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A personalized cloud engine for multimedia search based on binary ant colony algorithm

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Abstract

At present, the search content and results of common multimedia search engines have gradually failed to meet the personalized search requirements of users. The paper focuses on personalized cloud search engines for multimedia. First, the binary ant colony algorithm is optimized by the cloud model. Then, the binary ant colony algorithm is used to improve the multimedia search engine. Detailedly, a binary directed graph for ant colony traversal is designed in which each ant traverses its own path, and the solution traverses by each ant is integrated to solve the problem. Experiments show that the proposed method effectively improves the query speed of personalized multimedia search engines, reduces redundant information, and improves the user search experience.

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Acknowledgements

This paper is funded by following projects: National Natural Science Foundation of China (No. 7156303, No. 61741509); Project of Inner Mongolia Educational Department (NJZY015).

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Authors and Affiliations

  1. Ordos Institute of Technology, Ordos, 017000, China

    Tao Jin & Haijun Wang

  2. Department of Industrial Engineering and Engineering Management, Western New England University, Springfield, MA, 01119, USA

    Zhaojun (Steven) Li

Authors
  1. Tao Jin
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  2. Haijun Wang
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  3. Zhaojun (Steven) Li
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Correspondence to Zhaojun (Steven) Li.

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Jin, T., Wang, H. & Li, Z.(. A personalized cloud engine for multimedia search based on binary ant colony algorithm. Multimed Tools Appl 79, 16487–16499 (2020). https://doi.org/10.1007/s11042-019-7372-3

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