Bøger i Socio-Affective Computing serien

Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer.

This book presents a summary of the multimodal analysis of user-generated multimedia content (UGC). Several multimedia systems and their proposed frameworks are also discussed. Subsequently, we present a personalized music video generation system for outdoor user-generated videos.

These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving.

Sentic Computing

This book brings together contributions from specialists in affective computing, game studies, game artificial intelligence, user experience research, sensor technology, multi-modal interfaces and psychology that will advance the state-of-the-art in player experience research;

Sentiment analysis research has been started long back and recently it is one of the demanding research topics.

Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer.

This book brings together contributions from specialists in affective computing, game studies, game artificial intelligence, user experience research, sensor technology, multi-modal interfaces and psychology that will advance the state-of-the-art in player experience research;

Sentiment analysis research has been started long back and recently it is one of the demanding research topics.