Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Keyword Selection for Visual Search based on Wikipedia

비주얼 검색을 위한 위키피디아 기반의 질의어 추출

  • Kim, Jongwoo (Dept, of Computer Science and Engineering., Inha University) ;
  • Cho, Soosun (Dept. of Computer Science & Information Eng., Korea National University of Transportation)
  • Received : 2018.07.10
  • Accepted : 2018.07.25
  • Published : 2018.08.31
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Abstract

The mobile visual search service uses a query image to acquire linkage information through pre-constructed DB search. From the standpoint of this purpose, it would be more useful if you could perform a search on a web-based keyword search system instead of a pre-built DB search. In this paper, we propose a representative query extraction algorithm to be used as a keyword on a web-based search system. To do this, we use image classification labels generated by the CNN (Convolutional Neural Network) algorithm based on Deep Learning, which has a remarkable performance in image recognition. In the query extraction algorithm, dictionary meaningful words are extracted using Wikipedia, and hierarchical categories are constructed using WordNet. The performance of the proposed algorithm is evaluated by measuring the system response time.

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References

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