第四届国际协作大数据和数据分析研讨会 The 4th International Symposium on Big Data and Data Analytics in Collaboration BDDAC 2016

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The challenge of “Big Data” continues to grow and is an active area of significant research. “Big Data” is usually defined by its primary attributes of volume, velocity, variety and complexity, or some combination of these. The problem domains include scientific disciplines such as astronomy and biology, business disciplines such as marketing and security, law enforcement and even natural language processing as part, for example, of automated real time speech translation. While social media, so pervasive nowadays, is one of the main contributors to vast amounts of Big Data around the world, several other diverse sources such as fixed and mobile sensors, secondary data generated by physical simulations, transactional records from high speed trading systems, and high volume business record analytics also constitute important areas of research. Creating effective applications and solutions that work for real world “Big Data” problems requires both, collaborative technology and multi-disciplinary teams. These applications may leverage Big Data platforms, such as open source LexisNexis HPCC Systems and Hadoop platforms, or may involve novel approaches.

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2016-03-25

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This symposium solicits contributions that address contemporary and future challenges in big data and data analytics, particularly in collaboration systems, social networks, and information technologies. Topics may include

Theories and Methodologies for Big Data processing
Architectures and Design of Big Data processing systems
Computing languages applied to Big Data processing and analytics
Qualitative and Quantitative Studies of high performance data intensive computing systems
Machine Learning Methods applied to Big Data analytics
Natural Language Processing methodologies
Semantic Web analytics
Data Modeling for Social Networks
Discovery, Collection, and Extraction of information in Big Data sources
Processing of Big Data Streaming
Collaborative Filtering and Recommendation Systems
Text Categorization; Topic Recognition
Subjectivity in Textual Data; Sentiment Analysis; Polarity/Opinion Identification and Extraction
Big Data Mining and Discovery
Large-scale Social Image and Video Analysis and Retrieval
Security and Risk in Big Data processing and analytics
Privacy and Big Data analytics
Trust, Reputation and Recommendation Systems
Big Data Visualization
Leveraging Big Data in the Enterprise
Performance and Benchmarking for Big Data processing and analytics
NoSQL systems and Big Data
Distributed data-intensive computing systems
Semantic content extraction and analytics languages and techniques
Ontology representations and processing in Big Data