Graph-Query Suggestions for Knowledge Graph Exploration

Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

26 Citations (Scopus)
301 Downloads (Pure)

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.

Original languageEnglish
Title of host publicationThe Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020
Number of pages7
PublisherAssociation for Computing Machinery (ACM)
Publication date20 Apr 2020
Pages2549-2555
ISBN (Electronic)9781450370233
DOIs
Publication statusPublished - 20 Apr 2020
Event29th International World Wide Web Conference, WWW 2020 - Taipei, Taiwan, Province of China
Duration: 20 Apr 202024 Apr 2020

Conference

Conference29th International World Wide Web Conference, WWW 2020
Country/TerritoryTaiwan, Province of China
CityTaipei
Period20/04/202024/04/2020
SponsorChunghwa Telecom, et al., Microsoft USA, Quanta Computer, Taiwan Mobile, ZOOM

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