Fast text classification with Naive Bayes method on Apache Spark
Yazarlar (3)
İskender Ülgen Oğul
Karabük Üniversitesi, Türkiye
Doç. Dr. Caner ÖZCAN Karabük Üniversitesi, Türkiye
Özlem Hakdağlı
Karabük Üniversitesi, Türkiye
Bildiri Türü Tebliğ/Bildiri Bildiri Dili Türkçe
Bildiri Alt Türü Tam Metin Olarak Yayınlanan Tebliğ (Ulusal Kongre/Sempozyum)
Bildiri Niteliği Web of Science Kapsamındaki Kongre/Sempozyum
DOI Numarası 10.1109/SIU.2017.7960721
Kongre Adı 25. IEEE SİNYAL İŞLEME ve İLETİŞİM UYGULAMALARI KURULTAYI
Kongre Tarihi 15-05-2017 / 18-05-2017
Basıldığı Ülke Türkiye Basıldığı Şehir Antalya
Bildiri Linki http://dx.doi.org/10.1109/siu.2017.7960721
UAK Araştırma Alanları
Görüntü İşleme
Özet
The increase in the number of devices and users online with the transition of Internet of Things (IoT), increases the amount of large data exponentially. Classification of ascending data, deletion of irrelevant data, and meaning extraction have reached vital importance in today's standards. Analysis can be done in various variations such as Classification of text on text data, analysis of spam, personality analysis. In this study, fast text classification was performed with machine learning on Apache Spark using the Naive Bayes method. Spark architecture uses a distributed in-memory data collection instead of a distributed data structure presented in Hadoop architecture to provide fast storage and analysis of data. Analyzes were made on the interpretation data of the Reddit which is open source social news site by using the Naive Bayes method. The results are presented in tables and graphs.
Anahtar Kelimeler
Apache Spark | Big data | Classification | Machine learning | Naive Bayes | Text mining
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Web of Science 3
Scopus 7
Google Scholar 10
Fast text classification with Naive Bayes method on Apache Spark

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