Konstantin Kakaes of the New America Foundation recently discussed the NLP challenges of language translation. Kakaes writes, “Recently, on the eighth floor of an office building in Arlington, Va., Rachel held her finger down on a Dell Streak touchscreen and asked Aziz whether he knew the village elder. The handheld tablet beeped as if imitating R2-D2 and then said what sounded like, ‘Aya tai ahili che dev kali musha.’ Aziz replied in Pashto, and the Streak said in a monotone: ‘Yes, I know.’ Rachel asked: ‘Would you introduce me to him?’ Aziz failed to understand the machine’s translation (though he does speak English), so she asked again: ‘Could you introduce me to the village elder?’ This time, there was success, after a fashion. Aziz, via the device, replied: ‘Yes, I can introduce myself to you.’ Aziz, who is at most middle-aged and was wearing a sweater vest, was not the village elder.” Read more

SemTechBiz is Less Than 3 Weeks Away

The Semantic Tech & Business Conference (SemTechBiz) is coming to San Francisco on June 3-7! Join us for case studies, innovative panels, tutorials, and keynotes that will provide you with practical advice, hands-on guidance, and breakthrough approaches to solving business problems with semantic technology. Passes go up $200 at the door. Sign up now and save !

Lance Ulanoff of Mashable reports, “Bing has been reinvented, offering enhanced search results that tap into the power of social media. Microsoft has done this by pulling people out of search results and putting them in their place: A right-hand social column that will eventually include Facebook, Twitter, Google+ Quora and LinkedIn integration, as well as people who may know something about your most recent Bing query. It even offers a way to ask questions on your favorite social network, directly through Bing.”

Ulanoff continues, “It’s something of an about-face for the Number 2 search engine, which up until earlier this year has been slowly but surely integrating Facebook information (like “Likes”) directly into Bing Search results. Read more

At this week’s SAP Sapphire conference. NetBase will be taking its relationship with the enterprise vendor to the next level. Last December the two paired up to bring NetBase’s social intelligence (SI) to SAP BusinessObjects’ business intelligence (BI).

Coming up now is a complete integration of the NetBase technology into SAP’s Social On Demand customer relationship management (CRM) console. “Having access to social data is becoming critical to every part of the organization,” says NetBase chief marketing officer Lisa Joy Rosner. So, “social media [becomes] just one more data point” for which the enterprise must account.

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The financial services sector was in focus at this week’s Sentiment Analysis Symposium in New York City, which is organized and produced by Alta Plana Corp. and its founder, Seth Grimes.  Take, for example, the presentation by Rich Brown, head of Elektron Analytics at Thomson Reuters, who disclosed that the company is about to launch market response indicators in support of its Thomson Reuters News Analytics system for the financial community. That product this week also won The Technical Analyst’s 2012 award for best news analytics software.

With its software, originally discussed here, qualitative, unstructured information is turned into a quantitative data set allowing users – machines and humans – to quickly analyze thousands of news stories in less time than it takes to read a single headline, as Thomson Reuters describes it. It uses natural language processing technology to get to the end game, which is to forecast financial market response from news and social media sentiment. Some 82 fields of metadata come into play for automating the analysis of news content. That encompasses sentiment down through to the degree of positive, negative or neutral expressions and how individual companies mentioned in a piece fare in those respects – rather than just the tone of the piece at large. “The computational linguistics system measures the author’s tone as positive or negative on any given entity, which is important and the harder part of it,” Brown said. Other fields include, for example, relevance, genre, intensity of news flow, and more.

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First Retail has been named a “Cool Vendor in Analytics and Business Intelligence by Gartner: “The report, issued on April 27, 2012, highlights five vendors selected by Gartner for their solutions in the analytics and business intelligence market.” The report states, “Selecting Cool Vendors in the analytics market this year was difficult. New providers of analytic solutions abound, especially in the popular areas of mobile, social, cloud and big data. We, as an industry, are building silos of analysis that will eventually have to be integrated, but the benefit of specialized analysis for problems that have not been addressed before outweighs most organizations’ needs for a holistic view, at least for now.” Read more

Wavii made waves when it launched  its automated, algorithm-driven news aggregation service in April, which has been billed as making Facebook out of Google. But what makes Wavii work? When The Semantic Web Blog found a picture in Wavii.com’s Flickr photostream featuring the word “predicates” on a white board, it was time to discover whether Semantic Web standards had anything to do with its engine.

