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

Sean Sposito of American Banker reports that more and more banks are deploying artificial intelligence in an attempt to better understand their customers. He writes, “As BBVA Compass was tinkering with its retail banking pricing strategies last fall, robots were scraping the web behind the scenes. Like its peers, the Birmingham, Ala. bank needed to adapt to caps on interchange fees. It had to decide which benefits its retail customers would keep and which would get the ax. On a hunch, the bank decided to drop its $25 checking anniversary bonus, while keeping its debit rewards and other features. The computers confirmed that people were upset, but prodded executives to tell customer service reps and tellers to explain that BBVA Compass had decided to keep its other perks.”

He continues, “Those robots, really snippets of code dipping and diving into paragraphs and sentences across the internet, gave the bank what focus groups and pollsters would have taken months to confirm. Read more

FindtheBest (the site where users can compare some 700 topics side by side, initially discussed here) has some new capabilities on tap. This includes what it says are soft joins for relating together diverse data sets.

“Joins is a very hard database connection between two tables. Soft joins are a little more semantic,” says CEO Kevin O’Connor, co-founder of DoubleClick. “We’re linking a lot of data sets together on a loose basis.” To the end, he says, of trying to “cross-relate information a lot more, trying to discern all the data we have and give it some semantic meaning into ways people can understand it. It turns out there’s a huge, huge number of these semantic relationship between our data.”

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Is it time to disrupt the hospitality survey services industry? TrustYou thinks so. Today it’s launching its ReviewAnalyst Survey, a free guest satisfaction tool that hotels and hotel chains can use to integrate information from visitor surveys with information in social media reviews, and potentially bolster their reputation among consumers as a result.

TrustYou already monitors social sentiment across the web in online reviews, posts, and comments for the hotel, travel, and restaurant sectors.“Our key advantage is that we are the only ones in the space, I think, who tackled the key fundamentals of how can we scale this in as many languages as we want to,” says CEO Ben Jost. “That’s very interesting for the hospitality industry, because it’s very international. We currently have 12 languages and today, if we have enough content, we can add a new language each day if we want to.

And we can learn the key concepts for a new vertical every three to four weeks.”

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A new article announced that, “After 3 years in development and 6 months in private beta, thesocialCV.com is live.  The product emerged from the R&D of a partner product the companyPosts launched with Google and was previewed at a London TechCrunch event. It makes use of sophisticated semantic tools to aggregate data contained within social profiles.  The product contains more than 65 million social media profiles and is indexing an additional 400,000 daily.” Read more

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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