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@article{(International Science Index):http://waset.org/publications/10006151,
  title    = {Neuro-Fuzzy Based Model for Phrase Level Emotion Understanding},
  author    = {Vadivel Ayyasamy},
  country   = {India},
  institution={National Institute of Technology Trichy},
  abstract  = {The present approach deals with the identification of Emotions and classification of Emotional patterns at Phrase-level with respect to Positive and Negative Orientation. The proposed approach considers emotion triggered terms, its co-occurrence terms and also associated sentences for recognizing emotions. The proposed approach uses Part of Speech Tagging and Emotion Actifiers for classification. Here sentence patterns are broken into phrases and Neuro-Fuzzy model is used to classify which results in 16 patterns of emotional phrases. Suitable intensities are assigned for capturing the degree of emotion contents that exist in semantics of patterns. These emotional phrases are assigned weights which supports in deciding the Positive and Negative Orientation of emotions. The approach uses web documents for experimental purpose and the proposed classification approach performs well and achieves good F-Scores.
},
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {11},
  number    = {1},
  year      = {2017},
  pages     = {53 - 59},
  ee        = {http://waset.org/publications/10006151},
  url       = {http://waset.org/Publications?p=121},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 121, 2017},
}