Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная
The Solution of the Profiling Problem Based on Data Analysis. / Busarov, Vyacheslav; Grafeeva, Natalia.
The Solution of the Profiling Problem Based on Data Analysis. 2016. стр. 307-312.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная
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TY - GEN
T1 - The Solution of the Profiling Problem Based on Data Analysis
AU - Busarov, Vyacheslav
AU - Grafeeva, Natalia
PY - 2016
Y1 - 2016
N2 - This article describes the problem of profiling of objects with varied characteristics. This is relevant for today task, which requires working with large amounts of data and cannot be solved manually. In this paper we describe a solution based on search algorithms of frequent itemsets. The article also presents the results of a comparative analysis of the algorithms (which was the subject of a separate research). The main focus of the article is aimed at substantiation of the choice of an appropriate algorithm based on some characteristic of the source dataset. The study is based on work with actual data of the restaurant industry. Despite this, the results have a wide application, as the approach described in this article can easily be generalized to datasets in any other industry. This article is a logical continuation of the article [5].
AB - This article describes the problem of profiling of objects with varied characteristics. This is relevant for today task, which requires working with large amounts of data and cannot be solved manually. In this paper we describe a solution based on search algorithms of frequent itemsets. The article also presents the results of a comparative analysis of the algorithms (which was the subject of a separate research). The main focus of the article is aimed at substantiation of the choice of an appropriate algorithm based on some characteristic of the source dataset. The study is based on work with actual data of the restaurant industry. Despite this, the results have a wide application, as the approach described in this article can easily be generalized to datasets in any other industry. This article is a logical continuation of the article [5].
KW - Data mining Frequent itemsets Profiling problem
M3 - Conference contribution
SN - 978-952-68397-5-2
SP - 307
EP - 312
BT - The Solution of the Profiling Problem Based on Data Analysis
ER -
ID: 7624791