Textual data is a core source of information in the enterprise. Example demands arise from sales departments (monitor and identify leads), human resources (identify professionals with capabilities in ‘xyz’), market research (campaign monitoring from the social web), product development (incorporate feedback from customers), and the medical domain (anamnesis).
In this post, we describe In-Database Relation Extraction (INDREX), a system that transforms text data into relational data with Impala (the open source analytic database for Apache Hadoop), with low overhead needed for extraction, linking, and organization. Read this paper for complete details about our approach and our implementation.
Researchers at MIT have created a language, Picture, based on Julia that makes it much easier to write programs that use probabilistic reasoning for 2D and even 3D based computer vision. Their work is to be presented at the Computer Vision and Pattern Recognition conference in June.
After two years of maintenance and repairs the Large Hadron Collider (LHC) is ready to start up again, this time at 13 TeV - almost double its previous energy. This new energy frontier will allow researchers to probe new boundaries in our understanding of the fundamental structure of the universe.
Here at VMware, we’ve recognize that containers, microservices, and DevOps – among other technologies and methodologies – are changing how modern applications are built, deployed, and managed. We’ve espoused our belief thatVMs and containers are better together, and we continue streamlining application development for DevOps teams on our unified platform. Our sister company, Pivotal, has been working on containers with us for several years, and both VMware and Pivotal continue to support open standards in the community.
Last year we announced QUIC, a UDP-based transport protocol for the modern Internet. Over the last quarter, we’ve been increasing the amount of traffic to Google services that is served over QUIC and analyzing QUIC performance at scale. Results so far are positive, with the data showing that QUIC provides a real performance improvement over TCP thanks to QUIC's lower-latency connection establishment, improved congestion control, and better loss recovery.
The twitteR package, released back in 2010, has long provided the means to access and analyze your Twitter social network data with R. But until recently, there hasn't been anything comparable for the Facebook social network. But now, thanks to Pablo Barbera, there is the RFacebook package which provides a collection of R functions to access data from your Facebook social network. To use RFacebook, you first need to sign up for a Facebook developer account, which is quick and easy as long as you already have a Facebook profile. JulianHi provides an excellent step-by-step tutorial on getting started with...
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