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Exquisitor at the Lifelog Search Challenge 2019

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 7-11 (5 pages)

Publication milestones

  • Published - 06/2019

Publication status

Published - 06/2019

Place of publication

Ottawa, Canada

Publisher

Association for Computing Machinery, United States

ISBN (Electronic)

978-1-4503-6781-3

Publication IDs

  • Scopus: 85067972838

Host publication title

Proceedings of the ACM Workshop on Lifelog Search Challenge, LSC@ICMR 2019

Abstract

Interactive learning is an umbrella term for methods that attempt to understand the information need of the user and formulate queries that satisfy that information need. We propose to apply the state of the art in interactive multimodal learning to visual lifelog exploration and search, using the Exquisitor system. Exquisitor is a highly scalable interactive learning system, which uses semantic features extracted from visual content and text to suggest relevant media items to the user, based on user relevance feedback on previously suggested items. Findings from our initial experiments indicate that interactive multimodal learning will likely work well for some LSC tasks, but also suggest some potential enhancements.

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Citations
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Captures
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