Insight

Oleg Shilovitsky of Inforbix recently described how Inforbix addresses disambiguation without so-called icebergs of information. Shilovitsky begins by quoting another article out of TopQuadrant: “Increasing regulatory and competitive demands on the business are forcing decision making to be more timely, and to be more integrated across the traditional business boundaries. However these icebergs are getting in the way of effective decision making.  One way to make any or all of this information available to consumers is to create the bigger iceberg. ‘Simply’ create the relational database schema that covers every past, current, and future business need, and build adapters to populate this database from the operational data stores. Unfortunately this mega-store can only get more complex as it has to keep up with an expanding scope of information required to support the decision making processes.” Read more

Bob DuCharme, author and speaker, has provided an excellent example of one of the benefits RDF has over XML. In his example, DuCharme shows how to perform a simple federated query with RDF across two different address books. He writes, “Once, at an XML Summer School session, I was giving a talk about semantic web technology to a group that included several presenters from other sessions. This included Henry Thompson, who I’ve known since the SGML days. He was still a bit skeptical about RDF, and said that RDF was in the same situation as XML—that if he and I stored similar information using different vocabularies, we’d still have to convert his to use the same vocabulary as mine or vice versa before we could use our data together.” Read more

[Editor's Note: This guest post is by Tom Reamy, Chief Knowledge Architect and founder of KAPS Group, a group of knowledge architecture, taxonomy, and eLearning consultants. Tom has 20 years of experience in information architecture, intranet management and consulting, and education and training software.  Tom will be presenting a tutorial, Text Analytics for Semantic Applications and moderating a panel, Emotional Semantics - Beyond Sentiment at the upcoming SemTechBiz Conference in San Francisco.]

While sentiment analysis continues to generate a lot of press, it is not clear how much real value organizations are deriving from it.  One reason for that is that the standard approach to sentiment has been mostly statistical and/or long lists of sentiment terms.  However, if you add in other, advanced text analytics capabilities such as auto-categorization using advanced operators, you can not only develop more sophisticated sentiment analysis, you can also develop a whole new class of applications that either enhance and/or go beyond simple sentiment analysis.

These advanced operators include such commands as DEST_6 (count two words as a positive indicator only if they are with 6 words of each other) or SENT (only count words in the same sentence).

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Mike Bergman recently gave a talk in which he discussed how “the pragmatic contributions of semantic technologies reside more in mindsets, information models and architectures than in ‘linked data’ as currently practiced.” He writes, “No matter how expressed, the idea behind all of these various [Semantic Web related] terms has in essence been to make meaningful connections, to provide the frameworks for interoperability. Interoperability means getting disparate sources of data to relate to each other, as a means of moving from data to information. Interoperability requires that source and receiver share a vocabulary about what things mean, as well as shared understandings about the associations or degree of relationship between the items being linked.” Read more

The Economist has published an article, Bit Rot, regarding how the world is losing its ability to reconstruct history. The article states, “Picture yourself as a historian in 2035, trying to make sense of this year’s American election campaign. Many of the websites and blogs now abuzz with news and comment will have long since perished. Data stored electronically decays. Many floppy disks from the early digital age are already unreadable. If you are lucky, copies of campaign material, and of e-mails and other materials (including declassified official documents), will be available in public libraries. But will you be able to read them? Already, NASA has lost data from some of its earliest missions to the moon because the machines used to read the tapes were scrapped and cannot be rebuilt.” Read more

Mastufa Ahmed recently interviewed Luc Barthelet, Executive Director of Wolfram|Alpha to learn more about the company’s search algorithm. Asked about what semantic web technologies Wolfram uses, Barthelet responded, “Wolfram|Alpha is not searching the Semantic Web per se. It takes search queries and maps them to an exact semantic understanding of the query, which is then processed against its curated knowledge base. The main technology used is Mathematica whose language is used to describe the semantic queries, and Mathematica technology is used to build up the natural language parser, the data curation pipeline and perform the data processing, computation and visualization.” Read more

James Stevenson has shared his insights regarding the humanization of computing. He writes, “When Nicolaus Copernicus established that the earth moves around the sun he transformed our understanding of the solar system. The rise in digital devices such as PCs, laptops and smartphones, that we use to access personal and corporate information on a daily basis is having a similar impact on our expectations of computing, and has revolutionised the way we live our lives. We are now at a stage when IT is beginning to blend into the background and technology is everywhere.”

He continues, “The availability of omniscient network connections means that we are ‘always online’ and constantly connected to knowledge, people and things… We now live in a networked economy where we revolve around data that is accessed through a variety of digital devices held together by the web and available on demand. Read more

Are you wondering why your product pages don’t stand out in search results like those from Amazon (shown below) or other competing e-commerce websites? These expanded results are commonly known as Rich Snippets (as named by Google) and are the result of having your HTML structured correctly with semantic markup. Whether you’re savvy to HTML5 and the latest design trends, or you haven’t updated your website code in years, this is article will explain why it’s important you structure your data properly utilizing semantic standards.

There are a number of ways to structure your data to make it more relevant to search engines, as well as social media sites. As an e-commerce retailer it is important to understand which of these standards you should consider including in your website. You should take some time to ensure you are implementing semantic markup, and doing it correctly. It has the power to better inform potential customers with upfront knowledge prior to landing on your site. Customers can see product reviews, pricing and stock information, and even images before clicking through to your website. This can lead to increased click-through rates, improve conversions, and generally enhance your SEO objectives.

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Luca Scagliarini recently shared his insight into why he believes semantics will play an important role in the future of technology. He writes, “As a kid growing up in Milan I was obsessed with two things:  sports and the future… While other kids probably dreamed about having superpowers, my dreams were about a future that was more grounded in possibility than fantasy, about inventions that, with the right combination of genius and determination, were possible. Having my own personal television, one small enough to take anywhere and where I could watch anything I wanted, anytime, was something I knew would come eventually. And while the mini TV was an encouraging sign, the technology was still many years away.” Read more

Ivan Herman recently offered some insight into how Watson actually works. Herman reports, “I was at Chris Welty’s keynote yesterday at the WWW2012 Conference. His talk was on Jeopardy/Watson and, although this is not the first time I heard/saw something on Watson, some things really became clear only at his keynote. Namely: what is really the central paradigm that made the question answering mechanism so successful in the case of Watson? Well… query answering in Watson is not some sort of a deterministic algorithm that turns a natural language question into a query into a huge set of data. This approach does not work.” Read more