k-Nearest Neighbor second-order word embeddings

Implementation of k-nearest neighborhood methods of generating second-order word embeddings, as described in:

D Newman-Griffis and E Fosler-Lussier, "Second-Order Word Embeddings from Nearest Neighbor Topological Features." arXiv, arXiv:1705.08488. 2017.

This library contains two components:

Nearest neighbor calculation

Scripts: nn_saver.py, nearest_neighbors.py
Implemented in Tensorflow
Uses cosine similarity to identify nearest neighbors

Graph generation

Script: generate_graph.py
Generates a weighted, directed edgelist file compatible with node2vec

Dependencies

A few custom libraries are included as frozen copies in the dependencies folder:

drgriffis.common.log -- Logging utilities, from here
pyemblib -- Library for reading/writing word embedding files (Github link)
configlogger -- Library for writing runtime configuration to logfiles (Github link)