Want web sites to run as smooth as silk? So do the developers behind Silk, who’ve been working the last couple of years to make it easy to apply semantics to create more powerful web sites, with information that can be used more effectively.

Silk, which The Semantic Web Blog previously has covered here and here, now is in the process of testing its WYSIWYG Silk Editor with a select user set, and is slowly inviting more interested parties to get involved. It expects to release it publicly soon. The simplicity of the Silk Editor, says Sander Koppelaar, head of business development, is that it looks very much like familiar environments – think a graphical Wiki – while supporting tagging information on a page, such as the population or capital of Amsterdam, if that were the subject.

“That way you first create pages that are very handy for users because they are built for humans, containing text and images you’d see on a normal web site,” he says. “But more or less without noticing it you build on your data model and can start to use that to create the great overviews and answer actual questions about the data.”

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Announcing Semantic Tech & Business Conference - San Francisco 2012

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Former Paypal and Intuit CEO Bill Harris these days is heading up financial advisory service Personal Capital, which now is adding an independent media property to its portfolio to aggregate and deliver financial news to individuals. That new property, Daily Capital, launches today and is powered by Eqentia’s semantic technology. Eqentia offers a content discovery and knowledge management portal for consumers, and also has other enterprises using its technology for their backbone portal infrastructures. But Eqentia CEO William Mougayar thinks this deal is likely the biggest one so far in terms of how much visibility it’s going to get and its potential to grow.

As Harris explains to The Semantic Web Blog in an email interview, Personal Capital provides clients with a holistic view of their complex financial lives, “and the mission of Daily Capital is the same: to cut through the clutter and highlight the best financial content from around the Web.”

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A recent article reports, “Many newspapers and other traditional media entities still think of themselves as delivering their content in a specific package… But few are thinking about their businesses in radically different ways — as content-generating engines with multiple delivery methods, or as platforms for data, around which other things can be built. USA Today appears to be moving in this direction, by opening up its data for others to use and even commercialize, following in the footsteps of The Guardian and its ground-breaking open platform.” Read more

A few short years ago, a group of semantic technology companies rode a wave of venture capital and inflated expectation. They were going to change the world. They were going to bring semantic technologies to the mainstream. They were going to make people very rich. They were the must-have keynotes of the conference circuit. And then, one by one, they disappeared. Powerset vanished inside Microsoft, to do something for Bing. Twine vanished inside Evri, amid rumours of a fire sale and investors covering their backs. Freebase vanished inside Google, and bits of Freebase DNA routinely pop up across Google’s sprawling empire. And Siri vanished inside Apple, as we scrambled to understand whether the Cupertino money machine was after semantic smarts or ‘just’ speech recognition technology. Now, though, the rumours suggest that Siri may be back, and that it’s going to be the thing that makes the next iPhone a compelling buy. Read more

We sat down with Mike Tung, CEO of Diffbot to learn more about this innovative technology that takes a different approach to deriving meaning from web pages.

SemanticWeb.com: What is Diffbot?
Mike Tung: Diffbot is a technology that allows software applications to interpret web pages the way human beings do–visually.  We offer an API to developers that lets them visually extract semantic information from web pages depending on the page type.  We’ve observed that the entire web can be classified into roughly 30 structural page types and have trained our visual extraction algorithm on two of those page types so far–frontpage and article pages.

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On the way from Infochimps: Its Geo APIs that bring to developers data from open sources such as GeoNames and The National Climate Data Center, as well as licensed sources such as Locationary and Foursquare.  Now for the twist: The data marketplace is semantifying the geo data with a schema.org approach. This is just the first step in a broader plan to format all data to which its new and existing APIs provide access to in a unified way.

As CTO Flip Kromer explains it, Infochimps takes from schema.org the collection of types it defines. “That was designed for microformat markup in web pages. And we say why not take this tastefully done collection of types and make it so that it can be used by mobile phone and web developers,” he says, so that they can easily and in a unified way build on the databases to which Infochimps provides access. “That if we map that back to a JSON HTTP API world, that’s a really good thing that unlocks a lot of power for developers.”

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The media industry has had a complicated relationship with the Web, and that’s putting it kindly. While other sectors pretty quickly realized ways to take advantage of that new thing called the Internet – to sell goods, accelerate supply chains, and build deeper customer relationships – established content providers spent years trying to figure it out. And many still are tussling with big issues, such as whether or not to charge for access to content.

