Abstract
Recently, the research fields of social interactions among people have received a great deal of attention in recent years and, beyond doubt, have established themselves as main cornerstones of intelligent multimedia processing. Learning and extracting patterns from multimedia data is inseparably connected with various types of uncertainty. Yet, it is becoming more and more apparent and accepted among researchers that collaborative interactions between people can be applied to various potential solutions [1, 2]. In this special issue, we are focusing on recent advances in the use of social interaction methods for multimedia processing. We especially welcome contributions on the use of formal frameworks for reasoning under integrating human intelligence, such as collaborative taggings, social mining, and machine learning, including but not limited to data preprocessing, model induction (e.g., classification, regression). The paper “Agent-mediated shared conceptualizations in tagging services”, authored by Aranda-Corral et al., deal with the problem on tagging behaviors of different users which causes semantic heterogeneity in tagging systems. Thereby, an agent-based reconciliation knowledge system based on Formal Concept Analysis (FCA), has been applied to facilitate the semantic interoperability between personomies (personal folksonomies). The paper “Emotion-based character clustering for managing story-based contents: a cinemetric analysis”, authored by Jung et al., has proposed an interesting method that can clusters entities by measuring emotional similarities between the entities. Particularly, this work introduces a cinematic approach to process movie contents. The paper “Semantics enhanced engineering and model reasoning for control application development”, authored by Hastbacka and Kuikka, claims that an approach applying Web Ontology Language (OWL) semantics and reasoning to models is presented with examples to support industrial control application engineering.
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