David Amerland of Imassera recently wrote, “It seems that $1 billion plus change these days is what’s required to buy a photo-sharing app (if you’re Facebook), a global phone manufacturer (if you’re Google) or a microblogging site (if you happen to be Yahoo). Beyond the jaw-dropping numbers that are casually bandied around for these acquisitions lies a game plan that has every major player struggling to position themselves for relevance and longevity in the semantic web. This ‘new’ web is characterized by two related things: data and connectivity and these happen to be the exact same building blocks out of which web verticals are created.” Read more

Lucena Research, a leading provider of investment decision support technology, today announced the launch of QuantDesk™ Back Tester, the trading strategy simulator component of QuantDesk™. QuantDesk™ Back Tester is a realistic market simulator that allows investors to test trading strategies over critical market periods. Back Tester represents a fourth component of Lucena’s flagship QuantDesk™ cloud-based platform, which allows users to build a strategy using Lucena’s modular algorithms such as scanning, forecasting, optimizing and hedging to help investment professionals validate and refine quantitative investment strategies. Read more

Alissa Lorentz of Wired reports, “With all the hype around Big Data, we’ve become extremely proficient at collecting data – be it from enterprise systems, documents, social interactions, or e-mail and collaboration services. The expanding smorgasbord of data collection points are turning increasingly portable and personal, including mobile phones and wearable sensors, resulting in a data mining gold rush that will soon have companies and organizations accruing Yottabytes (10^24) of data… So it’s all dandy that we’re getting better and better at sucking up every trace of potential information out there, but what do we do with these mountains of data? Move over Age of Content, enter the Age of Context.” Read more

Semantic technologies have made it to Gartner’s list of the top technology trends that will impact information infrastructure this year.

The research firm yesterday released the list of nine trends that it says will play key roles in modernizing information management and in making the role of information governance increasingly important. Semantic technologies come in at No.3 on the list – right behind closely-tied-to trends Big Data and modern information infrastructure.

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Matthew Weingarten of MMM-Online.com reports, “By applying a scientific approach, and taking advantage of technology that’s available, pharmaceutical marketers can boost the effectiveness of their marketing efforts and improve the return on their investment. Evidence-based approach shouldn’t be confined to the lab. Two current trends  push us toward enhanced rigor in marketing. First, the Internet has globalized the medical profession. Easily accessible medical databases put the latest research into the hands of doctors everywhere. As the profession has embraced social media, the network of influence has been completely remapped. The power of opinion leaders is now felt worldwide, through multiple channels.” Read more

Dan Woods of Forbes reports, “It’s easy to get caught up in the mystique of machine learning. After all, what’s not to like about the idea of algorithms sucking up and sorting through the data detritus of our companies’ back alleys like a Roomba Sweeper Vac? The reality is a bit more complex. Like any ‘breakthrough’ technology, machine learning involves some forethought and discipline before being let loose in the enterprise. I recently spoke with Bob Tennant, CEO of Recommind, a San Francisco-based unstructured information management and analysis company, seeking a few points of advice about where to use machine learning most effectively.” Read more

Alex Williams of TechCrunch reports, “AlchemyAPI has raised $2 million to extend the capabilities of its deep learning technology that applies artificial intelligence to read and understand web pages, text documents, emails, tweets, and other forms of content. Access Venture Partners led the Series A round, which the company will use to ramp up its sales and marketing, make hires and launch new services. Founder and CEO Elliot Turner says its natural language processing technology is used in vertical markets such as financial services, which uses Alchemy’s technology to analyze text and search for signals from the data it can plug into its trading algorithms. It is offered as a service or in the form of an appliance that companies install in its data centers.” Read more

Jacob Albert of Quartz reports, “First, they suggested taxing Google’s personalized ads to boost French advertisers. Then, they tried to tax Google News to finance the French press. Now, the French government is thinking about taxing the collection of personal data by Internet companies, according to a report put out Jan. 18. The main target would be American companies like Google, Facebook, or Amazon, whose data mining efforts generate enormous advertising profits but precious little tax revenue for countries like France.” Read more

According to a new article out of the company, “Instem, a leading provider of IT solutions to the global early development healthcare market, announced today it has released the next version of its OmniViz™ software solution enabling organizations to process larger datasets at greater speeds. OmniViz is a powerful data mining and analytics solution allowing users to analyze and explore critical information through its interactive and intuitive visualization technology. Utilizing sophisticated statistical and clustering algorithms, OmniViz processes and serves data to organizations to help reveal hidden patterns and features, allowing users to discover fresh insight and easily share that information with both colleagues and clients.” Read more

Derrick Harris of GigaOM reports, “When it comes to using data to determine how to build a team or manage a game, the National Football League appears years behind its professional sports brethren such as Major League Baseball and the National Basketball Association. But perhaps the increasing popularity of machine learning can change that by helping NFL teams make more sense of their very complex datasets. Delving deep into the world of computer science might sound like overkill, but professional football is big business in America, and an analytic edge off the field might be just as important as athletic or strategic edges on the field. Heck, it might help create them.” Read more