With the support of Google Developers, SindiceTech has announced the availability of its Freebase Distribution for the cloud. According to SindiceTech, “Freebase is an amazing data resource at the core of Google’s ‘Knowledge Graph’. Freebase data is available for full download but today, using it ‘as a whole’ is all but simple. The SindiceTech Freebase distribution solves that by providing all the Freebase knowledge preloaded in an RDF specific database (also called triplestore) and equipped with a set of tools that make it much easier to compose queries and understand the data as a whole.”
Posts Tagged ‘cloud’
Nara is officially on its way from being solely a consumer-lifestyle brand – with its neural networking technology helping users find dining and hotel experiences that match their tastes – to also being the power behind other companies’ recommendation and curation offerings. This summer it made a deal with Singapore Communications’ Singtel Digital Life Division to use its technology to help their users hone in on personalized eating options, and today that online food and dining guide, HungryGoWhereMalysia, goes live.
But Singtel won’t be the only outside party to plug into Nara’s backbone, as the company today also is announcing that it is licensing its capabilities to other parties interested in leveraging them. “An enterprise can plug into our neural network in the cloud through our API,” says CEO Tom Copeman, accessing its smarts for analyzing and then personalizing tons of data from anywhere on the web, tailored to the type of service they’d like to offer.
HungryGoWhereMalaysia, for example, is much like Nara for personalized restaurant discovery here in the states, except culturally branded to their markets; local consumers will get tailored list of dining recommendations from over 35,000 restaurants throughout the country, and as the service gets to know them better, suggestions will be more finely honed to match their Digital DNA profiles. “We believe we’re the first in computer science to receive third-party data from outside sources through our API into our neural network, to make the calculations and comparisons, and send back down a more organized, personalized and targeted selections based on individual preferences.”
Samsung Galaxy S4 or Apple iPhone 5? Many users are contemplating which smartphone upgrade is the right one for them. PolyVista, a BI text analytics tool that specializes in finding insights and sentiment in text-based data like online reviews, social media, blogs and surveys, wants to help out. It just published the results it gleaned from its PolyVista Zoom review analysis technology, which looked at online review text and analyzed each topic for positive and negative sentiment.
While both garnered more positive than negative commentary on social media, it concludes that the Galaxy S4 got a slight — 8 percent — edge over the iPhone 5.
That’s something both Apple and Samsung would like to know, too. And providing insights like that “from either structured or unstructured data to a business-person with a minimal amount of work by them” is what the company is aiming for, says Shahbaz Anwar, PolyVista CEO. Its value proposition, he says, is bringing text analytics via the cloud to companies that can’t afford to make the investments in expertise, talent software and infrastructure to do it in-house, particularly in verticals such as high-tech and services.
The enterprise version of Bottlenose has formally launched. Now dubbed Nerve Center, the service to provide real-time trend intelligence for brands and businesses, which The Semantic Web Blog previewed here, includes a dashboard featuring live visualization of all trending topics, hashtags and people, top positive and negative influences and sentiment trends, trending images, videos, links and popular messages, the ability to view trending messages by types (complaints vs. endorsements, for example) and real-time KPIs. As with its original service, Nerve Center leverages the company’s Sonar technology to automatically detect new topics and trends that matter to the enterprise.
“Broadly speaking, every large enterprise has to be doing social listening and social analytics,” CEO Nova Spivack told The Semantic Web Blog in an earlier interview, “including in realtime, which is one thing we specialize in. I don’t think any other product out there shows change as it happens as we do.” It’s important, he said, to understand that Bottlenose focuses on the discovery of trends, not just finding what users explicitly search for or track. Part of the release, he added, “will be some pretty powerful alerting to tell you when there is something to look at.”
Bottlenose earlier this month raised $3.6 million in Series A funding to help with its launch of Bottlenose Enterprise, the upcoming tool aimed at helping large companies discover and visualize trends from among a host of data sources, measuring and comparing them for those with the most “trendfluence.” Users will get a realtime dynamic view of change as it happens and a host of analytics for automating insights, the company says.
The Enterprise edition will be a big departure from the current Bottlenose Lite version for individual professionals. That difference starts with the amount of data it can handle. “The free, Lite version looks only at public API data like Twitter’s. The enterprise version uses the firehose,” says CEO Nova Spivack. Another big difference is that the enterprise version adds a lot more views and analytics, in comparison to the personal-use edition, where its Sonar technology provides the chief service of real-time detection of talk around topics personalized to users’ interests so they can visualize and track those topics over time.
