Hassan Murtaza

Academic

Career

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Scalable Aggregation of Text using big data tools
ScAT is real-time web based application which aims to save the Reader’s time while simplifying redundant news articles. A user can read news from 2 or more news channel, by doing this he waste a lot of time to study similar news articles. ScAT rectify this problem classifying news articles to provide ease to the Reader . For this we employ big data tool such as Apache Kafka and Apache Spark to streamline the News Articles from different news sources and perform Clustering, Aggregation and Summarization upon them. Fetched articles streamed by kafka and make them readily available for spark engine Processing.  
1-Backend of the System is implemented in python with the help of Apache Kafka and Apache Spark
2-GUI contain web portal which further comprised of two parts
2.1-Blog: It contain category wise Unique News and Similar News Articles in different tabs. Further more summary is also provided of similar news Articles.
2.2-Analytic: It contain graphs which explain the raw and processed text in numerical and graphical form. It provide comprehensive analytic of the text.
















Technology Used:
Python, Pyspark, Apache Kafka, Apache Spark,
Pycharm, Angular and android  
Supervisor Name:
Dr. Kifayat Ullah Khan Alizai
Group Members:   
Mohammad Shahid Shakeel (f17 - 8001)
Asad Arshad (i17 - 0312)
Hassan Murtaza (i17 - 0368)