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FIS Alpine Skiing seasons

Introduction

=== Load Sample Data
//setup
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[source,cypher]
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create
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swainjo / GreenMan
Last active August 29, 2015 14:05 — forked from pac19/Alpine Skiing.adoc
== Green Man POC
:neo4j-version: neo4j-2.1
:author: John Swain
:twitter: @swainjo
:tags: domain:POC
=== Load Sample Data
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Movie Recommendations with k-Nearest Neighbors and Cosine Similarity


Introduction

The k-nearest neighbors (k-NN) algorithm is among the simplest algorithms in the data mining field. Distances / similarities are calculated between each element in the data set using some distance / similarity metric ^[1]^ that the researcher chooses (there are many distance / similarity metrics), where the distance / similarity between any two elements is calculated based on the two elements' attributes. A data element’s k-NN are the k closest data elements according to this distance / similarity.


1. A distance metric measures distance; the higher the distance the further apart the neighbors. A similarity metric measures similarity; the higher the similarity the closer the neighbors.

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logo elite dangerous

In the video game Elite:Dangerous players can buy and sell commodities at stations around the galaxy. This gist shows how to use Neo4j and Cypher queries for trading decisions in this game.

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swainjo / index.html
Created May 30, 2014 15:12
Crimes EDA
<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8">
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta http-equiv="Content-Style-Type" content="text/css" />
<meta name="generator" content="pandoc" />
<!DOCTYPE html>
<meta charset="utf-8">
<style>
body {
font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
width: 960px;
height: 500px;
position: relative;
}