Abstract :
The huge quantity of information, talks, posts, and papers available on the web cannot be ignored by companies. Being aware in near-real time of hot topics and opinions about a product or a topic is strategic for taking better decisions. Unfortunately, this information is totally or partially unstructured, thus it is difficult to be exploited. Most of the commercial solutions are “closed” applications and most of the services are one-shot projects rather than stable monitoring systems that enable a limited exploitation of the information. Practitioners often refer to this family of tools as Opinion Mining software, Sentiment Analysis Software, or Brand Reputation Software. Many companies would prefer a solution that could be integrated in the enterprise information systems and that could be considered as yet another data flow to be included in the Business Intelligence platform and to be queried with the traditional tools that are well-known to the users. Social business intelligence is the discipline of combining corporate data with user-generated content to let decision-makers improve their business based on the trends perceived from the environment. Setting up a Social BI architecture requires contributions by several areas of computer science such as Information Retrieval, Text Mining, Database, Ontology and Artificial Intelligence The keynote will describe the features of a Social BI architecture, it will survey the research issues related to it and it will go into details about database and big data issues that would allow to create BI like capabilities.
