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What is text mining, and how can it be used? What relevance do these methods have to everyday work in information science and the digital humanities? How does one develop competences in text mining? Working with Text provides a series of cross-disciplinary perspectives on text mining and its applications. As text mining raises legal and ethical issues, the legal background of text mining and the responsibilities of the engineer are discussed in this book. Chapters provide an introduction to the use of the popular GATE text mining package with data drawn from social media, the use of text mining to support semantic search, the development of an authority system to support content tagging, and recent techniques in automatic language evaluation. Focused studies describe text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature. Interviews are included that offer a glimpse into the real-life experience of working within commercial and academic text mining. Introduces text analysis and text mining tools Provides a comprehensive overview of costs and benefits Introduces the topic, making it accessible to a general audience in a variety of fields, including examples from biology, chemistry, sociology, and criminology

Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching

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Leverage the power of Scala with different tools to build scalable, robust data science applications About This Book A complete guide for scalable data science solutions, from data ingestion to data visualization Deploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizations Build functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples provided Who This Book Is For If you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions. What You Will Learn Transform and filter tabular data to extract features for machine learning Implement your own algorithms or take advantage of MLLib's extensive suite of models to build distributed machine learning pipelines Read, transform, and write data to both SQL and NoSQL databases in a functional manner Write robust routines to query web APIs Read data from web APIs such as the GitHub or Twitter API Use Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirements Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Deploy scalable parallel applications using Apache Spark, loading data from HDFS or Hive In Detail Scala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and scripting language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines. This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala. Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectu...

Scala (Computer science language) --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching

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Data mining --- User interfaces (Computer systems) --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Social aspects

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Machine learning. --- Computational intelligence. --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Learning, Machine --- Machine theory

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Make the most advanced predictive analytical processes easy using Watson Analytics with this easy-to-follow practical guide About This Book This is the first and the only book on IBM Watson Analytics, and it shows you how to leverage Watson in an enterprise environment through rich use cases Incorporate Watson Analytics into your business strategy and confidently add this cutting edge expertise to your resume This book is written by James D Miller, IBM-certified expert and accomplished Director and Sr. Project Leader Who This Book Is For If you want to perform data discovery and analysis and make sense of data you have, this book for you. Data scientists can also use this book to explore a new way to perform data analysis tasks on cloud with ease. This book does not require a programming background. What You Will Learn Study the language of Watson while you discover how easy it is to access and configure Review what a Watson use case is, why it's important, and how to identify one Design Watson Analytical solutions based upon your use cases Understand the basic concepts behind the content analysis cycle and where Watson fits in Explore all the features of Watson, such as Explore, Predict, and Assemble Customize and extend your Watson solutions Use Watson at the Enterprise level Integrate Watson with other toolsets In Detail Today, only a small portion of businesses actually use a real analytical tool as part of routine decision making. IBM Watson Analytics is changing that making the most advanced and predictive analytical techniques understandable and usable for any industry. This book will be the vital tour guide for your trip, starting with what IBM Watson Analytics is. We'll start off with introduction to Watson Analytics and then quickly move on to various use cases under which one can use the different analytics functionalities offered by Watson. During the course of the book, you will learn how to design solutions, and customize and extend Watson analytics. We will conclude by taking Watson Analytics to enterprise and integrating it with other solutions (other IBM solutions and analytics). Now is the time for you to learn IBM Watson to compete in the world. Style and approach Watson provides individuals with the ability to perform sophisticated data discovery and analysis without all of the complexity that usually goes along with it. This book will get you started with Watson analytics and how you can use it in day-to-day data analysis....

Data mining. --- Watson (Computer) --- IBM computers --- Supercomputers --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data mining --- E-books