Turns out, RDF is not at play here. But natural language processing certainly factors in, albeit from the perspective of information extraction and being almost entirely machine-learning based rather than deep-parsing oriented. The service’s technology is influenced by the expert machine-reading NLP work being done at the University of Washington, where Wavii advisor Oren Etzioni is a professor of computer science.

But Wavii CEO and founder Adrian Aoun can credit growing up in a household where his father was a linguist — a student of Noam Chomsky – for originally sparking his interest in how language works. Whenever his dad would have a debate about a language construct with his fellow MIT buddies, he says, “they’d turn to me and say which one sounds better….The irony is that they’re arguing over the rules, but they acknowledge the right answer is whatever humans do.”

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Michael Cooney reports that next month the Defense Advanced Research Projects Agency (DARPA) is set to detail “the union of advanced technologies from artificial intelligence, computational linguistics, machine learning, natural-language fields it hopes to bring together to build an automated system that will let analysts and others better grasp meanings from large volumes of text documents.”

DARPA stated, “Automated, deep natural-language understanding technology may hold a solution for more efficiently processing text information. Read more

While much of the publishing industry still is getting up to speed on what semantic technology can do for business, it’s already deep within the DNA of The Tribune Company – to the point where Keith DeWeese, Director, Information and Semantics Management, can comfortably use the word “ontology” in discussions with non-tech employees, and enjoy the fact that they’re equally comfortable using it themselves.

DeWeese has been with the company since 2007, putting in place a sophisticated semantic system for auto-tagging and indexing content using natural language processing and controlled vocabularies, and leveraging its taxonomy for projects such as providing advanced search functionality. Thanks to building a collaborative communication channel with Tribune executives, producers, and editors, “now I actually am in meetings with executives who say how exciting it is that we now can be part of a community of people applying semantic technologies to content,” he says. “The other day I was at a meeting where a top executive used the word ontology all the time. I kept smiling and later I thanked her.”

Closely engaging with his business customers also is helping make it possible to push the semantic vision further at the company.

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These days, it’s not just the traditional publishing community that has reason for leveraging the content syndication model. As more and more companies across vertical sectors themselves become content providers, syndication makes sense for them, too.

NewsCred has a new – and semantic – take on content syndication, with content partners ranging from Reuters to The Guardian to The Economist. Recently-added customers that leverage the service’s fully licensed text, image and video content include traditional publishers such as the New York Daily News (and NewsCred is in talks with it about becoming a content provider, too). But other recent customers point to the importance of quality content to the consumer and corporate brand market:  For example, insurance provider Zurich recently signed on. NewsCred also just closed a deal with Johnson & Johnson to be a subscriber of its syndication services for content related to the health care products and pharmaceuticals space.

Brands, says NewsCred CEO Shafqat Islam, are responding to consumers getting smarter and more demanding. “They have so much access to information that brands are starting to realize they can’t just sell products or services anymore,” he says. “They need more authentic, engaging conversations with their customers and the best way to build these authentic relationships is with highly-engaging, trusted, high-quality content.”

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Market Strategies International recently released the first edition of what it says will be an annual Social Media Brand Index, a measure for brands both of consumer-generated social media about them and of their own sponsored content. The Index takes into account four components. Volume, or the amount of buzz about a brand online, is one of them — and its most highly weighted component, too. The others take their cue from what we might call more meaning-related measures, sentiment analytics and semantic markup among them.

For example, there’s net Sentiment, which Market Strategies says represents the ratio of positive to negative sentiments expressed about a brand based on automated natural language processing of the content of posts, comments and mentions. Another component, Positive Emotions, seems to flow from that measure, representing the number of content items that are identified as having the warm fuzzies about them, again based on automated coding of content.

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