Big data business analytics liebowitz 3922

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Big data business analytics liebowitz 3922

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of the business-­use case, then it is hard Big Data: Structured and Unstructured  •  267 TABLE 15.1b Technology Platforms and Vendors Platforms Applications Technology Sources NLP Solution Vendors NLU solutions for various industries that use a variety of algorithms and methods in order to achieve performance, scalability and results Applications: • Social Network Mining • Open-­Source Information Analyses • Blog, Website, and News Analyses • Market Intelligence • Sentiment Analysis • Social Opinion Mining • Trends Analyses • Continuous News Monitoring • Website Monitoring • Web Scraping Keyword and key phrase extraction templates using word lists or thesauri Applications: • Web Scraping • Key Term Extraction • Key Phrase Watch List Monitors Attensity: http://www.attensity.com Autonomy: http://www.autonomy.com/ BBN: http://www.bbn com/­technology/­knowledge/­semantic_ web_applications Bitext: http://www.bitext.com/ Brainware: http://www.brainware.com/ Chilliad: http://www.chiliad.com ClearForest: http://www.clearforest com/ Lextek International: http://www lextek.com/ LXA Lexalytics: http://www.lexalytics com/ NetOwl: http://www.netowl.com/ SAS: http://www.sas.com/­text-­ analytics/text-­miner/­index.htm Lingpipe: http://alias-­i.com/­lingpipe/ Topic Mapper: http://www.ai-­one.com/ NLP Template-­ Based Sytems Carrot: http://project.carrot2.org/ Kea: http://www.nzdl.org/­Kea/ Sematext: http://sematext.com/­ products/key-­phrase-­extractor/­index html Maui: http://code.google.com/­p/ maui-­indexer/ Keyphrase Extractor: http://smile.deri ie/­projects/­keyphrase-­extraction to beat a good set of optimized commercial software developer toolkits (SDKs) and/­or open-­source technologies for customized programming of an application or solution (Table 15.1c) Open-­source tools are improving, and IBM’s Watson used many open-­source components While we have provided a broad-­strokes overview, there are many more companies and specialty component technologies on the market Some, like the intelligent agent–­based approaches like Connotate™, already have an early and strong lead with this very promising approach for scalable and distributed natural language processing 268  •  Big Data and Business Analytics TABLE 15.1c Technology Platforms and Vendors Platforms Applications Technology Sources NLP Toolkits These vendors provide all the algorithms in the form of specific language application programming toolkits Applications: • Medical Data Mining • Healthcare Records Analyses • Financial News Analyses • Extraction and Loading of Unstructured Text Into Databases • Customer Help and Support Systems NLP Open-­ Source Tools This is the classic build-­versus-­buy scenario An Internet search resulted in many tool suites, and this is simply a sampling, not representative of the total available Wikipedia list of open-­source NLP tools: http://en.wikipedia org/­wiki/­List of natural_language_ processing_toolkits Cognition: http://www.cognition.com/ Connexor: http://www.connexor.com/ Digital Reasoning: http://www digitalreasoning.com/­solutions/ Expert System: http://www.expertsystem net/ Extractiv: http://extractiv.com/ IBM: http://www.ibm.com/ developerworks/data/­downloads/­uima/ Ling-­Join: http://en.lingjoin.com/­product/­ ljparser.html Lingway: http://www.lingway.com/ Q-­go: http://www.q-­go.nl/ SAP: http://www.sap.com/­solutions/­ sapbusinessobjects/­in dex.epx Teragram: http://www.teragram.com/­oem/ Temis: http://www.temis.com Vantage Linguistics: http://www vantagelinguistics.com/ Xerox: http://www.xrce.xerox com/­Research-­Development/­Document-­ Content-­Laboratory Stanford NLP–­Stanford University (an Extensive tool suite, GPL): http://nlp stanford.edu/­software/­index.shtml Balie—Baseline Information Extraction (University of Ottawa, GNU GPL): http:// balie.sourceforge.net/ FreeLing (Universitat Politecnica de Catalunya, GNU LGPL): http://nlp.lsi.upc edu/­freeling/ Gate—General Architecture For Language Engineering (Java, University of Sheffield, LGPL): http://gate.ac.uk/ MALLET—Machine Learning for Language Toolkit (Java—University of Massachusetts—Common Public License): http://mallet.cs.umass.edu/ NLTK—Natural Language Tool Kit: http:// nltk.org/ Ellogon—Visual NLP (C++, LGPL): http:// www.ellogon.org/ Business & Management “The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions to ‘do this, avoid that.’” —From the Foreword by Joe LaCugna, PhD, Enterprise Analytics and Business Intelligence, Starbucks Coffee Company With the growing barrage of “big data,” it becomes vitally important for organizations to make sense of this data and information in a timely and effective way That’s where analytics come into play Research shows that organizations that use business analytics to guide their decision making are more productive and experience higher returns on equity Big Data and Business Analytics helps you quickly grasp the trends and techniques of big data and business analytics to make your organization more competitive Packed with case studies, this book assembles insights from some of the leading experts and organizations worldwide Spanning industry, government, notfor-profit organizations, and academia, they share valuable perspectives on big data domains such as cybersecurity, marketing, emergency management, healthcare, finance, and transportation • Understand the trends, potential, and challenges associated with big data and business analytics • Get an overview of machine learning, advanced statistical techniques, and other predictive analytics that can help you solve big data issues • Learn from VPs of Big Data/Insights & Analytics via case studies of Fortune 100 companies, government agencies, universities, and not-for-profits Big data problems are complex This book shows you how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage K16118 ISBN: 978-1-4665-6578-4 90000 w w w.c rc p r e s s c o m 781466 565784 www.auerbach-publications.com ... and business analytics • Get an overview of machine learning, advanced statistical techniques, and other predictive analytics that can help you solve big data issues • Learn from VPs of Big Data/ Insights... experience higher returns on equity Big Data and Business Analytics helps you quickly grasp the trends and techniques of big data and business analytics to make your organization more competitive... Enterprise Analytics and Business Intelligence, Starbucks Coffee Company With the growing barrage of big data, ” it becomes vitally important for organizations to make sense of this data and information

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Mục lục

  • Front Cover

  • Contents

  • Foreword

  • Preface

  • About the Editor

  • Contributors

  • Chapter 1 - Architecting the Enterprise via Big Data Analytics

  • Chapter 2 - Jack and the Big Data Beanstalk: Capitalizing on a Growing Marketing Opportunity

  • Chapter 3 - Frontiers of Big Data Business Analytics: Patterns and Cases in Online Marketing

  • Chapter 4 - The Intrinsic Value of Data

  • Chapter 5 - Finding Big Value in Big Data: Unlocking the Power of High-­Performance Analytics

  • Chapter 6 - Competitors, Intelligence, and Big Data

  • Chapter 7 - Saving Lives with Big Data: Unlocking the Hidden Potential in Electronic Health Records

  • Chapter 8 - Innovation Patterns and Big Data

  • Chapter 9 - Big Data at the U.S. Department of Transportation

  • Chapter 10 - Putting Big Data at the Heart of the Decision-­Making Process

  • Chapter 11 - Extracting Useful Information from Multivariate Temporal Data

  • Chapter 12 - Large-­Scale Time-­Series Forecasting

  • Chapter 13 - Using Big Data and Analytics to Unlock Generosity

  • Chapter 14 - The Use of Big Data in Healthcare

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