Effective Data Mining Techniques for Unstructured Data in Big Data

di Dnyandeo Khemnar (Autore)

Nilesh Thorat (Autore)

GRIN Verlag, 2022

Master's Thesis from the year 2017 in the subject Computer Science - Applied, grade: 10, Rajiv Gandhi University (PATEL COLLEGE OF SCIENCE AND TECHNOLOGY), course: COMPUTER SCIENCE, language: English, abstract: In this paper I collect healthcare data, which consists of all the details of the patients' symptoms, disease etc. After the collection of data, there will be pre-processing on all the details of the patients' data, as we need only filtered data for our analysis. The data will be stored in Hadoop. A user can retrieve the data by symptoms, disease etc. Big Data is a collection of large and complex data. It consists of structured, semi-structured, and unstructured types of data. Data gets generated from various sources and from different fields. In today's era, data is being generated in huge amounts. The whole world is moving towards the digitalization. Social media sites, digital pictures and videos, and many others. All this type of data is known as big data. Data mining is a useful technique for extracting a pattern. This is helpful from large scale data sets. Useful and meaningful data can be extracted from this big data with the help of data mining by processing on that data.

• Autore: Dnyandeo Khemnar, Nilesh Thorat
• Anno edizione: 2022
• Editore: GRIN Verlag
• Formato: EPUB2 con Adobe DRM
• Lingua: Inglese
• Compatibilità: Tutti i dispositivi (eccetto Kindle)
• Layout: Reflowable
• EAN: 9783346783394