Graph-Query Suggestions for Knowledge Graph Exploration

Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis

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.

Presented online see the program

Cite:

and
Graph-Query Suggestions for Knowledge Graph Exploration.”
Proceedings of the World Wide Web Conference (WWW 2020) (pp. 809-820).