on: October 31, 2016, by: Ann Kelly
What is an ontology? In simple terms, an ontology is a representational system which defines the concepts, topics, subjects and the relationships within a subject domain. Models such as taxonomies, ontologies, controlled vocabularies and thesauri allow organizations to identify and create a consistent language, which users understand and describes the organization, processes and customers so they can:...
on: October 18, 2016, by: Ann Kelly
Today whether you operate in capital markets, banking, or the insurance industry, you need solid information to make decisions that drive positive organization, stakeholder and customer outcomes. The key to managing risk and improving ROI in a world where the amount of digital information continues to explode is dependent upon an organizations ability to rapidly access, manage and make sense of that information. Unfortunately it’s not that simple. Information is scattered throughout the enterprise, is not accessible and each department, group and project uses a language and vocabulary that is unique. The ability to create a common vocabulary, which can be used to apply the context and meaning to all enterprise information and leverage it to support regulatory compliance efforts is key to successful results.
on: October 04, 2016, by: Ann Kelly
Recently I’ve been trying to explain to some very bright people who have significant knowledge about “data and analytics”, the difference between “relational thinking” and “semantic thinking”. These folks have a deep background in relational data, but very little knowledge of semantics. And like many people, they have sort of conflated “semantic technology” with “Semantic Web” and have mentally consigned the topic to the category of overwrought, futuristic and unrealistic musings.
on: September 26, 2016, by: Ann Kelly
In today’s enterprise, unstructured information has become one of the most valuable assets of the organization and its rate of growth is staggering. The need to extract information from internal and external sources and integrate it into existing systems for use in key business decisions is critical to successful business outcomes. Yet without a mechanism to apply context and meaning to information, the enterprise cannot integrate it into their systems. Semaphore, Smartlogic’s semantic platform, has been carefully architected to address this problem.
on: September 19, 2016, by: Ann Kelly
About two weeks ago, I saw an article (actually, one of my colleagues posted it on our intranet) from the MIT Technology Review about the limitations of Artificial Intelligence. The article is here for those of you who want to read it in full, but the fundamental concept is; while AI has made great strides in the last 20 years or so (see the recent win by Google’s AlphaGo over Lee Sodol, who is thought to be one of the best Go players of all time), it is still fundamentally inadequate in one respect – we have not yet built a machine that can carry on a conversation with anything remotely approximating human facility. Quite simply, the computer does not understand the meaning of words that it is using and is therefore unable to use them intelligently.
on: September 12, 2016, by: Steve Rice
At Smartlogic, we're committed to providing our customers with a reliable service platform. Today we are announcing "Service Status," an online, interactive web site, which provides a real-time view of Smartlogic services to help you keep your business operating 24 hours a day, 7 days a week.
on: September 06, 2016, by: Ann Kelly
Smartlogic Semaphore is used by global organizations to unify the information in their enterprise by consistently labeling data, harmonizing their vocabulary, describing the meaning of data and extracting facts from information assets.
on: August 30, 2016, by: Ann Kelly
Recently one of our Twitter followers asked if we agreed with the way Gartner has positioned taxonomy and ontology management on the 2016 Emerging Technologies Hype Cycle. The technology profile (or “dot” as they are fondly called) is halfway between the Peak of Inflated Expectations and the Trough of Disillusionment with an estimated maturity date of more than 10 years.
on: August 22, 2016, by: Ann Kelly
Classification is the process of describing a piece of information (a contract, a proposal, a policy), what it’s about (subjects, topics, themes), and how it should be managed (distributed, secured, archived) by applying one or more metadata tags. Metadata can be applied manually by humans or automatically using technology. Where manual classification relies on a human to read and classify information by selecting the right metadata tags, automatic classification uses statistical methods or model-driven rules to precisely, consistently and efficiently apply the metadata.
on: August 15, 2016, by: Ann Kelly
As Life Science organizations continue to struggle with the proliferation of structured and unstructured information flowing into their organization, forward looking companies are managing enterprise information using cutting-edge technologies. To enhance information discovery, information scientists are integrating disparate information into a single, unified knowledge platform and applying semantic technologies to harmonize and link information using vocabularies and publicly available medical taxonomies.
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