Steve O’Hear of TechCrunch reports, “The idea of matching prospective dates based on shared interests is about as old as dating itself. But understanding how one set of interests relate to another, certainly at scale, is arguably something that machines can do a lot more efficiently than humans, so why not harness that capability for match-making purposes. Loveflutter, which soft-launched in New York last month, and gets a UK push today, aims to do just that. Powered by Freebase, the 37-million strong open database of people, places and things acquired by Google in 2010 and now part of the search giant’s Knowledge Graph, the online dating site connects people based on shared interests.” Read more

Swipp, which in January launched its social intelligence platform and consumer social networking app (see our story here), today follows through on the plans it alluded to then of letting businesses leverage its technology for merging social and knowledge streams. Structured data is at the heart of the Swipp platform, with the Freebase entity graph providing reference knowledge and context for topics; its value propositions are that comments are tied to a specific, exact topic and that it creates a real-time Index for users’ social data sentiment scores for each topic that can be combined and sorted by geography, time, gender, and age.

The new Swipp Plus tool suite, the company says, draws on its social intelligence platform to prepare businesses – from consumer brands to content providers – to better connect with customers on today’s social web. Swipp Plus now enables them to leverage capabilities in its platform to add a Swipp widget to their web sites, blogs, maps, QR codes, and various online arenas around pieces of content, particular products, or concepts, and it also is working to build out mobile capabilities for direct feedback.

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Last Friday saw the release of the Wikilinks Corpus from Research at Google, 40 million entities in context strong.

As explained in a blog post by Dave Orr, Amar Subramanya, and Fernando Pereira at Google Research, the Big Data set “involves 40 million total disambiguated mentions within over 10 million web pages — over 100 times bigger than the next largest corpus.” The mentions, the post relates, are found by looking for links to Wikipedia pages where the anchor text of the link closely matches the title of the target Wikipedia page. If each page on Wikipedia is throught of as an entity, then the anchor text can be thought of as a mention of the corresponding entity, it says.

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There’s more than one way to get a taxonomy. A company can go out and buy one for its industry, for instance, but the risk is that the terms may not relate to how it talks about content in its own organization, and the hierarchy may not be the right fit either. That sets up two potential outcomes, says Chris Riley, VP of marketing at Pingar: You wind up having to customize it, or with users who just ignore it.

It’s possible to build one, but that’s a big job and a costly one, too – especially for many enterprises, where there hasn’t traditionally been a focus on structuring content and so the skills to do it aren’t necessarily there. While industries like publishing, oil and gas, life sciences, and pharma have that bent, many other verticals do not. In fact, Riley notes, they may realize they have a content organization problem, but not that what they’d benefit from to address it even goes by the name ‘taxonomy.’

Pingar’s looking to help out those enterprises that want to bring organization to their content, whether or not they’re familiar with the concept of a taxonomy. It just launched its automated Taxonomy Generator Service that uses an organization’s own content to build a taxonomy that mirrors its own way of talking about things and its understanding of relationships between child and parent terms.

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When Don Thorson and Charlie Constantini looked at the social graph – some 1 billlion connected people all sharing information at an incredibly fast pace – they saw a problem, and an opportunity. Data extraction wasn’t playing as big a role in the picture as it could, so the possibility that all those connected users out there could actually be gaining knowledge proportional to the size of the social network wasn’t being realized. How to return more value to end users? Thorson, whose career has spanned the video game, computer, Internet and communications industries and companies including Atari, Apple, Netscape, and Ribbit, says there had to be a way to “unlock what the world thinks about everything with the optimistic view that all of us are smarter than any of us.”

So was Swipp born. The startup – co-founded by CEO Thorson, Chief Swipp officer Constantini, and CTO Ramani “Nara” Narayan (both also Ribbit veterans) – and its new social intelligence platform launched yesterday. Its aim is to extract the wisdom of the crowd in a global, aggregated way with a solid data structure foundation as its starting point. Swipp’s effort to merge the worlds of social tools and knowledge tools is based on organizing data around terms or topics in what Thorson calls a “pure data” approach – not an interpreted or extracted one – allowing for data to be aggregated, displayed, and archived around a specific person, place, or thing.

So, when a consumer “swipps” – enters a topic via the web or a mobile device, adds a comment about it, and scores it so that their rating becomes part of the Swipp Index (its stock index of social intelligence) – he or she gets what Constantini calls a “one-two punch of what the world is saying and the truth.” That is, you get to see what people are saying socially about that exact topic, and the Index, which is the combined social data for each topic that can be sorted by geography, time, gender, and age. For the reference knowledge and the context behind millions of topics, Swipp leverages Freebase and its entity graph of people, places and things.

