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meCurate: Personalized Curation Service using a Tiny Text Intelligence

Published: 03 April 2017 Publication History

Abstract

The necessity and importance of intelligent content curation have been demanding, as exemplified by Google Photos and Inbox. In this demo, we demonstrate a personalized curation service on a smartphone, called meCurate. By understanding implicit user interests from user smartphone usage data, meCurate intelligently organizes both in-device user content (e.g., SMSs and bookmarks) and external content (e.g., news articles crawled from The New York Times website), which are likely to match the inferred user's interests. In addition, meCurate retrieves semantically relevant in-device user content and external content to an explicit text or voice query. To this end, we utilize a tiny text intelligence which is suitable for smartphones with limited resources. Notably, meCurate works in a stand-alone, privacy-protecting manner without sending out any in-device personal data or content, resulting in a unique user experience.

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Cited By

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  • (2020)Data DashboardProceedings of the 2020 ACM Designing Interactive Systems Conference10.1145/3357236.3395457(311-326)Online publication date: 3-Jul-2020
  • (2019)From Small-scale to Large-scale Text ClassificationThe World Wide Web Conference10.1145/3308558.3313563(853-862)Online publication date: 13-May-2019
  • (2019)meChatProceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3307334.3328568(655-656)Online publication date: 12-Jun-2019
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Published In

cover image ACM Other conferences
WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion
April 2017
1738 pages
ISBN:9781450349147

Sponsors

  • IW3C2: International World Wide Web Conference Committee

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Publisher

International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 03 April 2017

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Author Tags

  1. personalized curation
  2. semantic search
  3. tiny text intelligence
  4. user understanding

Qualifiers

  • Demonstration

Funding Sources

  • National Research Foundation of Korea

Conference

WWW '17
Sponsor:
  • IW3C2

Acceptance Rates

WWW '17 Companion Paper Acceptance Rate 164 of 966 submissions, 17%;
Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

View all
  • (2020)Data DashboardProceedings of the 2020 ACM Designing Interactive Systems Conference10.1145/3357236.3395457(311-326)Online publication date: 3-Jul-2020
  • (2019)From Small-scale to Large-scale Text ClassificationThe World Wide Web Conference10.1145/3308558.3313563(853-862)Online publication date: 13-May-2019
  • (2019)meChatProceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3307334.3328568(655-656)Online publication date: 12-Jun-2019
  • (2019)meChat: In-Device Personal Assistant for Conversational Photo SharingIEEE Internet Computing10.1109/MIC.2018.288305923:2(23-30)Online publication date: 1-Mar-2019
  • (2017)MoCA+: incorporating user modeling into mobile contextual advertisingProceedings of the 18th ACM/IFIP/USENIX Middleware Conference: Posters and Demos10.1145/3155016.3155022(21-22)Online publication date: 11-Dec-2017
  • (2017)sigInterfaceProceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers10.1145/3123024.3123137(185-188)Online publication date: 11-Sep-2017
  • (2017)DemoProceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3081333.3089329(184-184)Online publication date: 16-Jun-2017
  • (2017)DemoProceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3081333.3089326(181-181)Online publication date: 16-Jun-2017

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