Application of Clustering Algorithm CLOPE to the Query Grouping Problem in the Field of Materialized View Maintenance

Autor: Kateryna Novokhatska, Oleksii Kungurtsev

Publikováno v: Journal of Computing and Information Technology, Vol 24, Iss 1, Pp 79-89 (2016)

In recent years, materialized views (MVs) are widely used to enhance the database performance by storing pre-calculated results of resource-intensive queries in the physical memory. In order to identify which queries may be potentially materialized,

Externí odkaz: https://doaj.org/article/0b1c4e1395b64e69b3c5d9a951132bec

Improving CLOPE’s Profit Value and Stability with an Optimized Agglomerative Approach

Autor: Yefeng Li, Jiajin Le, Mei Wang

Publikováno v: Algorithms, Vol 8, Iss 3, Pp 380-394 (2015)

CLOPE (Clustering with sLOPE) is a simple and fast histogram-based clustering algorithm for categorical data. However, given the same data set with the same input parameter, the clustering results by this algorithm would possibly be different if the

Externí odkaz: https://doaj.org/article/13321226cb364e3db5dba3eea2120b13

Development of the model and method of selecting the description of rational architecture of information system

Publikováno v: Eastern-European Journal of Enterprise Technologies; Том 1, № 2(79) (2016): Information technology. Industry control systems; 4-12
Восточно-Европейский журнал передовых технологий; Том 1, № 2(79) (2016): Информационные технологии. Системы управления в промышленности; 4-12
Східно-Європейський журнал передових технологій; Том 1, № 2(79) (2016): Інформаційні технології. Системи управління в промисловості; 4-12

Рассмотрена задача разработки модели и метода выбора варианта описания рациональной архитектуры информационной системы. Разработанны

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=scientific_p::08a5ba0490eb1592e96776f3e69ada4b
http://journals.uran.ua/eejet/article/view/60583

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Filtering Social Tags for Songs based on Lyrics using Clustering Methods

Autor: Chawla, Rahul

Publikováno v: Open Access Theses.

In the field of Music Data Mining, Mood and Topic information has been considered as a high level metadata. The extraction of mood and topic information is difficult but is regarded as very valuable. The immense growth of Web 2.0 resulted in Social T

Externí odkaz: http://scholarlyrepository.miami.edu/oa_theses/272