Posts Tagged ‘semantic technology’

Expert System and WAND Partner for a More Effective Management of Enterprise Information

Expert System LogoBARRINGTON, ILLINOIS–(Marketwired – Oct. 7, 2014) – Expert System US, Inc., a leader in semantic technology, and WAND, Inc, the leader in the development of enterprise taxonomies, today announced a partnership that will enable businesses to implement a simpler, more accurate organization of data and documents.

Making internal and external information more “findable” allows enterprises to be more innovative, to manage the relationships with their customers more effectively and to minimize operational risks. In summary, to make them more competitive. Expert System and WAND will increase the findability of information by effectively integrating the three most important steps in the content management process: Read more

Start Your Innovation Engines

Interop New York took place at the Jacob Javits Center in Manhattan last week. The semantic web wasn’t a focus of the show, but innovation had its place among the various keynotes and sessions. And innovation certainly is a theme that goes hand-in-hand with the semantic web.

byzIn that spirit, we’ll share some comments from some of the speakers about how they embraced concepts and argued for changes that they believed would make them more innovative companies – even when that was a scary thing to do. With any luck, their experience, advice and thoughts may give you some direction when it comes to taking your ideas about how semantic web technologies could help your own business become more innovative, and acting on them:

  •  From Michael Bryzek, co-founder and CTO, Gilt: In discussing the e-retailer’s move to a micro-services architecture, which he said supports the concept of autonomous innovation and is part of implementing a culture where employees can thrive, Bryzek told the audience that accepting the risk of failure was the first step.  “Start with the assumption you’ll fail,” he said. “If you want a chance at innovation, that alleviates some of the pressure because we all agree we are going to do something risky and we are in it together now.” There are only so many great companies in the world, and it’s true you might not make it to be among them, but “it sure is fun and great to work together to try and build something amazing.”

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Drupal Deepens Semantic Web Ties

semtechbiz-10th-125sqAmong the mainstream content management systems, you could make the case that Drupal was the first open source semantic CMS out there. At next week’s Semantic Technology and Business Conference, software engineer Stéphane Corlosquet of Acquia, which provides enterprise-level services around Drupal, and Bock & Co. principal Geoffrey Bock will discuss in this session Drupal’s role as a semantic CMS and how it can help organizations and institutions that are yearning to enrich their data with more semantics – for search engine optimization, yes, but also for more advanced use cases.

“It’s very easy to embed semantics in Drupal,” says Bock, who analyses and consults on digital strategies for content and collaboration. At its core it has the capability to manage semantic entities, and in the upcoming version 8 it takes things to a new level by including schema.org as a foundational data type. “It will become increasingly easier for developers to build and deliver semantically enriched environments,” he says, which can drive a better experience both for clients and stakeholders.

Corlosquet, who has taken a leadership role in building semantic web capabilities into Drupal’s core and maintains the RDF module in Drupal 7 and 8, explains that the closer embrace of schema.org in Drupal is of course a help when it comes to SEO and user engagement, for starters. Google uses content marked up using schema.org to power products like Rich Snippets and Google Now, too.

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Cognitive Computing And Semantic Technology: When Worlds Connect

ccimageIn mid-July Dataversity.net, the sister site of The Semantic Web Blog, hosted a webinar on Understanding The World of Cognitive Computing. Semantic technology naturally came up during the session, which was moderated by Steve Ardire, an advisor to cognitive computing, artificial intelligence, and machine learning startups. You can find a recording of the event here.

Here, you can find a more detailed discussion of the session at large, but below are some excerpts related to how the worlds of cognitive computing and semantic technology interact.

One of the panelists, IBM Big Data Evangelist James Kobielus, discussed his thinking around what’s missing from general discussions of cognitive computing to make it a reality. “How do we normally perceive branches of AI, and clearly the semantic web and semantic analysis related to natural language processing and so much more has been part of the discussion for a long time,” he said. When it comes to finding the sense in multi-structured – including unstructured – content that might be text, audio, images or video, “what’s absolutely essential is that as you extract the patterns you are able to tag the patterns, the data, the streams, really deepen the metadata that gets associated with that content and share that metadata downstream to all consuming applications so that they can fully interpret all that content, those objects…[in] whatever the relevant context is.”

