What do big companies have that most emerging businesses don’t have to help them get value from Big Data? Well, to start with, there’s lots of money and a ton of technology resources.

Never fear. At the upcoming Semantic Tech & Business conference in Berlin, Christopher Testa, CTO of startup WhiteBox Inc., plans to give companies with considerably fewer resources than giants like Google and IBM insight into how to use Big Data as a small, lean startup. His guidance will draw from his own past experiences at Google training AdSense; lessons learned studying the development of IBM’s Watson; and his current efforts to apply Big Data principles to create an expert system for amateur radio operator license exams at his own startup, with limited engineering resources. Most recently Testa was head of engineering at Ad.ly, and that will factor into advice about how to run a data center with free and open source solutions, too.

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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!

Editor’s Note: Here at the Semantic Web Blog we’ve done a lot of coverage of the personalized news mag app space. That includes some in-depth looks into Zite, acquired by CNN in August, such as this article. Most recently, we brought you news of Zite’s iPhone app.

Today, over at Zite’s blog, the company today will run a piece entitled Zite: Under the Hood. It should be of interest to anyone who wants more details about how its technology operates. It goes like this:

Zite: Under the Hood

If you’re already a Zite user, you’ve experienced the delivery of personalized content that is updated every time you open the app. To make that transparent and easy for you, takes a lot of effort. The Zite team brings together decades of software development in artificial intelligence, machine learning and natural language technologies, and more than six years of product development, to blend and tune the experience for you. In short, Zite works by:

• mining content from your social web
• modeling that content
• modeling the community that interacts with it
• modeling your interests
• matching your interests to the content and your community, to help you discover content you’ll want to see.

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Tagged has acquired Topicmarks in the hopes of improving its friend suggestions. Josh Constine reports, “Tagged’s mission is to help strangers meet each other online, so it has to offer friend suggestions of people you’ll like and who’ll like you back. That’s why it acquired Topicmarks, a natural language processing and machine learning company. Topicmarks will allow Tagged to analyze the profiles of its 100 million registered users and match them with others with similar interests and vocabulary. Topicmarks’ technology, CEO, CTO, and 3 senior engineers will join Tagged in exchange for cash and stock. Its existing service will remain active for the foreseeable future.” Read more

Bill Ives recently discussed the advancements of Salience 5.0 with Lexalytics CEO Jeff Catlin. Ives writes, “Semantic technology differs from most computing as it learns on the job. This can provide great benefits but it can also be time consuming… [Lexalytics] came up with a clever idea to reduce the learning curve. They had their semantic engine digest Wikipedia to gain an understanding of human thought and build their Concept Matrices™. This allows it to do things that most computer technology would struggle with such as understanding that pizza is a food even though the word food was never associated with pizza in the text it was looking at.” Read more

A new article marvels at the advances of artificial intelligence, pointing to a news brief written by a computer: “WISCONSIN appears to be in the driver’s seat en route to a win, as it leads 51-10 after the third quarter. Wisconsin added to its lead when Russell Wilson found Jacob Pedersen for an eight-yard touchdown to make the score 44-3.” The article notes, “Those words began a news brief written within 60 seconds of the end of the third quarter of the Wisconsin-UNLV football game earlier this month… The clever code is the handiwork of Narrative Science, a start-up in Evanston, Ill., that offers proof of the progress of artificial intelligence — the ability of computers to mimic human reasoning.” Read more

Pearson has created a semantically powered tool to help students assess their reading abilities. The article explains that the Pearson Reading Maturity Metric is “a new and more accurate measure of the reading difficulty of texts. Developed by scientists at Pearson’s Knowledge Technologies group, the new computer-based technology measures how close an individual student’s reading abilities are to what they will need to succeed in college and careers.” Read more

Mike Bergman recently shared a list of the top ten challenges facing IT over the last ten years and the amazing strides that have been made in each area. Bergman states that in the last ten years, “a whole slew of Grand Challenges in computing hung out there: tantalizing yet not proven. These areas ranged from information extraction and natural language understanding to speech recognition and automated reasoning. But things have been changing fast, and with a subtle steadiness that has caused it to go largely unremarked. Sure, all of us have been aware of the huge changes on the Web and search engine ubiquity and social networking. But some of the fundamentally hard problems in computing have also gone through some remarkable (but largely unremarked) advances.” Read more

A quirky new article likens search engines to humongous babies. The article states, “You can’t expect it to understand complicated things. You would never try to teach language to a human baby by reading it Nietzsche, and you shouldn’t expect a baby google to learn bibliographic data by feeding it MARC (or RDA or METS or MODS, or even ONIX). When a baby says ‘goo-goo’ to you, you don’t criticize its misuse of the subjunctive. You say ‘goo-goo’ back. When Google tells you that that it wants to hear ‘schema.org’ microdata, you don’t try to tell it about the first indicator of the 856 ‡u subfield. You give it schema.org microdata, no matter how babyish that seems.” Read more

A recent article reports, “There’s an urgency among many organizations to create mobile applications that will engage customers, keep brands top of mind, and improve retention. In the rush to deliver a compelling application, too many of those same firms are launching apps built from the company perspective, without considering the user experience. As applications and services become more and more complex, for example, customers are often at a loss when trying to find what they need in a maze of menus and keywords.”

The article continues, “Understanding the intention of customers—what is known as semantic search—is becoming an increasingly important aspect of the evolution of mobile devices, services, and applications. Read more

A recent article reports, “A new technology enables almost any application to learn like a human. The Topic-Mapper software development kit (SDK) by ai-one inc. reads and understands unstructured data without any human intervention. It allows developers to build artificial intelligence into almost any software program. This is a major step towards what Ray Kurzweil calls the technological singularity – where superhuman intelligence will transform history.” Read more