Multimedia data mining and knowledge discovery is a fast emerging interdisciplinary applied research area. There is tremendous potential for effective use of multimedia data mining (MDM) through intelligent analysis. Diverse application areas are increasingly relying on multimedia understanding systems. Advances in multimedia understanding are related directly to advances in signal processing, computer vision, machine learning, pattern recognition, multimedia databases, and smart sensors.

The main mission of this special issue is to identify state-of-the-art machine learning paradigms that are particularly powerful and effective for modeling and combining temporal and spatial media cues such as audio, visual, and face information and for accomplishing tasks of multimedia data mining and knowledge discovery. These models should be able to bridge the gap between low-level audiovisual features which require signal processing and high-level semantics. Original contributions, not currently under review or accepted by another journal, are solicited in relevant areas including (but not limited to) the following:

• Multiresolution-based video mining and features extraction
• Dimension reduction and unsupervised data clustering for multimedia content analysis tasks
• Mining methods and algorithms (classification, regression, clustering, probabilistic modelling), as well as association analysis
• Machine learning paradigms that perform spatial and temporal data mining
• Machine learning paradigms that allow for an effective learning of hidden patterns
• Object recognition and tracking using machine learning algorithms
• Interactive data exploration and machine learning discovery
• Mining of structured, textual, multimedia, spatiotemporal, and web data
• Application of MDM to contents-based image/video retrieval and medical data

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/aai/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable: