Extracting repeater knowledge from citizen report data | Zendy

Eiji Kano | Zendy; Kazuhiko Tsuda | Zendy

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Extracting repeater knowledge from citizen report data

Author(s) -

Eiji Kano,

Kazuhiko Tsuda

Publication year - 2020

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.2020.09.240

Subject(s) - computer science , citizen science , repeater (horology) , data science , knowledge management , artificial intelligence , botany , encoding (memory) , biology

As citizen report systems are introduced in municipalities worldwide, research on extracting knowledge useful for resolving local issues from accumulated citizen report data is being actively promoted. However, to utilize this knowledge in practice, clarifying the characteristics of the participating reporters and the bias caused by them is necessary. This study focuses on repeat reporters who play an important role and extracts knowledge regarding their behavioral characteristics from citizen report data.

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