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Search Engine Yandex Gets More Personal, And More Semantic, Too

Image courtesy of Pixomar / FreeDigitalPhotos.net

Search engine Yandex this week added personalization capabilities for Eastern European users’ search results. It analyses their online behavior including their search history, clicks on search results, and language preferences for its suggestions.

Kaliningrad is the name of the latest edition of Yandex’ personalized search engine. It uses that information to make suggestions and rank search results individually tailored for each user, showing book lovers that do a search on Harry Potter links related to the books, while those who prefer movies get film-oriented link fare.

Semantic markup didn’t play a role in the development of the technology, Yandex technical product manager and developer advocate Alexander Shubin says. But it can be applied for future enhancements, he notes. The new personalization reportedly leverages Yandex’ machine-learning-based query and search results algorithms “Spectrum” and “MatrixNet” to train the results to users’ requirements.

That said, Yandex has been diving deeper into semantic web waters. Beyond taking advantage of sites using schema.org markup to improve the display of search results, Shubin provides this update: “We enhanced our markup validator to understand all the markup (Open Graph, schema.org, RDFa, microformats). It is universal now (as Google’s or Bing’s instruments).”

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Google Debuts Data Highlighter: An Easy Way Into Structured Data

Structured data makes the Web go around. Search engines love it when webmasters mark up page content. Google’s rich snippets, for instance, leverages sites’ use of microdata (preferred format), or RDFa or microformats: It makes it possible to highlight in a few lines specific types of content in search results, to give users some insight about what’s on the page and its relationship to their queries – prep time for a recipe, for instance.

Plenty of web sites generated from structured data haven’t added HTML markup to their pages, though, so they aren’t getting the benefits that come with search engines understanding the information on those web pages.

Maybe that will change, now that Google has introduced Data Highlighter, an easy way to tell its search engine about the structured data behind their web pages. A video posted by Google product management director Jack Menzel gives the snapshot: “Data Highlighter is a point- and-click tool that allows any webmaster to show Google the patterns of structured data on their pages without modifying the pages themselves,” he says.

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With MarkLogic Search Technology, Factiva Enables Standardized Search And Improved Experiences Across Dow Jones Digital Network,

Dow Jones & Company’s Factiva information service has long been distinguished by the semantic tools it applies to its content to surface relevant search information. Last week the company announced what it says is one of the most significant investments it’s made in the Factiva product suite, licensing new search technology from MarkLogic Corp.

The arrangement is positioned as providing standardized search technology across the Dow Jones digital network, including Factiva, WSJ.com and Dow Jones Financial Services products. To be specific, the investment in one underlying search technology that will be used by the company’s multiple businesses and products means that, “one powerful, unified search platform will service the search needs of our consumer and enterprise customers around the world,” says Georgene Huang, head of Factiva. “Any improvements or customizations we build atop this infrastructure will be scalable and efficiently accessible to all.” That will allow better and easier synergies between the development, products and the content, she says.

The new search technology, Huang says, complements its continuing investment in Factiva’s core metadata and taxonomy strengths in many ways.

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Singly “App Fabric” Platform Helps Developers Deeply Connect To Other Apps So Users Can Connect With All Their Data

Singly, which has as its mission connecting people more closely with their data everywhere it lives, now is opening up the beta of its development platform to help developers create the apps that can make that happen.

As co-founder and CEO Jason Cavnar describes Singly’s work, “it is an app fabric product” that gives developers a way to build applications without having to worry about making all the different connection points into the other applications they want their products to talk to. “That’s handled as a service for them. Like Amazon Web Services is for the infrastructure layer, we would like to be a trusted partner in the data layer,” he says.

“It’s really about a person’s life and experiences – sharing that wherever it is in other applications into a new one and that new one generating things to share back out,” says fellow co-founder and CTO Jeremie Miller, who invented Jabber/XMPP technologies and was the primary developer of jabberd 1.0, the first XMPP server. APIs are prominent in Singly’s approach to unlocking that data, but Miller sees some parallels between its own mission and that of the semantic web – a concept whose potential he’s always been excited about, he says, but which he doesn’t think has caught on as he’d hoped.

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Universities Put Cash Towards Helping HomeGrown Tech Startups Along

Image Photo Courtesy Flickr/401(K) 2012

Universities play an important role in advancing the technology ecosystem, semantic technology included. Look for starters at work done at The Tetherless World Constellation at Rensselaer Polytechnic Institute, Wright State University’s Kno.e.sis Ohio Center of Excellence in Knowledge-enabled Computing, MIT, and the Digital Enterprise Research Institute located at the National University of Ireland, Galway.

In addition to driving technology ever forward, institutions like these and others also provide a home for incubating good ideas that could become good businesses. Music discovery service Seevl and the enterprise-focused SindiceTech are two examples of semantic spin-outs from DERI, for instance, while MIT Media Lab gave birth to commercial properties with semantic underpinnings including music intelligence platform The Echo Nest. The Kno.e.sis Center points work it’s doing in the commercial direction, too: Its LinkedIn profile description notes that its “work is predominantly multidisciplinary, and multi-institutional, often involving industry collaborations and significant systems developing, with an eye towards real-world impact, technology licensing, and commercialization.”

