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Getting Structured Data from the Internet

Getting Structured Data from the Internet
Author: Jay M. Patel
Publisher: Apress
Total Pages: 325
Release: 2020-12-13
Genre: Computers
ISBN: 9781484265758
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Utilize web scraping at scale to quickly get unlimited amounts of free data available on the web into a structured format. This book teaches you to use Python scripts to crawl through websites at scale and scrape data from HTML and JavaScript-enabled pages and convert it into structured data formats such as CSV, Excel, JSON, or load it into a SQL database of your choice. This book goes beyond the basics of web scraping and covers advanced topics such as natural language processing (NLP) and text analytics to extract names of people, places, email addresses, contact details, etc., from a page at production scale using distributed big data techniques on an Amazon Web Services (AWS)-based cloud infrastructure. It book covers developing a robust data processing and ingestion pipeline on the Common Crawl corpus, containing petabytes of data publicly available and a web crawl data set available on AWS's registry of open data. Getting Structured Data from the Internet also includes a step-by-step tutorial on deploying your own crawlers using a production web scraping framework (such as Scrapy) and dealing with real-world issues (such as breaking Captcha, proxy IP rotation, and more). Code used in the book is provided to help you understand the concepts in practice and write your own web crawler to power your business ideas. What You Will Learn Understand web scraping, its applications/uses, and how to avoid web scraping by hitting publicly available rest API endpoints to directly get data Develop a web scraper and crawler from scratch using lxml and BeautifulSoup library, and learn about scraping from JavaScript-enabled pages using Selenium Use AWS-based cloud computing with EC2, S3, Athena, SQS, and SNS to analyze, extract, and store useful insights from crawled pages Use SQL language on PostgreSQL running on Amazon Relational Database Service (RDS) and SQLite using SQLalchemy Review sci-kit learn, Gensim, and spaCy to perform NLP tasks on scraped web pages such as name entity recognition, topic clustering (Kmeans, Agglomerative Clustering), topic modeling (LDA, NMF, LSI), topic classification (naive Bayes, Gradient Boosting Classifier) and text similarity (cosine distance-based nearest neighbors) Handle web archival file formats and explore Common Crawl open data on AWS Illustrate practical applications for web crawl data by building a similar website tool and a technology profiler similar to builtwith.com Write scripts to create a backlinks database on a web scale similar to Ahrefs.com, Moz.com, Majestic.com, etc., for search engine optimization (SEO), competitor research, and determining website domain authority and ranking Use web crawl data to build a news sentiment analysis system or alternative financial analysis covering stock market trading signals Write a production-ready crawler in Python using Scrapy framework and deal with practical workarounds for Captchas, IP rotation, and more Who This Book Is For Primary audience: data analysts and scientists with little to no exposure to real-world data processing challenges, secondary: experienced software developers doing web-heavy data processing who need a primer, tertiary: business owners and startup founders who need to know more about implementation to better direct their technical team

Data on the Web

Data on the Web
Author: Serge Abiteboul
Publisher: Morgan Kaufmann
Total Pages: 280
Release: 2000
Genre: Computers
ISBN: 9781558606227
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Data model. Queries. Types. Sysems. A syntax for data. XML.. Query languages. Query languages for XML. Interpretation and advanced features. Typing semistructured data. Query processing. The lore system. Strudel. Database products supporting XML. Bibliography. Index. About the authors.

Mastering Structured Data on the Semantic Web

Mastering Structured Data on the Semantic Web
Author: Leslie Sikos
Publisher: Apress
Total Pages: 244
Release: 2015-07-11
Genre: Computers
ISBN: 1484210492
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A major limitation of conventional web sites is their unorganized and isolated contents, which is created mainly for human consumption. This limitation can be addressed by organizing and publishing data, using powerful formats that add structure and meaning to the content of web pages and link related data to one another. Computers can "understand" such data better, which can be useful for task automation. The web sites that provide semantics (meaning) to software agents form the Semantic Web, the Artificial Intelligence extension of the World Wide Web. In contrast to the conventional Web (the "Web of Documents"), the Semantic Web includes the "Web of Data", which connects "things" (representing real-world humans and objects) rather than documents meaningless to computers. Mastering Structured Data on the Semantic Web explains the practical aspects and the theory behind the Semantic Web and how structured data, such as HTML5 Microdata and JSON-LD, can be used to improve your site’s performance on next-generation Search Engine Result Pages and be displayed on Google Knowledge Panels. You will learn how to represent arbitrary fields of human knowledge in a machine-interpretable form using the Resource Description Framework (RDF), the cornerstone of the Semantic Web. You will see how to store and manipulate RDF data in purpose-built graph databases such as triplestores and quadstores, that are exploited in Internet marketing, social media, and data mining, in the form of Big Data applications such as the Google Knowledge Graph, Wikidata, or Facebook’s Social Graph. With the constantly increasing user expectations in web services and applications, Semantic Web standards gain more popularity. This book will familiarize you with the leading controlled vocabularies and ontologies and explain how to represent your own concepts. After learning the principles of Linked Data, the five-star deployment scheme, and the Open Data concept, you will be able to create and interlink five-star Linked Open Data, and merge your RDF graphs to the LOD Cloud. The book also covers the most important tools for generating, storing, extracting, and visualizing RDF data, including, but not limited to, Protégé, TopBraid Composer, Sindice, Apache Marmotta, Callimachus, and Tabulator. You will learn to implement Apache Jena and Sesame in popular IDEs such as Eclipse and NetBeans, and use these APIs for rapid Semantic Web application development. Mastering Structured Data on the Semantic Web demonstrates how to represent and connect structured data to reach a wider audience, encourage data reuse, and provide content that can be automatically processed with full certainty. As a result, your web contents will be integral parts of the next revolution of the Web.

