captainjackrana

{
  "basics": {
    "name": "Thomas Edison Silva",
    "label": "Inventor and Businessman",
    "picture": "https://example.com/photo.jpg",
    "email": "[email protected]",
    "phone": "(123) 456-7890",
    "website": "https://thomasedison.com",
    "summary": "Prolific inventor and businessman known for developing many devices that greatly influenced life around the world, including the phonograph, the motion picture camera, and the electric light bulb.",
    "location": {

captainjackrana

{
  "basics": {
    "name": "Thomas Edison",
    "label": "Inventor and Businessman",
    "picture": "https://example.com/photo.jpg",
    "email": "[email protected]",
    "phone": "(123) 456-7890",
    "website": "https://thomasedison.com",
    "summary": "Prolific inventor and businessman known for developing many devices that greatly influenced life around the world, including the phonograph, the motion picture camera, and the electric light bulb.",
    "location": {

captainjackrana

from matminer.datasets import load_dataset
from pymatgen.core import Composition
from matminer.featurizers.structure import DensityFeatures
from matminer.featurizers.conversions import StrToComposition
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_absolute_error
from sklearn.dummy import DummyRegressor
import pprint

from automatminer import MatPipe

captainjackrana

/* we have to go through all nodes */
MATCH (node:Page)
WITH
COLLECT(distinct node) AS pages
UNWIND pages as dest
  /* let's find all source citations for a given node */
  MATCH (source:Page)-[:NEXT]->(dest)
  WITH
    COLLECT(DISTINCT source) AS sources,
    dest AS dest