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Last month at its MarkLogic World 2013 conference, the enterprise NoSQL database platform provider talked semantics as it related to its MarkLogic Server technology that ingests, manages and searches structured, semi-structured, and unstructured data (see our story here). The vendor late last week was scheduled to provide an early access release of MarkLogic 7, formally due by year’s end, to some dozens of initial users.

“People see a convergence of search and semantics,” Stephen Buxton, Director, Product Management, recently told The Semantic Web Blog. To that end, a lot of the vendor’s customers have deployed MarkLogic technology as well as specialized triple stores, but what they really want, he says, is an integrated approach, “a single database that does both individually and both together,” he says. “We see the future of search as semantics and the future of semantics as search, and they are very much converging.” At its recent conference, Buxton says the company demonstrated a MarkLogic app it built to function like Google’s Knowledge Graph to provide an idea of the kinds of things the enterprise might do with both search and semantics together.

Following up on the comments made by MarkLogic CEO Gary Bloom at his keynote address at the conference, Buxton explained that, “the function in MarkLogic we are working on in engineering is a way to store and manage triples in the MarkLogic database natively, right alongside structured and unstructured information – a specialized triples index so queries are very fast, and so you can do SPARQL queries in MarkLogic. So, with MarkLogic 7 we will have a world-class triple store and world-beating information store – no one else does documents, values and triples in combination the way MarkLogic 7 will.”

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Search is a fundamental, a system building block, and something that should be a critical part of enterprise architectures. That’s what Grant Ingersoll, co-founder and CTO at search, discovery and analytics vendor LucidWorks – which leverages the Apache Lucene/Solr open source search project – told an audience at last week’s GigaOM Structure Data event.

The company late last year launched LucidWorks Big Data for developing Big Data applications, which builds on top of its heritage developing the LucidWorks Search solution. “It’s a platform for organizations and developers to build out next-generation data applications,” Ingersoll said in a conversation with the Semantic Web Blog. Its focus is on tight integration of key Apache open source projects and layering with a REST API, to provide developers single-source access to the stack’s richness for creating applications that provide comprehensive search, discovery and analysis of an organization’s vast content and user interactions.

LucidWorks Big Data is made up of Apache Hadoop; the Apache Mahout machine-learning library; Hive, a data warehouse system for Hadoop that facilitates data summarization, ad-hoc queries, and the analysis of large datasets stored in Hadoop-compatible file systems; and Apache OpenNLP, a machine-learning based toolkit for the processing of natural language text that supports common NLP tasks.

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Google Analytics gives web site owners good information about what’s clicking with visitors to their site, how those users got there, and more. But, attaining that insight can be somewhat laborious for those not well-versed in the tool and its interface, says Nick Cassimatis, associate professor in the Department of Cognitive Science at Rensselaer Polytechnic Institute. He’s the founder of natural language processing technology startup SkyPhrase. His take: Apply SkyPhrase to the task, and things get a lot easier.

The startup in February began private beta testing of its NLP interface to Google Analytics. “Google Analytics lets you ask things like how many people from California visited the site last month, or which of your pages were most visited on mobile devices,” says Cassimatis. “Our system lets you ask these questions in natural language and get answers to them” more seamlessly than using Google Analytics alone.

Previous to bringing its NLP help to Google Analytics, SkyPhrase had a public site that let users run natural language searches of their Gmail or Twitter accounts, as well as flights and music.

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Common Crawl, the non-profit organization creating a repository of openly and freely accessible web crawl data, is getting a present from search engine provider blekko. It’s donating its metadata on search engine ranking for 140 million websites and 22 billion webpages to Common Crawl.

“The blekko data donation is a huge benefit to Common Crawl,” Common Crawl director Lisa Green told The Semantic Web Blog. “Knowing what the blekko team is crawling and how they rate those pages allows us to improve our crawler and enrich our corpus for high-value webpages.”

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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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Early in the summer, The Semantic Web Blog introduced readers to Nara, an advanced neural networking service to automate, personalize and curate web dining experiences for users. (See that story here.)

The service is moving ahead with the launch today of its mobile version, as well as in other respects. “We’re now doing a full-on consumer launch of a polished product on both the web and mobile [platforms],” says CTO Nathan Wilson. “People really are clamoring for the mobile component, especially for this [dining] use case.” Versions for both the iPhone’s iOS and Android operating systems are available.

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The recommendation problem is a machine-learning problem, says  startup Jybe, and one that it aims to address with its iPhone app that now is in beta. Coming soon (though not immediately) to the iPhone 5, which will require some redesigning to maximize real estate, the mobile app supports earlier iPhones, the iPod touch and iPads running iOS 4.3 or later.

Unlike services such as Yelp, that are more reviews than recommendations, Jybe takes the “serendipitous discovery” approach to real-world goods and services (movies, books, restaurants, and dishes). Founded by CEO Arnab Bhattacharjee, CTO Tim Converse, and chairman of the board Tuoc Vinh Luong, a team with a slate of experience in the search engine industry at names like Yahoo and Powerset, Jybe looks to provide implicit search, i.e. search without query. “The only way to figure out your interests is to figure out who you are, what you like and surface things interesting for you to consume,” says Bhattacharjee.

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Jolie O’Dell of VentureBeat reports that on Wednesday, “Gnip launched its Historical PowerTrack for Twitter, which will give developers the ability to search, find, analyze, and compare all the tweets ever written, even ones written before the developer in question started scraping Twitter. It’s the same level of access the Library of Congress got when it started archiving and storing all Twitter data, but this time, it’s commercially available. ‘There are a handful of companies that have collected some portion of Twitter data,’ said Gnip COO Chris Moody in a meeting with VentureBeat yesterday. ‘We were able to do it because we partnered with Twitter on it’.” Read more

Dollars to donuts most folks haven’t ever found a place to eat courtesy of neural networking technology before. Generally, Internet searches for spots to have a bite come courtesy of friends’ Facebook recommendations, services like Yelp, and even some semantically-powered offerings such as BooRah, now an Intuit company.

But the collection of neuroscientists, computer scientists, astrophysicists, and creative artists behind Nara, launching into public beta today, have taken the advanced neural networking route to automate, personalize and curate web dining experiences for users – though there’s more to come on the future menu. President and CEO Tom Copeman says of the company, which in April secured $3.6 million of a $4.5 million equity offering, that its cutting-edge neural network and proprietary and patented algorithms and process for analyzing tons of web data, and personalizing it, including considering user feedback on the suggestions it offers, is creating a whole new category.

That is the pure-play digital lifestyle brand that “creates an emotional connection between us and the Web. We’re trying to change how people think about the web, and from sense of what it means to me, and makes sense to me, and how personal it is to me.”

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Amir Efrati of the Wall Street Journal reports that Google has seen a surge in search activity since launching the Knowledge Graph. He writes, “People doing Web searches now see a big box of information and photos related to search queries such as sports teams (try typing “San Francisco Giants”), geography (try “Matterhorn”), attractions (try “Matterhorn Bobsleds”), celebrities (try “Pink”), and science (try “Jupiter” or “Einstein”) located prominently on the right of the search results page. Before the change, Google users might have seen relevant search ads, content boxes with information from Google+, the company’s social network, or nothing at all. The new feature currently draws upon information from sites like Wikipedia, as well as music and movie catalogs that Google has licensed, among other things.” Read more