Opinion Mining Based on People’s Feedback About Engineering Degree

  • M. Karpagam
  • S. Kanthimathi
  • S. Akila
  • S. Kanimozhi SugunaEmail author
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 44)


Support Vector Machine (SVM) is a learning model which can be used as data analyzer for classification by its associated algorithms. SVM classifies the data by finding the hyper-plane that maximizes the gap between two classes. The structure of decision tree consists of root, branches and leaf nodes and the tests performed on an attribute and leaf nodes were represented by internal nodes which denote the result of the test. In this paper, a model to classify data using an ensemble of decision tree and support vector machine is proposed on a dataset collected on the topic of ‘Engineering Degree’. Combining the decision tree and support vector machine can be an effective method for classifying the data as it reduces the testing and training time of the data collected. The analysis of the result has been performed on a sample set of data taken from a large collection stored in the cloud using Hadoop.


Support vector machine (SVM) Decision tree algorithm Classification Hadoop hive Engineering degree 


Compliance with Ethical Standards

All author states that there is no conflict of interest. We used our own data. Humans/animals are not involved in this research work.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • M. Karpagam
    • 1
  • S. Kanthimathi
    • 1
  • S. Akila
    • 1
  • S. Kanimozhi Suguna
    • 1
    Email author
  1. 1.School of ComputingSASTRA Deemed UniversityThanjavurIndia

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