While Web 2.0 was about data, Web 3.0 is about knowledge and
information. Scripting Intelligence: Web 3.0 Information Gathering
and Processing offers the reader Ruby scripts for intelligent
information management in a Web 3.0 environmentincluding
information extraction from text, using Semantic Web technologies,
information gathering (relational database metadata, web scraping,
Wikipedia, Freebase), combining information from multiple sources,
and strategies for publishing processed information. This book will
be a valuable tool for anyone needing to gather, process, and
publish web or database information across the modern web
environment.Text processing recipes, including speech tagging and
automatic summarization Gathering, visualizing, and publishing
information from the Semantic Web Information gathering from
traditional sources such as relational databases and web sites What
you'll learn Gather and process information within the Web 3.0
environment. See the flexibility of scripting with Ruby to gather
and process information. Extract text from various document
formats. Work with the Resource Description Framework(RDF) data
model and SPARQL query language, the foundations of the Semantic
Web. Use GraphViz for data visualization. Extract information from
relational databases and web sites. Who this book is for
Anyone needing to gather and display information available in
electronic formats Programmers needing to tag, summarize, or
publish information Ruby programmers and computer enthusiasts
interested in seeing what Ruby can do with information management
and Semantic Web tools Academic researchers needing to extract and
organize information in a more automated way Table of Contents
Parsing Common Document Types Cleaning, Segmenting, and
Spell-Checking Text Natural Language Processing Using RDF and RDFS
Data Formats Delving Into RDF Data Stores Performing SPARQL Queries
and Understanding Reasoning Implementing SPARQL Endpoint Web
Portals Working with Relational Databases Supporting Indexing and
Search Using Web Scraping to Create Semantic Relations Taking
Advantage of Linked Data Implementing Strategies for Large-Scale
Data Storage Creating Web Mashups Performing Large-Scale Data
Processing Building Information Web Portals
General
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