FMIC: Finding Most Important Contributors in small companies with diverse projects

Ashkan Sami, Makoto Takahashi, Masaharu Kitamura

研究成果: Paper査読

抄録

This paper presents an approach to find the most important combinations in problems that few members perform several tasks or are in several positions that results in determined number of outcomes. The position of the members regarding to a specific origin must be an important factor. FMIC deploys a special mapping that requires only addition and then based on algorithm similar to basket analysis finds the most important combinations. Speed is the main advantage of the approach. The database is scanned only once. In addition to artificially generated data, FMIC was applied to some DNA data and the algorithm found all the patterns with different support.

本文言語English
ページ471-475
ページ数5
出版ステータスPublished - 2005
イベントSICE Annual Conference 2005 - Okayama, Japan
継続期間: 2005 8月 82005 8月 10

Other

OtherSICE Annual Conference 2005
国/地域Japan
CityOkayama
Period05/8/805/8/10

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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