With just about every major brand and celebrity on Facebook and Twitter, the line between social media and popular culture is becoming harder to distinguish by the day. What is evident is the incredible power social media has in uncovering popular sentiment and the way information is being shared and disseminated. The sheer amount of data amassed on any social network on any given day holds an incredible amount of intelligence and insight into where the collective sentiment of the masses lies.

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Semantic Tech & Business Conference Returns to San Francisco

Semantic Tech & Business Conference returns to San Francisco in June! Join us from June 3-7 for complete coverage of Big Data, Linked Data, Extreme Information Management, and Semantic Web. From breakthrough approaches to solving business problems to the big data implications of fast–evolving technologies, SemTechBiz provides you with an unparalleled interactive experience and delivers tangible business value. We're offering a special early rate when you register by February 17. Sign up now!

Semantic web – snake oil for BI? Ovum, UK If the technical implementation challenges can be overcome then semantic technologies have the potential to advance the use of BI and analytics in interesting and innovative ways. If the BI 2.0 vision is to have any substance to it, then the semantic …

Executive Summary

Chemistry is a central science and the data produced as a consequence is immense. However, much of this data is which makes data integration difficult. In this article, we demonstrate how chemical data can be retrieved from reports, scientific theses and papers or patents and discuss how these sources can be processed using natural language processing techniques and named-entity recognisers to produce chemical data and knowledge expressed in RDF.

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Palm oil is a multi-billion dollar industry, yet to date no attempt has been made for complex knowledge modeling within the Palm Oil industry. As oil palm plantation industries contain numerous changing conditions and since relevant decision making parameters are dynamic as well, an intelligent Decision Support System (DSS) that is context sensitive, environment specific and localized for the user is needed. Our proposed solution empowers the end-users through semantic and ontology development methods, where the involvement of domain experts and end-users drive the application development.

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