Efficient personalized probabilistic retrieval of Chinese calligraphic manuscript images in mobile cloud environment

Y. Zhuang, Qing Li, D.K.W. Chiu, Z. Wu, H. Hu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

© 2014 ACM. Ancient language manuscripts constitute a key part of the cultural heritage of mankind. As one of the most important languages, Chinese historical calligraphy work has contributed to not only the Chinese cultural heritage but also the world civilization at large, especially for Asia. To support deeper and more convenient appreciation of Chinese calligraphy works, based on our previous work on the probabilistic retrieval of historical Chinese calligraphic character manuscripts repositories, we propose a system framework of the multi-feature-based Chinese calligraphic character images probabilistic retrieval in the mobile cloud network environment, which is called the DPRC. To ensure retrieval efficiency, we further propose four enabling techniques: (1) DRL-based probability propagation, (2) optimal data placement scheme, (3) adaptive data robust transmission algorithm, and (4) index support filtering scheme. Comprehensive experiments are conducted to testify the effectiveness and efficiency of our proposed DPRC method.
Original languageEnglish
JournalACM Transactions on Asian Language Information Processing
Volume13
Issue number4
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Keywords

  • Chinese calligraphic character
  • Probabilistic retrieval
  • Sentiment

ASJC Scopus subject areas

  • Computer Science(all)

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