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This is a book to help you build intelligent systems using artificial intelligence, linked data, semantic web technologies, use of NoSQL datastores, and general information gathering and processing. I have been working in the field of artificial intelligence (AI) since the early 1980s, mostly using Lisp languages like Common Lisp and Scheme, and more recently using Java, Ruby, Clojure and JavaScript.

This is not a book about AI, even though I do cover topics like neural networks and natural language processing. Intelligent systems provide support for human users to tease information from data, obtain knowledge from information, and perhaps even achieve some form of wisdom.

The major topics that I cover to support building intelligent systems are: text mining, access to data stores (PostgreSQL, MongoDB, StarDog RDF, Neo4J graph database, CouchDB, Solr, DynamoDB, and S3), neural networks, natural language processing (using both the Natural library and the Open Calais web service), semantic web, general information gathering (Freebase, GeoNames, DBPedia, and custom web scraping), and running big data applications using Hadoop.

This is a book for server side development using Node.js. Relatively little material in this book would be useful for client/browser use.

Here is the table of contents:

Preface...............................................1

Notes on Coding Standards................................... 2

Why not Coffescript?...................................... 2

About Me............................................ 2

Introduction............................................4

Github Repository for Book Software ............................. 4

Structure of this Book...................................... 5

Natural Language Processing using Natural and the Open Calais System. . . . . . . . .6

Natural.............................................. 6

OpenCalais........................................... 17

Wrap Up............................................. 18

Neural Networks.........................................19

A simple Javascript Implementation of the Backpropagation Neural Network Model . . . . 19

Using the Simple Neural Model to Analyze the University of Wisconsin Breast Cancer Data ... 28

Additional Resources ...................................... 31

DataStorage............................................33

The Postgres Relational Database ............................... 33

MongoDB NoSQL DataStore.................................. 38

CouchDB ............................................ 43

Solr Indexing and Search.................................... 49

Amazon Web Services ..................................... 53

Wrap Up............................................. 59

SemanticWeb...........................................60

RDF and the SPARQL Query Language ............................ 61

Setting Up and Using Stardog ................................. 64

Accessing Wikipedia data through the SPARQL interface for DBPedia . . . . . . . . . . . 67

Wrap Up............................................. 72

Graph Algorithms Using Neo4J.................................74

A Quick Overview of Graph Databases ............................ 75

Loading Datai nto Neo4j .................................... 75

Cypher Query Language using the Neo4j Web Interface . . . . . . . . . . . . . . . . . . . 78

JavaScript Neo4j Client..................................... 82

Wrap Up............................................. 87

Map Reduce Applications with Hadoop.............................88

Map Reduce Applications.................................... 88

Example Data.......................................... 90

A Simple Example........................................ 91

Information Gathering......................................96

Public and Private Data Fusion................................. 96

DBPedia Lookup Service .................................... 97

Freebase............................................. 98

GeoNames . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

Web Spiders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

Wrap Up. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .110

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