Online publishers and other content providers have a new analytics tool to help them understand what their readers care about and use that information to better connect them to their sites’ relevant and compelling content. Launching today is Dash, based on the predictive content analytics platform Parse.ly. The technology crawls every article page for Parse.ly’s publisher-partners, and analyzes, in real time and at scale, the text to identify relevant topics to group related content together. Behind this lies natural language processing technology, which uses language queues hidden inside the text to determine its affiliated topics. To date Dash has extracted over 350,000 unique topics through all the URLs is has crawled during private beta for a healthy taxonomy of topics across the web being consumed by users.

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Announcing Semantic Tech & Business Conference - San Francisco 2012

Semantic Tech & Business Conference is returning to San Francisco in June! Join us from June 3-7 for complete coverage of Big Data, Linked Data, Extreme Information Management, and Semantic Web. From breakthrough approaches to solving business problems to the big data implications of fast–evolving technologies, SemTechBiz provides you with an unparalleled interactive experience and delivers tangible business value. We're offering a special early rate when you register by February 17. Sign up now!

Christine Connors has written a short history of classification, noting how today’s taxonomies play into the grand scheme of things. Connors begins, “The earliest known means of classifying an object and keeping it in order are girginakku. These are ancient Mesopotamian clay tablets that were attached to scrolls and tablets and used to identify the contents. Examples of approximately 5300 years in age can be found in the British Museum. Girginakku at Glencairn. These clay tablets were used for many purposes, including cataloging. The famous Library of Alexandria in Egypt housed one of the earliest forms of library catalog in the third century BCE. The library reportedly housed more than 120,000 scrolls which were stored in bins categorized by subject.” Read more

A recent article reports, “The Real Story Group just released a new Advisory Paper: ‘Taxonomy Management Tools: A Comparative Evaluation.’ Taxonomy management tools have become a key player in end-to-end architectures for tackling content organization challenges, but the tools vary substantially in approach, and the marketplace as a whole remains somewhat immature, according to The Real Story Group, an independent analyst firm that evaluates web and enterprise technologies.” Read more

If you missed the excellent live webcast introduction to SKOS by Bob DuCharme (of TopQuadrant and the recently released Learning SPARQL), the recorded webcast is now available.

You will probably find this webcast useful if: Read more

Eqentia added to its content discovery and knowledge management portal this week features to recommend additional content or people connections to end users and content curators. But it’s also been doing some other interesting work in the past couple of months on the back-end that draws on semantic technologies to help curators and content administrators of custom Eqentia-based knowledge portals with their taxonomies.

This is where YAGO (Yet Another Great Ontology), a semantic knowledge base some 2 million entities strong that extracts structured information from Wikipedia via DBpedia, comes into play. In essence, YAGO reveals Wikipedia to the Semantic Web, explains CEO William Mougayar.

YAGO gives Eqentia a list of companies and persons to to use for its auto-complete list. Once the user clicks what he wants from the auto complete list — say “Steve Jobs”– Eqentia takes “Steve_Jobs” (note the underscore) and builds a SPARQL query to DBpedia that extracts all related labels by which DBpedia knows “Steve Jobs.” As Eqentia explains it, the upshot is that Eqentia uses a local copy of YAGO to quickly search companies and persons to get a unique “key” that is shared by all 3 systems (YAGO, DBpedia and Wikipedia), and which is then used to query DBpedia for any related labels.

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To begin: Semantics is the study of meaning. It focuses on the relation between words and phrases and due to the relationship what they mean in context. Semantics is a game changer when it comes to the management of large volumes of structured and unstructured data. Having the ability to understand words in context using lexical or linguistic semantics will drive linked data initiatives and ultimately, as many believe, will make Web 3.0 a reality. With this in mind, possessing a “semantic platform” is the new marketing target for many software companies and they are quickly moving to describe themselves as a semantic platform in hopes of aligning themselves with the semantic snowball as it continues to gather speed.

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Big Data is throwing its weight around, and perhaps not entirely the way originally expected. Will your business be able to lift the load?

Getting onboard with semantic search technologies is one way to build muscle to meet the challenge of filtering through the onrush of information. “The concept of Big Data was traditionally associated with databases and such structured information,” says Luca Scagliarini, VP, Strategic and Business Development of Expert System. To this end, organizations put a lot of focus on pulling that information together in data warehouses and creating MDM (Master Data Management) initiatives for defining and managing the entities in them.

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A survey on controlled vocabularies is coming to a close. We reported some of the survey’s preliminary findings a few weeks ago, and now more preliminary findings have been released prior to the May 18^th close of the survey. The article states, “143 people whose organization already make use of controlled vocabularies answered the question ‘Which kind of controlled vocabulary do you use or plan to use in your applications?’ The results so far show that lightweight models like taxonomies and thesauri are somewhat preferred over ontologies.” Read more

A recent article out of the Semantic Web Company explains how Google Refine can be used to transform spreadsheets into Simple Knowledge Organization System (SKOS). The article uses the example of the Global Industry Classification Standard (GICS), “an industry taxonomy designed to categorize any private company.” GICS is “mainly used by the financial community to aid in the investment research process.”

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The iSchool Institute of the University of Toronto has put together a web resource called The Taxonomy Guide. According to the Institute, “Enterprises are increasingly turning to taxonomies to navigate through structured and unstructured information dispersed through the organization… The Taxonomy Guide is a web resource of organized, structured, and clearly written content on building and implementing an enterprise taxonomy.” Read more