Posts Tagged ‘Open Graph’

Semantic Tech Lends A Hand To Thanksgiving Holiday Sales

Photo courtesy: https://www.flickr.com/photos/119886413@N05/

Photo courtesy: https://www.flickr.com/photos/119886413@N05/

Retailers are pushing holiday shopping deals earlier and earlier each year, but for many consumers the Thanksgiving weekend still signals the official start of the gift-buying season. With that in mind, we present some thoughts on how the use of semantic technology may impact your holiday shopping this year.

  • Pinterest has gained a reputation as the go-to social network for online retailers that want to drive traffic and sales. Shoppers get an advantage, too, as more e-tailers deploy Rich Pins, a feature made available for general use late last year, for their products, using either schema.org or Open Graph. Daily updated Product Rich Pins now include extra information such as real-time pricing, availability and where to buy metatags right on the Pin itself. And, anyone who’s pinned a product of interest will get a notification when the price has dropped. OverstockTarget, and Shopify shops are just some of the sites that take advantage of the feature. Given that 75 percent of its traffic comes from mobile devices, it’s nice that a recent update to Pinterest’s iPhone mobile app – and on the way for Andoid and iPads – also makes Pins information and images bigger on small screens.

 

  • Best Buy was one of the earliest retailers to look to semantic web technologies to help out shoppers (and its business), adding meaning to product data via RDFa and leveraging ontologies such as GoodRelations, FOAF and GEO. Today, the company’s web site properties use microdata and schema.org, continually adding to shopper engagement with added data elements, such as in-stock data and store location information for products in search results, as you can see in this presentation this summer by Jay Myers, Best Buy’s Emerging Digital Platforms Product Manager, given at Search Marketing Expo.

 

  • Retailers such as Urban Decay, Crate&Barrel, Golfsmith and Kate Somerville are using Edgecase’s Adaptive Experience platform, generating user-friendly taxonomies from the data they already have to drive a better customer navigation and discovery experience. The system relies on both machine learning and human curation to let online buyers shop on their terms, using the natural language they want to employ (see our story here for more details).

 

  • Walmart at its Walmart Labs has been steadily driving semantic technology further into its customer shopping experience. Last year, for example, Walmart Labs senior director Abhishek Gattani discussed at the Semantic Technology and Business conference capabilities it’s developed such as semantic algorithms for color detection so that it can rank apparel, for instance, by the color a shopper is looking for and show him items in colors close to read when red itself is not available, as well as categorizing queries to direct people to the department that’s really most interesting to them. This year, WalMart Labs added talent from Adchemy when it acquired the company to bring further expertise in semantic search and data analytics to its team, as well as Luvocracy, an online community that enables the social shopping experience—from discovery of products recommended by people a users trusts to commerce itself. Search and product discovery is at the heart of new features its rolling out to drive the in-store experience too, via mobile apps such as Search My Store to find exactly where items on their list are located at any retail site.

What’s your favorite semantically-enhanced shopping experience? Share it with our readers below to streamline their holiday shopping!

 

MindMeld Makes Context Count In Search

mmapiMindMeld – you may know the term best from StarTrek and those fun-loving Vulcan practices. But it lives too at Expect Labs, as an app that listens to and understands conversations and finds relevant information within them, and as an API that lets developers create apps that leverage contextually-driven search and discovery – and may even find the information users need before they explicitly look for it.

Anticipatory computing is the term Expect Labs uses for that. “This is truly a shift in the way that search occurs,” says director of research Marsal Gavaldà. “Anticipatory computing is the most general term in the sense that we have so much information about what users are doing online that we can create accurate models to predict what a user might need based on long-ranging history of that user profile, but also about the context.”

The more specific set of functionality that contributes to the overarching theme of anticipatory computing, he explains, “means that you can create intelligent assistants that have contextual search capabilities, because our API makes it very easy to provide a very continuous stream of updates about what a user is doing or where a user is.”

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Open The Door To Bringing Linked Data To Real-World Projects

ld1Linked Data: Structured Data on the Web is now available in a soft-cover edition. The book, authored by David Wood, Marsha Zaidman, Luke Ruth, and Michael Hausenblas, and with a forward by Tim Berners-Lee, aims to give mainstream developers without previous experience with Linked Data practical techniques for integrating it into real-world projects, focusing on languages with which they’re likely to be familiar, such as JavaScript and Python.

Berners-Lee’s forward gets the ball rolling in a big way, making the case for Linked Data and its critical importance in the web ecosystem:“The Web of hypertext-linked documents is complemented by the very powerful Linked Web of Data.  Why linked?  Well, think of how the value of a Web page is very much a function of what it links to, as well as the inherent value of the information within the Web page. So it is — in a way even more so — also in the Semantic Web of Linked Data.  The data itself is valuable, but the links to other data make it much more so.”

The topic has clearly struck a nerve, Wood believes, noting that today we are “at a point where structured data on the web is getting tremendous play,” from Google’s Knowledge Graph to the Facebook Open Graph protocol, to the growing use of the schema.org vocabulary, to data still growing exponentially in the Linked Open Data Project, and more. “The industry is ready to talk about data and data processing in a way it never has been before,” he continues. There’s growing realization that Linked Data fits in with and nicely complements technologies in the data science realm, such as machine learning algorithms and Hadoop, such that “you can suddenly build things you never could before with a tiny team, and that’s pretty cool….No technology is sufficient in and of itself but combine them and you can do really powerful things.”

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Facebook Graph Search: What’s It To Ya?

rsz_fbgraphsearchA new survey is just out reporting on how people are using Facebook. Just over 300 users were randomly selected by Stone Temple Consulting to gain some insight into Facebook feature awareness.

While not a definitive study (nor is it touted as one), one finding of interest to Semantic Web Blog readers is this: Below one-third of users have even heard of Graph Search, its functional semantic search engine for discovering relationships between entities in users’ networks of friends. It’s recently expanded from enabling queries around people, places, photos and interests culled from people’s profiles or pages (books your friends liked, for instance, or photos they took in San Francisco) to include searches of  status updates, photo captions, check-ins and comments. Of those who do know what Graph Search is, just over one-third said that they had used it.

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Reason To Be Thankful: Being Named A Fast-Growing Tech Company

rsz_thankful_imageIt’s got to be a happy Thanksgiving for a number of tech companies that made their way to Deloitte’s recently-released Technology Fast 500. The 2013 ranking of the fastest-growing tech companies based in North America also has something to show for anyone who’s doubted that there’s money to be made taking advantage of semantic and other Web 3.0 concepts, a look at the list should show it’s time for the doubting to stop.

Have a look at some of the winners with their overall rankings:

#2 Acquia. Drupal claims the title of being the first mainstream content management system to support semantic web technology in its core. The Drupal-powered project Acquia was co-founded by Drupal creator Dries Buytaert to provide cloud, SaaS, and other services to organizations building websites on Drupal – and has on staff software engineer Stéphane Corlosquet, who had a big hand in bringing those semantic capabilities to Drupal’s core. In fact, Corlosquet spoke at the most recent SemTechBiz about Acquia as an example of a Drupal-powered project managing its content as Linked Data.

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Take A Peek At Some Semantic Halloween Treats

rsz_bones5How can the semantic web help you participate in and celebrate Halloween this year? We trolled around and came up with a few ideas:

* Still haven’t found just the right costume yet for tonight’s festivities (for you, that is – we’re sure the kids have had theirs planned for some time). Perhaps you’re thinking hard about a do-it-yourself skeleton theme, but aren’t sure of the details for creating the most realistic effect? Well, if you head over to semantic search engine DuckDuckGo’s science goodies section, you’ll get a quick response on the number of bones in the human body, courtesy of Wolfram/Alpha computations. You can take it from there.

