  Emotion recognition in conversations is an important step in various virtual
chat bots which require opinion-based feedback, like in social media threads,
online support and many more applications. Current Emotion recognition in
conversations models face issues like (a) loss of contextual information in
between two dialogues of a conversation, (b) failure to give appropriate
importance to significant tokens in each utterance and (c) inability to pass on
the emotional information from previous utterances.The proposed model of
Advanced Contextual Feature Extraction (AdCOFE) addresses these issues by
performing unique feature extraction using knowledge graphs, sentiment lexicons
and phrases of natural language at all levels (word and position embedding) of
the utterances. Experiments on the Emotion recognition in conversations dataset
show that AdCOFE is beneficial in capturing emotions in conversations.