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Attensity Adds to Patent Portfolio for Unstructured Data Analysis Technology

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Redwood City, CA – July 8, 2014 – Attensity (@Attensity), the leading provider of corporate insight solutions based on proprietary data contextualization, today announced the issuance of US Patent No. 8,645,395 on unstructured data sentiment analysis. This patent was awarded to Biz360 Inc., a wholly owned subsidiary of Attensity Group, Inc., and adds to the nearly dozen that Attensity currently holds for analysis of unstructured data. Read more

How Semantic Technology is Improving the Financial Service Industry

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Marty Loughlin of Wall Street & Technology recently noted that in this era of “massive business and IT transformation,” organizations in the financial industry “will need to change how they track, manage, and consume data. For many organizations, this data is not easily accessible — it is distributed across the organization, often trapped in local business units, applications, data warehouses, spreadsheets, and documents. Traditional technologies are struggling to address this challenge and many believe a new approach is required. Some of the new big-data solutions do help. They are good at liberating and colocating data. However, they often struggle to make it usable. Creating a ‘data lake’ where rigid structure is not required can result in yet another silo of unusable data where context, meaning, and sources are lost. Many organizations are turning to semantic technology for the answer.” Read more

Why the Role of the Data Scientist is Growing

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Kevin Casey of Information Week recently wrote, “Old-school organizations will fuel the next swell of data-driven initiatives in IT. So what’s in store for the early movers and, specifically, their big-data professionals? How will the data scientist and similar roles evolve? ‘The role is becoming bigger,’ said Olly Downs, chief scientist at big-data analytics firm Globys, in a recent interview. By bigger, he means in every way — what was once a niche is now, at least in some companies, a driving force.” Read more

The Varied Definitions of Machine Learning

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James Kobielus of Info World recently shared his thoughts on the best definition for machine learning. He writes, “Increasingly, the term ‘machine learning’ is… beginning to acquire a catch-all status. Or, at the very least, machine learning has become a convenient handle that today’s data scientists use to refer to the wide range of leading-edge techniques for automating knowledge and pattern discovery from fresh data, much of it unstructured. People’s working definitions of machine learning seem to be creeping into broader, vaguer territory. That’s my impression from reading the recent article “Learning and Teaching Machine Learning: A Personal Journey.” In it, author Joseph R. Barr of San Diego State University and True Bearing Analytics discusses both the history of machine learning and his own education in the topic. He states that ‘it’s safe to regard machine learning, data mining, predictive analysis, and advanced analytics as more or less synonymous’.” Read more

Extracting Value from Big Data Requires Machine Learning

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James Kobielus of InfoWorld recently wrote, “Machine-generated log data is the dark matter of the big data cosmos. It is generated at every layer, node, and component within distributed information technology ecosystems, including smartphones and Internet-of-things endpoints… Clearly, automation is key to finding insights within log data, especially as it all scales into big data territory. Automation can ensure that data collection, analytical processing, and rule- and event-driven responses to what the data reveals are executed as rapidly as the data flows. Key enablers for scalable log-analysis automation include machine-data integration middleware, business rules management systems, semantic analysis, stream computing platforms, and machine-learning algorithms.? Read more

WEBINAR: Using Semantic Technology to Drive Agile Analytics

Webinar Title: Using Semantic Technology to Drive Agile AnalyticsIn case you missed the outstanding webinar, “Using Semantic Technology to Drive Agile Analytics” delivered earlier this week by David Read and Scott Van Buren of Blue Slate Solutions, the recording and slides are now available (and posted below). The webinar was co-produced by SemanticWeb.com and DATAVERSITY.net and runs for one hour, including a Q&A session with the audience that attended the live broadcast.

The presenters will also deliver a half-day tutorial at the upcoming Semantic Technology & Business Conference: “Integrating Data Using Semantic Technology.” Registration for the conference is now open.

If you watch, please use the comments section below to leave your questions, comments, and ideas for webinars you would like to see in the future.

About the Webinar

How do you accelerate data warehousing to meet the demands of the data-driven economy? Semantic technology provides an agile platform to bring data together, focus on data that matters and ultimately derive a target data model that can be easily extended. This webinar will present a semantically-based data federation case study and highlight the semantic components that facilitate agile data federation in the enterprise.

(Presentation Video and Slides after the jump…)
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