BDDAC 2016 - 4th International Symposium on Big Data and Data Analytics in Collaboration (BDDAC 2016)

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.
You are cordially invited to participate in, contribute to, and attend the International Symposium on Big Data and Data Analytics in Collaboration (BDDAC 2016) to be held as part of CTS 2016 (http://cts2016.cisedu.info/) June 06-10, 2016 in Orlando, Florida, USA. The Symposium is to address, explore and exchange information on the state-of-the-art and practice in the broad multidisciplinary field of Big Data. Participation is extended to researchers, designers, educators and interested parties in all disciplines and specialties (computer science, linguistics, psychology, statistics, sociology, multimedia and semantic web technologies, …).
The BDDAC Symposium topics include (but are not limited to) the following:
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