الفهرس 
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Abstract
Human-machine interface technology has been investigated for several
decades. Recent research has placed more emphasis on the recognition
of nonverbal information and has especially focused on emotion reaction. Many kinds of physiological characteristics are used to extract
emotions, such as voice, facial expressions, hand gestures, body
movements, heartbeat and blood pressure. Scientists have found that
emotion technology can be an important component in artificial intelligence, especially for human-human communication. Although human-computer interaction IS different from human-human communication, some theories show that human-computer interaction
shares basic characteristics with human-human interaction [Reeves et al.
1996]. In addition, affective information is pervasive in electronic
documents such as digital news reports, economic reports, e-mail, etc.
Emotion recognition In Text data is an area in Natural Language Processing that studies the ways of extracting the emotion from the Text; it used Natural Language Processing algorithms to understand the semantics or explicit message of text. Emotion detection based on Text Data was normally conducted from the viewpoint of prosody and articulation features. There is still an opening question on how to extract the emotion from the text input. The proposed thesis aims to develop new approaches in identifying text in sentence level and document level by using contextual pattern. The
contextual pattern for the sentence is constructed based on Link Parser
system and Word sense Disambiguation technique (Word Net).