Abstract
Entity tasks, such as linking, integration, and translation, are crucial for many search and NLP applications. For this purposed entity graphs have been manually built or automatically harvested. In this paper, we survey existing approaches abstracting these problems into a graph-based iterative matching on a pair of entity graphs.
Original language | English |
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Title of host publication | TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 248-255 |
Number of pages | 8 |
ISBN (Electronic) | 9781509057320 |
DOIs | |
Publication status | Published - 2017 Mar 16 |
Event | 2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016 - Hsinchu, Taiwan, Province of China Duration: 2016 Nov 25 → 2016 Nov 27 |
Publication series
Name | TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings |
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Other
Other | 2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016 |
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Country/Territory | Taiwan, Province of China |
City | Hsinchu |
Period | 16/11/25 → 16/11/27 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Control and Optimization
- Information Systems