TransE, or Translating Embeddings for Modeling Multi-relational Data, lets us embed the contents of a knowledge graph by assigning vectors to nodes and edge types (a.k.a. predicates) and, for each subject-predicate-object triple, minimizing the distance between the object vector and … Read More
Here at CCRi, we’re working on such an interesting set of technologies that we could probably find a conference to speak at every week if we wanted to. Two especially nice conferences that recently included CCRi speakers were the Google … Read More
Release 1.3 of GeoMesa has taken some great steps in making GeoMesa an even better analytics platform for Big Spatial Data. Many improvements fall into two categories: support for a wider range of Spark features and improved support for interactive … Read More
It’s a cliché that a picture is worth a thousand words, but what if you want to create a picture of two thousand nodes connected to each other with several fields of information attached to each node? Trying to … Read More
When starting a new data science project, one should typically first understand the problem domain, state a hypothesis, and then gather data to prove or disprove said hypothesis. But, if I’m being honest, I usually start with a new data … Read More
Earlier this summer, the CCRi blog entry GeoMesa analytics in a Jupyter notebook introduced the use of Jupyter notebooks with Scala and GeoMesa to do Apache Spark analytics and geospatial visualization. As the blog entry said, it only scratched the … Read More