Spivack calls what Enterprise does “enterprise-scale trend detection in the cloud,” leveraging a massive Hadoop infrastructure and technologies including Cassandra, MongoDB, and the Storm distributed realtime computation system to process data for deep dives. The cloud handles the computation, and results are shared at the edge, where certain kinds of analytics and visualizations occur locally in the browser for a realtime expience with no latency. With sources such as social streams, stock information, even a company’s proprietary data, and more, the Enterprise version helps brands discover important trends like keywords to bid on or viral content to share, who are their influencers and detractors, what sentiment and demographic movements are taking shape, and to create correlations across data points, too.
The cloud’s role in processing big semantic data sets was recently highlighted in early April when DERI and Fujitsu Laboratories announced a new data storage technology for storing and querying Linked Open Data that resides on a cloud-based platform (see our story here).
The cloud conversation, with storage as one key discussion point, will continue to be an active one in Big Data circles, whether users are working with massive, connected Linked Data sets or trying to run NLP across the Twitter firehose. CloudSigma, for example, recently publicly disclosed that it is using an all solid-state drive (SSD) solution for its public cloud offering that lets users purchase CPU, RAM, storage and bandwidth independently. The use of SSD, says CEO Robert Jenkins, avoids the problem that spinning disks have with the randomized, multi-tenant access of a public cloud that leads to storage bottlenecks and curbs performance.
That, combined with the company’s approach of letting customers size virtual machine resources as they like, as well as leverage exposed advanced hypervisor settings to optimize for their particular applications, he says, brings the use of the public cloud infrastructure closer to what companies can get out of private cloud environments, and at a price-performance win.
Enterprise NoSQL database platform provider MarkLogic has come into some cash: a $25 million round of growth capital from investors including Sequoia Capital, Tenaya Capital, Northgate Capital, CEO Gary Bloom and other corporate executives. Yesterday, at the company’s MarkLogic World 2013 conference, Bloom also prepared the audience to hear more today from company executives about MarkLogic’s next steps in semantics for its MarkLogic Server technology that ingests, manages and searches structured, semi-structured, and unstructured data.
“The way to think about this is that when we look at semantics, we didn’t … say we just want to check a box on semantics,” Bloom said, by working with partners on some low-hanging fruit – although it will be collaborating with them on various semantic enrichment capabilities. “We think semantics is critical technology, and more interesting I believe is that it is a critical technology that is both a search technology as well as a database technology.” Others in the marketplace will focus on changing their search engines to do semantics, but optimum results won’t come if all that’s being done is layering in semantics at the search level, he said.
It’s April Fool’s Day on the Web, and we’re sensing some semantic allusions and downright sentiment analytics assertions in today’s pranks. Have a look:
- Head over to your Google search engine and you’ll be teased to find out what that smell is with Google Nose. or, as they describe it, the new scentsation in search. Go beyond type, talk, and touch for a new notation of sensation, it promises. The Internet sommelier, Google explains, comes with an expertly curated Knowledge Panels to pair images, descriptions, and aromas. While it credits new technologies such as StreetSense (responsible for Google inhaling and indexing millions of atmospheric miles), and Android Ambient Odor Detection (which collects smells via the mobile OS), it seems to me that the Knowledge Graph had to have a hand in this one.
Whisk Lands U.K. Food Network, More Funding; Looks Next To U.S. Shores And Using Its Semantic Sense To Propel New Foodie Features
Whisk, the U.K.-based service for matching online recipes with online ingredients-shopping, went live in a big way at year’s end, with a partnership with TV channel and recipe publisher Food Network. As its iOS and Android apps rolled out to accompany its browser plug-in, Food Network in the U.K. featured a button on its recipe search engine for a widget that taps into the service, which is underpinned by semantic technology and a cloud infrastructure. A recent second round of angel funding also has taken the service’s total investment to more than £500,000.
Whisk co-founder Craig Edmunds reports about 12,000 app downloads so far, and about a 1.5 percent steady click-through from the button on the publisher’s site – right where it expected to be at this point, he says. Getting the big-name Food Network signed on actually changed plans a bit for the service, which The Semantic Web Blog covered earlier here, and whose co-founder Nick Holzherr was a keynote speaker at the London SemTech event.
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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