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.
|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 8 → 2005 8月 10
|Other||SICE Annual Conference 2005|
|Period||05/8/8 → 05/8/10|
ASJC Scopus subject areas
- コンピュータ サイエンスの応用