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What’s new with Freebase? Well, aside from its data now being used by Bing to provide information about entities in a similar way to Google’s Knowledge Graph, a new design of its web client is being tested here.

Its post about the new design highlights these as a few of the client’s biggest changes:

* A search bar at the top of the screen lets you filter the topic display and show any by domain, type or property. When you filter by domain, the page will show all of the types and their properties linked to the current topic. When filtering by type, it will show just the properties within that type and filtering by property will show just that property.

Photo Courtesy: Flickr/Lars Plougmann

In recent blogs we’ve discussed where semantic technologies have gone in 2012, and a bit about where they will go this year (see here, here and here).

Here are some final thoughts from our panel of semantic web experts on what to expect to see as the New Year rings in:

John Breslin,lecturer at NUI Galway, researcher and unit leader at DERI, creator of SIOC, and co-founder of Technology Voice and StreamGlider

Broader deployment of the schema.org terms is likely. In the study by Muehlisen and Bizer in July this year, we saw Open Graph Protocol, DC, FOAF, RSS, SIOC and Creative Commons still topping the ranks of top semantic vocabularies being used. In 2013 and beyond, I expect to see schema.org jump to the top of that list.

Christine Connors, Chief Ontologist, Knowledgent:

I think we will see an uptick in the job market for semantic technologists in the enterprise; primarily in the Fortune 2000. I expect to see some M&A activity as well from systems providers and integrators who recognize the desire to have a semantic component in their product suite. (No, I have no direct knowledge; it is my hunch!)

We will see increased competition from data analytics vendors who try to add RDF, OWL or graphstores to their existing platforms. I anticipate saying, at the end of 2013, that many of these immature deployments will leave some project teams disappointed. The mature vendors will need to put resources into sales and business development, with the right partners for consulting and systems integration, to be ready to respond to calls for proposals and assistance.

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It’s been a big week for news, especially on the East Coast, where Hurricane Sandy punched hard. Add to that the U.S. presidential elections, the fighting in Syria, and the World Series win by the San Francisco Giants.

For those fortunate enough to have a charged iPad, or access to a power outlet (easier said than done in some parts of the country in the wake of the hurricane), a semantically-enabled application aims to bring the news videos that matter to those devices.

Link TV, which had a role in the ViewChange.org project that The Semantic Web Blog covered here, already offers up Link News, a site for global news and documentaries, that also relies on semantic technology to offer a portal to news from around the world. This week, it unveiled the LinkTV World News App for iPad that pulls top world news selected by editors from more than 125 video news outlets worldwide.

Announcing the app, Paul Mason, who became the company’s president and CEO last year (see our coverage here), said,  ”The LinkTV World News app does the heavy lifting so users don’t have to. A team of seasoned journalists using the best semantic ‘smart search’ technology sifts through thousands of newscasts and raw videos to bring people the stories that matter most.”

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Paul Wilton was Technical and development lead for semantic publishing at BBC News and Sport Online during the 2010 World Cup.  Currently he is the Technical architect at Ontoba.  In this interview, a supplement to “Dynamic Semantic Publishing for Beginners”, Paul describes the current landscape for DSP as it applies to news organizations.

Q. Are you seeing a wide disparity in the way that news organizations have approached the creation and use of semantically-linked (or annotated) content?

A. Actually the pattern and often the (general) technical architecture is surprisingly similar. Where things differ are the applications, models used and instance data. This is undoubtedly bleeding edge technology, and typically the impetus to begin investigating the use of linked data, RDF and semantics in the technology stack has come from within the Information Architecture and R&D teams, not from the offices of the CTO/CIO. Maybe this is starting to change now.

Q. Do many news organizations have the resources (staff and/or Content Management Systems) that are able to publish and use semantic data?

A. Not in our experience, but this shouldn’t be a barrier to integrating semantic technologies and publishing linked data.

The key components to adopting semantic publishing – a semantic repository (triple store); appropriate linked data sets; and the ability to semantically annotate your content – can be built alongside an existing Content Management System. Read more

Ontology2 has announced the release of :BaseKB Early Access 2 (EA2), a tool for accessing Freebase data in RDF.

Paul Houle, founder of Ontology 2, says, “:BaseKB is an important milestone for both Freebase and the Semantic Web. :BaseKB opens Freebase to users of SPARQL and other RDF standards.  The superior quality of Freebase data solves data quality problems that have,  so far,  frustrated Linked Data applications.”

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