Graph-Query Suggestions for Knowledge Graph Exploration
Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis
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.”
Proceedings of the World Wide Web Conference (WWW 2020)