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, M.;
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.
2020
9781450370233
data management, data exploration, knowledge graph
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1115701
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