2018 IEEE多媒体内容多模式表示，检索，分析国际研讨会 2018 IEEE International Workshop on Multimodal Representation, Retrieval, and Analysis of Multimedia Content

活动简介

The presence of social media platforms creates an abundance of multimedia content on the web due to advancements in digital devices and affordable network infrastructures. It has enabled anyone with an Internet connection to easily create and share their ideas, opinions, updates, and preferences through multimedia content with millions of other people around the world. Thus, it necessitates novel techniques for an efficient processing, analysis, mining, and management of multimedia data to provide different multimedia-related services. Such techniques should also able to search and retrieve information from within multimedia content. Since much signicant contextual information such as spatial, temporal, and crowd-sourced information is also available in addition to the multimedia content, it is very important to leverage multimodal information because different representations represent different knowledge structures. However, decoding such knowledge structures into useful knowledge from a huge amount of multimedia content is very complex due to several reasons. Till date, the most of the semantic analysis, sentiment analysis, multimedia representation, multimedia information search and retrieval, opinion mining, and event understanding engines work in the unimodal setting. There is very limited work done which use multimodal information for these tasks. In this light, this workshop will focus on the use of multimodal information to analyze, represent, mine and manage multimedia content to support several semantic and sentiment based multimedia analytics problems. It will also focus on interesting multimedia systems that build upon semantic and sentiment information derived from multimedia data.

征稿信息

Topics of interest include but are not limited to:
Multimodal Multimedia Search, Retrieval and RecommendationMultimodal Personalized Multimedia Retrieval and RecommendationMultimodal Event Detection, Recommendation, and UnderstandingMultimodal Multimedia based FAQ and QA SystemsMultimodal based Diverse Multimedia Search, Retrieval and RecommendationMultimodal Multimedia Content AnalysisMultimodal Semantic and Sentiment based Multimedia AnalysisMultimodal Semantic and Sentiment based Multimedia AnnotationMultimodal Semantic-based Multimedia Retrieval and RecommendationMultimodal Sentiment-based Multimedia Retrieval and RecommendationMultimodal Filtering, Time-Sensitive and Real-time Search of MultimediaMultimodal Multimedia Annotation MethodologiesMultimodal Sentiment-based Multimedia Retrieval and AnnotationMultimodal Context-based Multimedia Retrieval and AnnotationMultimodal Location-based Multimedia Retrieval and AnnotationMultimodal Relationship-based Multimedia Retrieval and AnnotationMultimodal Mobile-based Retrieval and Annotation of Big MultimediaMultimodal Multimedia Data Modeling and VisualizationMultimodal Feature Extraction and Learning for Multimedia Data RepresentationMultimodal Multimedia Data EmbeddingMultimodal Medical Multimedia Information RetrievalMultimodal Subjectivity Detection Extraction from MultimediaMultimodal High-Level Semantic Features from MultimediaMultimodal Information FusionMultimodal Affect RecognitionMultimodal Deep Learning in Multimedia and Multimodal FusionMultimodal Spatio-Temporal Multimedia Data MiningMultimodal Multimedia based Massive Open Online Courses (MOOC)Multimodal/Multisensor Integration and AnalysisMultimodal Affective and Perceptual MultimediaMultimedia based Education