PyTorch-BigGraph: Faster embeddings of large graphs - Facebook Code(About) > A new tool from Facebook AI Research that enables training of multi-relation graph embeddings for very large graphs. PyTorch-BigGraph (PBG) handles graphs with billions of nodes and trillions of edges. Since PBG is written in PyTorch, researchers and engineers can easily swap in their own loss functions, models, and other components.
[Github](https://github.com/facebookresearch/PyTorch-BigGraph), [Blog post](https://ai.facebook.com/blog/open-sourcing-pytorch-biggraph-for-faster-embeddings-of-extremely-large-graphs)
Aho-Corasick (java implementation)(About) Nowadays most free-text searching is based on Lucene-like approaches, where the search text is parsed into its various components. For every keyword a lookup is done to see where it occurs. When looking for a couple of keywords this approach is great. But what about it if you are not looking for just a couple of keywords, but a 100,000 of them? Like, for example, checking against a dictionary?
This is where the Aho-Corasick algorithm shines.
fozziethebeat/S-Space - Java - GitHub(About) a collection of algorithms for building Semantic Spaces. Semantics space algorithms capture the statistical regularities of words in a text corpora and map each word to a high-dimensional vector that represents the semantics.
angular-jsonld(About) This angular module facilitates the integration of JSON-LD server APIs in AngularJS clients. It is implemented on top of Restagular. Its purpose is to provide an adapter layer to map client's data model to the server's API model by using the semantics embedded in JSON-LD as the contract interface. Another important functionality of angular-jsonld is to enable easy navigation of JSON-LD hyperlinks in client's code.
FasterXML/jackson-databind(About) The general-purpose data-binding functionality and tree-model for Jackson Data Processor. It builds on core streaming parser/generator package, and uses Jackson Annotations for configuration.