Akan veri kümeleme probleminde ağaç veri yapılarının performans karşılaştırması

Teknolojideki gelişmeler, insanların pek çok farklı kaynakta üretilen verileri toplamasına ve analiz etmesine imkân tanımıştır. Sensörler, mobil cihazlar, nesnelerin interneti gibi yapılarda üretilen veriler akan veri formatında olup, bu tür verilerden işlenerek faydalı bilgilerin elde edilmesi zor bir problemdir. Akan verileri analiz etmek için sıklıkla kullanılan yöntemlerden birisi olan kümelemede, veriler dağılımlarına göre çeşitli gruplara ayrılarak analiz edilir. Bu çalışmada, akan veri kümeleme problemi için iki yeni algoritma geliştirilerek literatürdeki başka bir yöntemle karşılaştırılmıştır. Farklı veri kümeleri üzerinde yapılan deneyler neticesinde, geliştirilen algoritmaların iyi sonuçlar verdiği görülmüştür.

Anahtar Kelimeler:

akan veri, kümeleme, ağaç veri yapıları

A comparison of tree data structures in the streaming data clustering issue

Advances in technology have allowed people to collect data produced in many different sources and analyze it. The data collected from sensors, mobile devices, and the internet of things are in the form of streaming data, and it is a hard problem to obtain useful information from such data. In clustering which is one of the most frequently used methods to analyze streaming data, data is analyzed by dividing them into various groups according to their distribution. In this study, two new algorithms in streaming data clustering were developed and compared with another clustering algorithm in the literature. As a result, the algorithms developed gave successful results on different datasets.

Keywords:

streaming data, clustering, tree data structure.,

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