Linked Data

Linked Data
Author: Luke Ruth
Publisher: Simon and Schuster
Total Pages: 402
Release: 2013-12-30
Genre: Computers
ISBN: 163835216X
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Summary Linked Data presents the Linked Data model in plain, jargon-free language to Web developers. Avoiding the overly academic terminology of the Semantic Web, this new book presents practical techniques, using everyday tools like JavaScript and Python. About this Book The current Web is mostly a collection of linked documents useful for human consumption. The evolving Web includes data collections that may be identified and linked so that they can be consumed by automated processes. The W3C approach to this is Linked Data and it is already used by Google, Facebook, IBM, Oracle, and government agencies worldwide. Linked Data presents practical techniques for using Linked Data on the Web via familiar tools like JavaScript and Python. You'll work step-by-step through examples of increasing complexity as you explore foundational concepts such as HTTP URIs, the Resource Description Framework (RDF), and the SPARQL query language. Then you'll use various Linked Data document formats to create powerful Web applications and mashups. Written to be immediately useful to Web developers, this book requires no previous exposure to Linked Data or Semantic Web technologies. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. What's Inside Finding and consuming Linked Data Using Linked Data in your applications Building Linked Data applications using standard Web techniques About the Authors David Wood is co-chair of the W3C's RDF Working Group. Marsha Zaidman served as CS chair at University of Mary Washington. Luke Ruth is a Linked Data developer on the Callimachus Project. Michael Hausenblas led the Linked Data Research Centre. Table of Contents PART 1 THE LINKED DATA WEB Introducing Linked Data RDF: the data model for Linked Consuming Linked Data PART 2 TAMING LINKED DATA Creating Linked Data with SPARQL—querying the Linked PART 3 LINKED DATA IN THE WILD Enhancing results from search RDF database fundamentals Datasets PART 4 PULLING IT ALL TOGETHER Callimachus: a Linked Data Publishing Linked Data—a recap The evolving Web

Query Processing over Graph-structured Data on the Web

Query Processing over Graph-structured Data on the Web
Author: M. Acosta Deibe
Publisher: IOS Press
Total Pages: 244
Release: 2018-10-12
Genre: Computers
ISBN: 1614999163
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In the last years, Linked Data initiatives have encouraged the publication of large graph-structured datasets using the Resource Description Framework (RDF). Due to the constant growth of RDF data on the web, more flexible data management infrastructures must be able to efficiently and effectively exploit the vast amount of knowledge accessible on the web. This book presents flexible query processing strategies over RDF graphs on the web using the SPARQL query language. In this work, we show how query engines can change plans on-the-fly with adaptive techniques to cope with unpredictable conditions and to reduce execution time. Furthermore, this work investigates the application of crowdsourcing in query processing, where engines are able to contact humans to enhance the quality of query answers. The theoretical and empirical results presented in this book indicate that flexible techniques allow for querying RDF data sources efficiently and effectively.

