The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).

If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Fullscreen Fullscreen Off


Objectives: In this paper, we present an experiment, which concerned with detection of emotion class at sentence level. Methods: Approach is based upon combination of both machine leaning and key word based approach. There is a large annotated data set which manually classified a sentence beyond six basic emotions: love, joy, anger, sadness, fear, surprise. Findings: Using annotated data set define an emotion vector of key word in input sentence. Novelty: Using an algorithm calculate the emotion vector of sentence by emotion vector of word. Then on the basis of emotion vector categorized the sentence into appropriate emotion class. Results are shown and found good in comparison to individual approach.

Keywords

Emotion Detection, Emotion Vecotor, Machine Learning, Natural Language Processing, Sentence Level.
User