coverage, and frequency. Our experimental evaluation uses the DBpedia and YAGO K Bs and shows that for the facet annotation problem, we obtain better results than a state-of-the-art approach for the annotation of web tables as modified to annotate a set of values
paper
Facet annotation, data semantics, data lifting, table annotation, faceted search, eCommerce
English
World Wide Web (WWW) Conference APR 23-27
2018
WEB CONFERENCE 2018: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW2018)
978-1-4503-5639-8
2018
1215
1224
reserved
Porrini, R., Palmonari, M., Cruz, I. (2018). Facet Annotation Using Reference Knowledge Bases. In WEB CONFERENCE 2018: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW2018) (pp.1215-1224). ACM [10.1145/3178876.3186020].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/192020
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