Question-Answering for Agricultural Open Data

In the agricultural sector, the improvement of productivity and quality with respect to such attributes as safety, security and taste has been required in recent years. We aim to contribute to such improvement through the application of Information and Communication Technology (ICT). In this paper, we first propose a model of agricultural knowledge by Linked Open Data (LOD) with a view to establishing an open standard for agricultural data, allowing flexible schemas based on ontology alignment. We also present a semi-automatic mechanism that we developed to extract agricultural knowledge from the Web, which involves a bootstrapping method and dependency parsing, and confirmed a certain degree of accuracy. Moreover, we present a voice-controlled question-answering system that we developed for the LOD using triplification of query sentences and graph pattern matching of the triples. Finally, we confirm through a use case that users can obtain the necessary knowledge for several problems encountered in the agricultural workplace.