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Multi-view Ensemble Learning for Poem Data Classification Using SentiWordNet

Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 27)

Abstract

Poem is a piece of writing in which the expression of feeling and ideas is given intensity by particular attention to diction, rhythm and imagery [1]. In this modern age, the poem collection is ever increasing on the internet. Therefore, to classify poem correctly is an important task. Sentiment information of the poem is useful to enhance the classification task. SentiWordNet is an opinion lexicon. To each term are assigned two numeric scores indicating positive and negative sentiment information. Multiple views of the poem data may be utilized for learning to enhance the classification task. In this research, the effect of sentiment information has been explored for poem data classification using Multi-view ensemble learning. The experiments include the use of Support Vector Machine (SVM) for learning classifier corresponding to each view of the data.

Keywords

Classification Multi-view Ensemble Learning Poem SentiWordNet 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.School of Computer and Systems SciencesJawaharlal Nehru UniversityNew DelhiIndia

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