We consider the task of exploratory search through graph queries on knowledge graphs. We propose to assist the user by expanding the query with intuitive suggestions to provide a more informative (full) query that can retrieve more detailed and relevant answers. To achieve this result, we propose a model that can bridge graph search paradigms with well-established techniques for information-retrieval. Our approach does not require any additional knowledge from the user and builds on principled language modelling approaches. We empirically show the effectiveness and efficiency of our approach on a large knowledge graph and how our suggestions are able to help build more complete and informative queries.
Graph-Query Suggestions for Knowledge Graph Exploration / Lissandrini, Matteo; Mottin, Davide; Palpanas, Themis; Velegrakis, Ioannis. - (2020), pp. 2549-2555. (Intervento presentato al convegno 29th International World Wide Web Conference, WWW 2020 tenutosi a Taipei Taiwan nel April 20 - 24, 2020) [10.1145/3366423.3380005].
Graph-Query Suggestions for Knowledge Graph Exploration
Lissandrini, Matteo;Mottin, Davide;Palpanas, Themis;Velegrakis Yannis
2020-01-01
Abstract
We consider the task of exploratory search through graph queries on knowledge graphs. We propose to assist the user by expanding the query with intuitive suggestions to provide a more informative (full) query that can retrieve more detailed and relevant answers. To achieve this result, we propose a model that can bridge graph search paradigms with well-established techniques for information-retrieval. Our approach does not require any additional knowledge from the user and builds on principled language modelling approaches. We empirically show the effectiveness and efficiency of our approach on a large knowledge graph and how our suggestions are able to help build more complete and informative queries.File | Dimensione | Formato | |
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