Given the projects with commercial prospects underway within their own houses, it would seem there’s opportunity for universities themselves to look for even more ways to contribute to that success. And that’s just what the University of Minnesota is doing: This week it said that it’s launching a $20 million seed fund over a ten-year timeframe to support the innovative ideas to which its campus plays host.

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Tagging the Visual Web: Visual Media Doesn’t Have To Be Dumb Anymore

Instagram. Tumblr. Pinterest. The web in 2012 is a tremendously visual place, and yet, “visual media still as dumb today as it was 20 years ago,” says Todd Carter, founder and CEO of Tagasauris.

It doesn’t have to be that way, and Tagasauris has put its money on changing the state of things.

Why is dumb visual media a problem, especially at the enterprise-level? Visual media, in its highly un-optimized state, hasn’t been thought of in the same way that companies think about how making other forms of data more meaningful and reasonable can impact their business processes. A computer’s ability to assess image color, pattern and texture isn’t highly useful in the marketplace, and as a result visual media has “just been outside the realm of normal publishing processes, normal workflow processes,” Carter says. Therefore, what so many organizations – big media companies, photo agencies, and so on –  would rightly acknowledge to be their treasure troves of images don’t yield anywhere near the economic value that they can.

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Google Knowledge Graph Picks Up A Few New Languages, And Shows Some Medical Smarts

What links someone searching the web for information about Prince Henry the Navigator in Portuguese and someone trolling for details about the medication synthroid?

The answer: Google’s Knowledge Graph, which now covers 570 million entities, 18 billion facts and connections, and about three times as many queries globally as when it was first launched. Google has announced that the Knowledge Graph will bring its intelligence to searches conducted in Portuguese as well as Spanish, French, German, Japanese, Russian, and Italian.

Over the next few days, according to the Google Inside Search blog, users searching in those languages will also start to benefit from the Graph’s work toward achieving its goal of mapping out billions of real-world things, and find new information relevant to their language and country.

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Professional Investors: Get Your Quant In A Box

The talk of falling off the fiscal cliff that’s drowning out the holiday music could take its toll on what historically is a strong month for the stock market, according to Reuters, How that scenario will play out, not to mention a ton of other factors, is just the kind of thing to keep hedge fund managers, wealth advisors and advanced individual investors on their toes as they calculate investment strategies.

A new cloud-based artificial intelligence solution from Lucena, the first features of which are going live today, focuses on helping these users scientifically validate their investment plans, the idea being to find new market opportunities and reduce risk. The early stage company is headed up by serial entrepreneur and CEO Erez Katz, whose partner in the venture is CTO Tucker Balch, a professor of Interactive Computing at the Georgia Institute of Technology whose work focuses on machine learning and robotics.

QuantDesk is the result of five years of research Balch has done at the institution. It is, as Katz describes it, a “quant in a box” that can give sophisticated investment professionals in small or mid-size firms, who lack the resources of the large investment houses to hire quantitative analysts to derive complex and sophisticated trading algorithms, access to a scientific approach to “validate or pivot the decision process,”

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All That Jazz: A Linked Data Look Into The Musical Genre’s Community Relationships

Linked Data projects in and of themselves are cool. But sometimes, one of them just stands out as even cooler. Such is the case with Linked Jazz, some 2900-triples strong in the service of identifying and revealing the network of social relationships among the jazz community.

Talk about all that jazz. The effort, led by Cristina Pattuelli, associate professor at the Pratt Institute School of Information and Library Science, includes a visualization tool developed by a graduate student there, Matthew Miller, that provides different and compelling ways to explore connections among the jazz greats and the lesser-knowns, as well. You can view individuals based on the number of connections they have, for instance, or on their shared connections.

“It can be used dynamically to click on an artist and see the pattern of all the connections around him, play a clip from YouTube, have a little bio,” Pattuelli says. It’s innovative, she says, because it runs direct from a browser. Read more

Semantic Tech Checks In As The Holiday Shopping Begins

 

Photo credit: FlickR/crd!

 

With Thanksgiving Day, Black Friday and Small Business Saturday behind us, and Cyber-Monday right in front of us, it is clear the holiday season is in full force. Apparently, retailers – both online and real-world – are doing pretty well as a group when it comes to sales racked up.

Reports have it that e-commerce topped the $1 billion mark for Black Friday in the U.S. for the first time this year, with Amazon, Walmart, Best Buy, Target and Apple taking honors as the most visited online stores, according to ComScore. Consumers spent $11.2 billion at stores across the U.S. on Black Friday, said ShopperTrak, down from last year but probably impacted by more people heading out to more stores for deals that began on Thursday night. The National Retail Federation put total spending over the four-day weekend at a record $59.1 billion, up 13 percent from $52.4 billion last year.

Not surprisingly, semantic technology wants in on the shopping action. Social intelligence vendor NetBase, for instance, just launched a new online tool that analyzes the web for mentions of the 10 top retailers to show the mood of shoppers flocking to those sources. The Mood Meter, which media outlets and others can embed in their sites, ranks the 10 brands based on sentiment unearthed with the help of its natural language processing technology.  Read more

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