Metadata Basics for Web Content

Metadata Basics for Web Content
Author: Michael C. Andrews
Publisher:
Total Pages: 405
Release: 2017-02-16
Genre:
ISBN: 9781520553467
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Metadata (also known as structured data) plays a growing role in how customers and other online audiences get information. Well-defined metadata ensures that digital content is ease-to-locate, is up-to-date, can be targeted to specific needs, and can be re-used for multiple purposes by both the publishers and consumers of the content. Metadata plays a key role in SEO, content licensing, content marketing, social media visibility, analytics, and mobile app design. Metadata is most powerful when it is designed and developed in an integrated manner, where all these roles support each other. Metadata Basics for Web Content is the first comprehensive survey discussing the various kinds of metadata available to support the creation, management, delivery, and assessment of web content. The book is designed to help publishers of web content understand the many benefits of metadata, and identify what they need to do to realize these benefits.Metadata may sound like a specialized technical topic, but it affects everyone who is involved with publishing content online. Effective metadata requires the collaboration of various members of a web team. The book provides insights about metadata will be useful for web team members with different responsibilities, whether they are authors, content strategists, SEOs, web analytics professionals, user experience designers, front-end developers, or marketing experts. The book provides a foundation for publishers to develop integrated requirements relating to web metadata, so that their content can be successful in supporting a diverse range of business goals.Book features: Extensive diagrams explaining key conceptsGlossary of over 75 important termsOver 200 footnotes providing additional details and links to tutorialsSimple code examples illustrating concepts discussed. Links to resources such as important industry standards and software toolsAbout the AuthorMichael C Andrews is an American IT consultant currently based in Hyderabad, India. He started working with online metadata as a technical information specialist at the US Commerce Department in the 1980s, and was among the first wave of people whose full-time job responsibilities focused on using the Internet to access and manage published content. For the past 15 years he has worked as a consultant in the fields of user experience and content strategy. He's worked as a senior manager for content strategy with one of the world's largest digital consultancies, and has advised clients such the National Institutes of Health, Verizon and the World Bank. He has lived and worked in the US, UK, New Zealand, Italy, as well as India.Andrews has an MSc in human computer interaction from the University of Sussex in England, and a Masters with a specialization in international finance from Columbia University in New York. He also has a certificate in XML and RDF Technologies from the Library Juice Academy.

Mastering Structured Data on the Semantic Web

Mastering Structured Data on the Semantic Web
Author: Leslie Sikos
Publisher:
Total Pages:
Release: 2015
Genre:
ISBN: 9781484210512
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A major limitation of conventional web sites is their unorganized and isolated contents, which is created mainly for human consumption. This limitation can be addressed by organizing and publishing data, using powerful formats that add structure and meaning to the content of web pages and link related data to one another. Computers can "understand" such data better, which can be useful for task automation. The web sites that provide semantics (meaning) to software agents form the Semantic Web, the Artificial Intelligence extension of the World Wide Web. In contrast to the conventional Web (the "Web of Documents"), the Semantic Web includes the "Web of Data", which connects "things" (representing real-world humans and objects) rather than documents meaningless to computers. Mastering Structured Data on the Semantic Web explains the practical aspects and the theory behind the Semantic Web and how structured data, such as HTML5 Microdata and JSON-LD, can be used to improve your site's performance on next-generation Search Engine Result Pages and be displayed on Google Knowledge Panels. You will learn how to represent arbitrary fields of human knowledge in a machine-interpretable form using the Resource Description Framework (RDF), the cornerstone of the Semantic Web. You will see how to store and manipulate RDF data in purpose-built graph databases such as triplestores and quadstores, that are exploited in Internet marketing, social media, and data mining, in the form of Big Data applications such as the Google Knowledge Graph, Wikidata, or Facebook's Social Graph. With the constantly increasing user expectations in web services and applications, Semantic Web standards gain more popularity. This book will familiarize you with the leading controlled vocabularies and ontologies and explain how to represent your own concepts. After learning the principles of Linked Data, the five-star deployment scheme, and the Open Data concept, you will be able to create and interlink five-star Linked Open Data, and merge your RDF graphs to the LOD Cloud. The book also covers the most important tools for generating, storing, extracting, and visualizing RDF data, including, but not limited to, Protégé, TopBraid Composer, Sindice, Apache Marmotta, Callimachus, and Tabulator. You will learn to implement Apache Jena and Sesame in popular IDEs such as Eclipse and NetBeans, and use these APIs for rapid Semantic Web application development. Mastering Structured Data on the Semantic Web demonstrates how to represent and connect structured data to reach a wider audience, encourage data reuse, and provide content that can be automatically processed with full certainty. As a result, your web contents will be integral parts of the next revolution of the Web.

Unstructured Data Analysis

Unstructured Data Analysis
Author: Matthew Windham
Publisher: SAS Institute
Total Pages: 166
Release: 2018-09-14
Genre: Computers
ISBN: 1635267099
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Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data. This book covers the five critical elements of entity extraction, unstructured data, entity resolution, entity network mapping and analysis, and entity management. By following examples of how to apply processing to unstructured data, readers will derive tremendous long-term value from this book as they enhance the value they realize from SAS products.