It sounds like fictional television or the latest science fiction thriller. However, with software-defined networking (SDN), networks are taking advantage of the benefits of cloud-based virtualization and through many steps that are so much more complicated than I am making them sound, they are on the cusp of enabling networks to remain self-aware, self-defending, and self-healing - all the time.
With the Data Harmony User's Group in full swing, today started the case studies. Personally, I find these the most interesting because it is a real life application of all the technology, including the hurdles and bumps along the way.
Semantic Web Company recently announced the launch of PoolParty Semantic Suite Version 5. This taxonomy management and knowledge graph management software platform includes support for ontology management, custom schema management, enhanced entity extraction, linked data harvesting, Web crawling, and auto-classification in enterprise systems such as SharePoint, Confluence, Drupal and more.
Artificial intelligence has come a long way from the character Data on Star Trek and even farther from 2001: A Space Odyssey. It is now part of our daily habits, i.e. Apple's Siri.
TEAM Asparona announced recently that it has entered into a strategic partnership with Syl Semantics. This new partnership will enable TEAM Asparona to provide Syl Search to their customers. This includes government agencies and commercial organizations with a requirement for advanced search capabilities.
There are many pieces that need to fit together to implement a semantic strategy. Just as the instruments in an orchestra combine to provide a beautiful sound, a semantic strategy can provide a wonderful platform for your user community to enjoy. To really make it work, however, you need to understand each instrument and how to organize them for the best effect. Register today and plan to attend the webinar - Orchestrating an Effective Semantic Strategy Webinar on December 16 from 11:00 a.m. to 12:00 p.m. (Mountain Time).
Many automated knowledge extraction and processing applications rely on computing semantic relatedness between textual labels representing biological and medical concepts. Because of the large amount of new findings, most methods benefit from making use of highly specific resources.