EmotionC: A Novel Framework for Emotion Detection Using Personalized Search Engine

In the days of the Modern era, searching or browsing through the Internet has been a part of our daily life. For example, if a person feels happy then he searches for a good movie or a song, if a person wants to commit suicide he searches the easy ways to commit suicide. The average person uses a browser for three to four times a day. So, detecting emotion by a person's search history could yield us the Emotional condition of a person. The existing search engines give us better results when the complete query is entered, hence it requires personalization to obtain better results with less input. In this paper, using ontology the users are segregated into different categories based on the emotion yielded. Also, each query is segregated into their respective category of emotion using clustering. Moreover, the privacy issue is addressed here by restricting the information only to the user profile. Finally, the user search history is tracked and based on the search history the emotion of a user will be detected.