High-quality papers are solicited on all the research areas related to Social BI. Suggested topics include (but are not limited to) the following:
- Algorithms and Techniques
- Text mining and topic discovery
- Integration of social data
- Opinion mining and sentiment analysis
- Mass opinion estimation and trend detection in social data
- Emotion detection and analysis in sentences, documents, and speech transcripts
- Multilingual sentiment analysis
- SBI and the semantic web
- Extraction, transformation, and loading for SBI
- Computational treatment of large amounts of user-generated content
- Query processing, optimization, and performance
- Visual interfaces and OLAP on social data
- Analytics for SBI
- Mining and what-if analysis on social data
Architectures and Methodology
- Advanced architectures for SBI
- Cloud SBI
- Tools for SBI
- Spatial data warehouses and location intelligence
- Methodological support for SBI
- Requirement analysis, design, implementation, and testing of SBI systems
- Modeling of social data
- Methods and benchmarks for evaluating SBI systems
- Case studies and project experiences
Papers must be submitted in PDF via EasyChair; they must not exceed 10 pages in the AISC format and must comply with the AISC formatting guidelines. Papers will be refereed based on their scientific merit and relevance to the workshop. Each paper will be reviewed by at least two Program Committee members. Duplicate submissions are not tolerated.
Submission implies the willingness of at least one of the authors to register and present the paper during the workshop.
Conference and workshop fees are announced on the ADBIS webpage.
The accepted papers will be published by Springer-Verlag in the Advances in Intelligent Systems and Computing series. Extended versions of the best workshop papers will be invited after the conference to contribute to a special issue of the International Journal of Data Warehousing and Mining. The publication of selected papers in this journal will be subject to a second round of reviews.