While Discovery Communications and Scripps Networks got good news from the European Commission today, Apple and Shazam weren't so lucky. In December, Apple confirmed that it purchased Shazam for an undisclosed amount believed to be in the range of $400 million. But today the European Commission said that upon request by a number of European nations, it would be assessing the deal. The proposed acquisition wasn't large enough to require evaluation by the EC directly, but Austrian laws required the companies to seek regulatory clearance there. A European Union provision allows EU countries to ask the EC to look at proposed mergers, and Austria did just that. Iceland, Italy, France, Norway, Spain and Sweden then signed onto that request.
The "C" Team cast begins to arrive. This will be their second show and there is excitement and a little bit of nervousness in the air, no one expected the show to become so popular so quickly. Fan art has already started coming in and every bit of math is being scrutinized, viewers are deeply invested in these characters and these friends who have decided to broadcast their friendships to the world every Thursday from 3:30pm - 6:30pm on Twitch. KATE WELCH: In a world that's full of games with constraints, you have one that ... Well, you can kind of just be or do anything and that's refreshing. It's not something that other media can offer you really.
But then the world changed. Evolutions in technology threw your business into complete upheaval. Almost overnight, your team found itself in a very competitive market. And everyone wants the talent and skills you need -- cybersecurity analysts, data scientists, digital marketers…and who knows what the next new skill will be. You have to disrupt, or be disrupted.
Knowledge acquisition is usually the first step in building ontologies. On the one hand, knowledge is typically implicitly contained in large collections of unstructured documents. Therefore it is extremely troublesome to manually identify relevant concepts. On the other hand, users are often not fully satisfied with the results of automated stateof-the-art ontology learning techniques. In this paper we present a technique for large-scale Knowledge Acquisition supported Semi-automated Ontology building (KASO) and a corresponding software system. By applying KASO and using this software, users are able to bootstrap the process of building high quality ontologies by automatically acquiring concepts from large-scale document collections and to make use of traditional knowledge acquisition approaches to refine and organize the machine-generated concepts. Evaluation studies and user experiences indicate the applicability of KASO in bootstrapping ontology construction.