* OK, costume’s in check. Now how about what to do while wearing it?

sensebotscreenSemantic search engine SenseBot might be a help here, pointing you to information it’s extracted from web pages and summarizing them in a, well, sensible way, as well as offering a cloud of the concepts it’s discovered for you to further narrow your agenda. The results can be a little off here and there, but it’s nice to have an option to further narrow a search, like one for adult activities to partake in on Halloween, to something more granular, like those designed for the “scare” factor.

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Facebook Wants You to Catalog the Known World

Tom Simonite of the MIT Technology Review reports, “More than one billion people visit Facebook each month, mostly to see photos and messages posted by friends. Facebook hopes to encourage some of them to do a little work for it while they’re there. By asking people to contribute data—from business locations to book titles—and to check one another’s work, Facebook is building a rich stock of knowledge that could make its software smarter and boost the usefulness of its search engine. ‘We’re trying to map what the real world looks like onto Facebook so you can run really expressive and powerful queries,’ says Mitu Singh, product manager for Facebook’s entities team, a group charged with building a resource called the entity graph.” Read more

Facebook Debuts Graph Search; Is Open Graph Protocol In The Picture?

Photos your friends took in New York City. Restaurants in Chicago your friends have been to. People who like running and who live in Denver, Colorado. Friends of friends who are interested in ballroom dancing or hiking.

Facebook’s new Graph Search promises to find all those things, and more, for you. Mark Zuckerberg announced the new way to get really personal in your searches for people, photos, places and interests today at an event at the company’s headquarters in Menlo Park, Calif., and the company has put up an explanatory page on the new service here.

While it doesn’t mention Open Graph specifically, the protocol that lets apps model a person’s activities based on actions and objects, it makes sense that the app-specific actions it lets people share on Facebook are feeding into the new search feature.

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Good-Bye to 2012: A Look Back At The Year In Semantic Tech, Part 1

Courtesy: Flickr/zoetnet

As we close out 2012, we’ve asked some semantic tech experts to give us their take on the year that was. Was Big Data a boon for the semantic web, or is the opportunity to capitalize on the connection still pending? Is structured data on the web not just the future but the present? What sector is taking a strong lead in the semantic web space?

We begin with Part 1, with our experts listed in alphabetical order:

John Breslin, lecturer at NUI Galway, researcher and unit leader at DERI, creator of SIOC, and co-founder of Technology Voice and StreamGlider:
I think the schema.org initiative really gaining community support and a broader range of terms has been fantastic. It’s been great to see an easily understandable set of terms for describing the objects in web pages, but also leveraging the experience of work like GoodRelations rather than ignoring what has gone before. It’s also been encouraging to see the growth of Drupal 7 (which produces RDFa data) in the government sector: Estimates are that 24 percent of .gov CMS sites are now powered by Drupal.

Martin Böhringer, CEO & Co-Founder Hojoki:

For us it was very important to see Jena, our Semantic Web framework, becoming an Apache top-level project in April 2012. We see a lot of development pace in this project recently and see a chance to build an open source Semantic Web foundation which can handle cutting-edge requirements.

Still disappointing is the missing link between Semantic Web and the “cool” technologies and buzzwords. From what we see Semantic Web gives answers to some of the industry’s most challenging problems, but it still doesn’t seem to really find its place in relation to the cloud or big data (Hadoop).

Christine Connors, Chief Ontologist, Knowledgent:

One trend that I have seen is increased interest in the broader spectrum of semantic technologies in the enterprise. Graph stores, NoSQL, schema-less and more flexible systems, ontologies (& ontologists!) and integration with legacy systems. I believe the Big Data movement has had a positive impact on this field. We are hearing more and more about “Big Data Analytics” from our clients, partners and friends. The analytical power brought to bear by the semantic technology stack is sparking curiosity – what is it really? How can these models help me mitigate risk, more accurately predict outcomes, identify hidden intellectual assets, and streamline business processes? Real questions, tough questions: fun challenges!

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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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