SmartBullets: A Cloud-Assisted Bullet Screen Filter based on Deep Learning

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Bullet-screen is a technique that enables the website users to send real-time comment 'bullet' cross the screen. Since all the comments are shown on the screen publicly and simultaneously, low-quality bullets will reduce the watching enjoyment of the users. In this paper, we present SmartBullets, a user-centered bullet-screen filter based on deep learning techniques. A convolutional neural network is trained as the classifier to remove low-quality bullet comments. Moreover, to increase the scalability of our model, we employ a cloud-assisted framework by developing a backend cloud server and a front-end browser extension. We evaluate our framework with forty volunteers and the result shows that our framework can effectively remove the low-quality bullets and improve the overall watching experience of viewers.

Original languageEnglish
Title of host publicationICCCN 2020 - 29th International Conference on Computer Communications and Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728166070
DOIs
StatePublished - Aug 2020
Externally publishedYes
Event29th International Conference on Computer Communications and Networks, ICCCN 2020 - Honolulu, United States
Duration: Aug 3 2020Aug 6 2020

Publication series

NameProceedings - International Conference on Computer Communications and Networks, ICCCN
Volume2020-August
ISSN (Print)1095-2055

Conference

Conference29th International Conference on Computer Communications and Networks, ICCCN 2020
Country/TerritoryUnited States
CityHonolulu
Period08/3/2008/6/20

Keywords

  • bullet-screen
  • comment filtering
  • danmaku
  • natural language processing

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