Given the Web’s impact on their business model and their revenues, you can forgive publishers if they might prefer if the darn Internet just stood still for a few minutes and let them catch their breaths and catch up.  Since that isn’t about to happen, the thing to do is to make peace with those changes, many of them thanks to Semantic Web technologies – and figure out fast how they’re going to profit from them.

They’ll have an opportunity to do just that at the upcoming Semantic Web Media Summit in New York City, whose speakers will include Michael Dunn, VP and CTO at Hearst Interactive Media on the topic of why media companies should be interested in this critical part of the Web 3.0 world.

Dunn sees a number of reasons for using Semantic Web technologies as the means for structuring the wealth of content that publishers produce. There’s improving its discoverability by the world via search and social, of course, but it matters for internal operations, too. And add to that the relationship with online advertising so that content can be better monetized.

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Social media intelligence and analytics provider ViralHeat is making its sentiment engine, which it claims as one of the biggest repositories of sentiment data on the market, available for free to developers as an API. The company has been building that engine in conjunction with its agency and big-brand customers (think the likes of Dell) the last few years, and is hoping that the move will open the door to new applications of sentiment analytics, as well as deliver benefits that will profit its paying clients.

“The key for brands and agencies is sentiment,” says CEO Raj Kadam, and ViralHeat got started down that road with a keyword dictionary approach to analyzing social media that proved disappointing. It led to a lot of neutral vs. positive or negative conclusions, and accuracy wasn’t a strong suit. That’s when it turned to its clients to take things up a few levels. “We scrapped that first approach and started building a really large-scale machine learning cluster focused on speed – we get hundreds of millions of mentions a week – and also on accuracy,” he says. Today, the technology runs mentions through its sentiment cluster and gets a sentiment score back, and from there humans play a role in further assessing the text and passing it back to continually train the engine.

Its speed, scalability, and training are what Kadam considers the features that differentiate its Python-built sentiment web service platform from other vendors in the space, and it’s that same Sentiment API that it’s opening up to others. Kadam says the fact that it can quickly do its work, tagging the sentiment score and its accuracy probability on the fly, is one reason why it can open up the API. “If that cluster was really slow it would take us days and probably a large swath wouldn’t get tagged,” he says. He says the latency on competitive systems is “incredible. It’s like batch processing. You send the data in and wait a really long time to get results. Ours is just completely real time.”

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On the way from Saplo – that’s the company whose tradeshow trademark is the wearing of shocking green suits by CEO Mattias Tyrberg and his co-founders – is a Prediction API for its text analytics platform. The vendor already provides through its API access to services for entity and topic tagging, related and similar articles, sentiment analysis and contextual recognition upon which developers can build applications.

The Prediction API, due around summer’s end, seeks to predict outcomes from text, as Tyrberg describes it. That is, it assesses how a company name or any other word has been described in text and  finds a correlation between that and expected outcomes, such as sales volumes.

It works by having the user submit historic text and historic data points, from which the technology analyzes the relationship between the meaning of the text and the data that the user wants to have predicted (it also will return data of how good it believes it can predict the outcome, Tyrberg says). After that, the user submits new text data to Saplo for a new time period, and based on that text Saplo returns a prediction of the next outcome.

“Think of it like BI,” says Tyrberg. “You might be able to predict new numbers based on previous numbers, but a lot of information that is available is in written text, and we can find the correlations between the meaning of that text and numerical data.”

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You may know Wordnik from subscribing to its Word of the Day service (by the way, today that word is eloign). Or perhaps you know it from some of the apps that have used its API – such as Freebase WordNet Explorer, or one of the many mobile ones that let users access direct features of the system through their smart phones.

Now comes something new on the API front: Word Graph is the latest result of some three years of algorithm development around analyzing the digital text that Wordnik has collected from partners, to understand the relationship between words in order to derive meaning. Word Graph matches content based on digital text from partners who need to understand more of what their content says and is, and to help them and their services make decisions based on that understanding.

In that respect, it’s taking Wordnik’s API services closer to helping accomplish business requirements, rather than drive neat B-to-C apps, from crossword puzzles to jumble games to pronunciation voice services, where its APIs have currently mostly been employed.

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