POWER: A domain-independent algorithm for Probabilistic, Open-World Entity Resolution-Reference-Cited by-同舟云学术

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POWER: A domain-independent algorithm for Probabilistic, Open-World Entity Resolution

Published:2015-09 Issue: Volume: Page:
ISSN:
Container-title:2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Williams Tom,Scheutz Matthias

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7347169/7353104/07353526.pdf?arnumber=7353526

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. (Gestures Vaguely): The Effects of Robots' Use of Abstract Pointing Gestures in Large-Scale Environments;Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction;2024-03-11

2. Failure Explanation in Privacy-Sensitive Contexts: An Integrated Systems Approach;2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN);2023-08-28

3. The Eye of the Robot Beholder;Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction;2023-03-13

4. AI in Industry Today;Artificial Intelligence for Industries of the Future;2022-09-24

5. A Task Design for Studying Referring Behaviors for Linguistic HRI;2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI);2022-03-07

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