Evaluation of Data Similarity using Data Jackets based on Users’ Recognition | Zendy

Nao Uehara | Zendy; Teruaki Hayashi | Zendy; Yukio Ohsawa | Zendy

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Evaluation of Data Similarity using Data Jackets based on Users’ Recognition

Author(s) -

Nao Uehara,

Teruaki Hayashi,

Yukio Ohsawa

Publication year - 2019

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2019.09.354

Subject(s) - computer science , similarity (geometry) , information retrieval , data mining , nearest neighbor search , pattern recognition (psychology) , artificial intelligence , image (mathematics)

Data jacket (DJ) emerged as a method to make use of data without revealing any actual content. In a DJ Store, one can search DJs, and learn the types of solution these DJs are used for. In this study, we propose a model that calculates and acquires similar DJs under the assumption that it may be used for similar solutions by acquiring DJs that are similar to a certain DJ. The experimental results show that the similarity model generated by the proposed method is the model that most reflects the similarity of the DJ’s outline.

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