Knowledge graphs (KGs) are a useful source of background knowledge to (dis)prove facts of the form (s, p, o). The goal of this paper is to present the Fact checking via path Embedding and Aggregation (FEA) system. FEA starts by carefully collecting the paths between s and o that are most semantically related to the domain of p. It learns vectorized path representations, aggregates them according to different strategies, and use them to finally (dis)prove a fact. Our experiments show that our hybrid solution brings benefits in terms of performance.
Fact-checking via path embedding and aggregation / Pirro', Giuseppe. - 2722:(2020), pp. 149-158. (Intervento presentato al convegno 2020 Advances in Semantics and Linked Data, ASLD 2020 and Joint Workshops AI4LEGAL 2020, NLIWOD, PROFILES 2020, QuWeDa 2020 and SEMIFORM 2020 tenutosi a Athen).
Fact-checking via path embedding and aggregation
Pirro' Giuseppe
2020
Abstract
Knowledge graphs (KGs) are a useful source of background knowledge to (dis)prove facts of the form (s, p, o). The goal of this paper is to present the Fact checking via path Embedding and Aggregation (FEA) system. FEA starts by carefully collecting the paths between s and o that are most semantically related to the domain of p. It learns vectorized path representations, aggregates them according to different strategies, and use them to finally (dis)prove a fact. Our experiments show that our hybrid solution brings benefits in terms of performance.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
