content detection from keywords
There are 198.000 unique keywords in GEOSS infrastructure metadata. I could not resist to connect them based on collocation in individual records. And here is the outcome with community detection:
social network analysis
document vectors for clustering of large document sets
Recently I have finished the work on understanding what exactly is the content of the GEOSS global data infrastructure. Many partial approaches were shown in previous posts and this one concludes the outcome. For all the 1.8M metadata records from GEOSS we calculated document vectors and tried to run cluster detection with cosine similarity as … Read moredocument vectors for clustering of large document sets
GEOSS 2: Bird’s eye perspective of the whole GEOSS content
When you have millions of datasets from ten thousands data providers, you may wonder a bit what is the overall picture after all. Below you can find two pictures describing the whole architecture using just keywords and keyword co-location. The first picture shows how the keywords cluster and what difficulties we have to discover any … Read moreGEOSS 2: Bird’s eye perspective of the whole GEOSS content
GEOSS post 1: Semantic spaces of textual metadata content
Sometimes we can discover more information in metadata abstracts than in all other fields, especially when we have so many records as GEOSS can provide. This global data sharing architecture boasting having 300 million metadata records on datasets and services is pretty much operational and delivering data on daily basis. Yet, nobody knows really what … Read moreGEOSS post 1: Semantic spaces of textual metadata content
Word context discovery in plain corpus
What can we discover if we teach word embedding over the whole corpus of European legislation and supportive documents? This is what happens when you run similarity queries five fold and domains you get: