cheerfulstoic

# encoding: UTF-8

require 'rubygems'
require 'nokogiri'
require 'open-uri'
require 'graphviz'

target = 'Philosophy'
links = {}

cheerfulstoic

require 'rubygems'
require 'rake'
require 'fileutils'
require "bundler"
require 'rspec/core/rake_task'

RSpec::Core::RakeTask.new(:spec)


desc "Task for cruise Control"

cheerfulstoic

batch_size = 10_000
previous_nodes_per_second = nil 

while true
  total_found = 0
  puts "Testing batch size of #{batch_size}..."
  time_taken = Benchmark.realtime do
    i = 0
    House.as(:h).find_in_batches(batch_size: batch_size) do |batch|

cheerfulstoic

= Bank Fraud Detection
:neo4j-version: 2.0.0-RC1
:author: Kenny Bastani
:twitter: @kennybastani
:tags: domain:finance, use-case:fraud-detection

= Bank Fraud Detection

(original source: https://github.com/neo4j-contrib/gists/blob/master/other/BankFraudDetection.adoc )

cheerfulstoic

MATCH (n)
OPTIONAL MATCH (n)-[r]-()
DELETE n,r;

CREATE (:Product {id: 1, name: 'Apple iPhone 6 128GB iOS 8 4.7" Touchscreen Factory Unlocked', price: 839.99});
CREATE (:Product {id: 2, name: 'HTC One M8 32GB Factory Unlocked Windows 8.1 Smartphone', price: 349.99});
CREATE (:Product {id: 3, name: 'DELL 15.6" Intel Core i7 1TB HDD Notebook', price: 649.99});
CREATE (:Product {id: 4, name: 'Canon EOS Rebel T5 EF-S 18-55mm IS II Digital SLR Kit US Warranty', price: 399.99});
CREATE (:Product {id: 5, name: 'Terralux TLF-TT-5 Tactical 5 Light 650 Lumens', price: 77.88});
CREATE (:Product {id: 6, name: 'Emergency One Person 3-month Food Storage Kit', price: 479.99});

cheerfulstoic

require 'json'

queries = []
queries << <<QUERY
{
  "statements" : [
  {
    "statement" : "CREATE (n:TransactionTestFoo) RETURN id(n)"
  },
  {

cheerfulstoic

# Show user friend relationships
    MATCH (user:User) RETURN user

# Show products in category hierarchy
    MATCH (product:Product)-[:has_category]->(category:Category)<-[:has_subcategory*]-(super_category:Category)
    RETURN *

# All users 25 and under
    MATCH (user:User) WHERE user.age <= 25 RETURN user.name, user.age;

cheerfulstoic

= Competitive Intelligence in Cancer Drug Discovery =
:neo4j-version: 2.0.0-RC1
:author: Wolfgang Hoeck
:twitter: @LiveDataConcept
:tags: life science domain:competitive intelligence in cancer drug discovery

Using the _Design for Queryability_ modeling approach by http://twitter.com/ianrobinson[Ian Robinson]

=== 1. Application/End-User Goals ===

cheerfulstoic

Analyzing StackOverflow with Neo4j and Clojure

Joining multiple disparate data-sources, commonly dubbed Master-Data-Management (MDM), is usually not a fun exercise. I would like to show you how using a graph database (Neo4j) and an interesting dataset (developer-oriented collaboration sites) to put the fun back into MDM. This approach will allow you to quickly and sensibly merge data from different sources into a consistent picture and query across the data efficiently to answer your most pressing questions.

You can read the associated blog posts on my blog. The blog posts cover the hows and whys of the project, while this and other GraphGists will examine how to answer specific questions of the data.

cheerfulstoic

class GithubClientCache
  CACHE = ActiveSupport::Cache::FileStore.new('cache')
  CACHE_EXPIRY_PERIOD = (60 * 60 * 24 * 365) # 1 year

  def initialize(current_object, arg_stack = [])
    @current_object = current_object
    @arg_stack = arg_stack
  end

  def method_missing(method, *args, &block)