Negative Correlation Discovery for Big Multimedia Data Semantic Concept Mining and Retrieval

Yilin Yan, Mei-Ling Shyu, Qiusha Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

With massive amounts of data producing each day in almost every field, traditional data processing techniques have become more and more inadequate. However, the research of effectively managing and retrieving these big data is still under development. Multimedia high-level semantic concept mining and retrieval in big data is one of the most challenging research topics, which requires joint efforts from researchers in both big data mining and multimedia domains. In order to bridge the semantic gap between high-level concepts and low-level visual features, correlation discovery in semantic concept mining is worth exploring. Meanwhile, correlation discovery is a computationally intensive task in the sense that it requires a deep analysis of very large and growing repositories. This paper presents a novel system of discovering negative correlation for semantic concept mining and retrieval. It is designed to adapt to Hadoop MapReduce framework, which is further extended to utilize Spark, a more efficient and general cluster computing engine. The experimental results demonstrate the feasibility of utilizing big data technologies in negative correlation discovery.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 10th International Conference on Semantic Computing, ICSC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages55-62
Number of pages8
ISBN (Print)9781509006618
DOIs
StatePublished - Mar 22 2016
Event10th IEEE International Conference on Semantic Computing, ICSC 2016 - Laguna Hills, United States
Duration: Feb 3 2016Feb 5 2016

Other

Other10th IEEE International Conference on Semantic Computing, ICSC 2016
CountryUnited States
CityLaguna Hills
Period2/3/162/5/16

Keywords

  • Big Data
  • Hadoop
  • Information Integration
  • MapReduce
  • Multimedia Semantic Mining and Retrieval
  • Negative Correlation
  • Spark

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Yan, Y., Shyu, M-L., & Zhu, Q. (2016). Negative Correlation Discovery for Big Multimedia Data Semantic Concept Mining and Retrieval. In Proceedings - 2016 IEEE 10th International Conference on Semantic Computing, ICSC 2016 (pp. 55-62). [7439305] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSC.2016.73