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 language | English |
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Title of host publication | The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020 |
Number of pages | 7 |
Publisher | Association for Computing Machinery (ACM) |
Publication date | 20 Apr 2020 |
Pages | 2549-2555 |
ISBN (Electronic) | 9781450370233 |
DOIs | |
Publication status | Published - 20 Apr 2020 |
Event | 29th International World Wide Web Conference, WWW 2020 - Taipei, Taiwan, Province of China Duration: 20 Apr 2020 → 24 Apr 2020 |
Conference
Conference | 29th International World Wide Web Conference, WWW 2020 |
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Country/Territory | Taiwan, Province of China |
City | Taipei |
Period | 20/04/2020 → 24/04/2020 |
Sponsor | Chunghwa Telecom, et al., Microsoft USA, Quanta Computer, Taiwan Mobile, ZOOM |