Effective Stream Analysis with Different Technologies

OData support
Supervisor:
Dr. Ekler Péter
Department of Automation and Applied Informatics

This task is about designing and implementing processes of a system that is able to collect and analyze news from online sources. The aim of the task is to find out how positive and negative the collected data is. The task includes getting familiar with popular data analytic systems, server side development, and creation of a client software.

The main result of the task is a website. The user can search for keywords to get the result of the analysis. This website shows if a keyword is a positive or a negative phrase according to the streams and also displays the news what the analysis was based on.

These days the analyses are important because of the size of data from streams. The analyzed data is compressed and keeps only the relevant information about the source data. The sentiment analysis helps to store less data from the original source with collecting more relevant informations about the text that other analyse do not include. This makes the sentiment analysis one of the most popular area of BigData.

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