Practical Web Analytics for User Experience teaches you how to use web analytics to help answer the complicated questions facing UX professionals. Within this book, you'll find a quantitative approach for measuring a website's effectiveness and the methods for posing and answering specific questions about how users navigate a website. The book is organized according to the concerns UX practitioners face. Chapters are devoted to traffic, clickpath, and content use analysis, measuring the effectiveness of design changes, including A/B testing, building user profiles based on search habits, supporting usability test findings with reporting, and more. This is the must-have resource you need to start capitalizing on web analytics and analyze websites effectively. Discover concrete information on how web analytics data support user research and user-centered design Learn how to frame questions in a way that lets you navigate through massive amounts of data to get the answer you need Learn how to gather information for personas, verify behavior found in usability testing, support heuristic evaluation with data, analyze keyword data, and understand how to communicate these findings with business stakeholders
Search is everywhere, yet it is one of the most misunderstood functionalities of the IT industry. In Apache Solr, author Xavier Morera guides you through the basics of this highly popular enterprise search tool. You'll learn how to set up an index and how to make it searchable, then query it with a simple enterprise search. Explanations for precision and recall are also included to help you ensure that relevant, accurate results have been returned. Custom UIs using Solritas and SolrNet are also covered. This updated and expanded second edition of Book provides a user-friendly introduction to the subject, Taking a clear structural framework, it guides the reader through the subject's core elements. A flowing writing style combines with the use of illustrations and diagrams throughout the text to ensure the reader understands even the most complex of concepts. This succinct and enlightening overview is a required reading for all those interested in the subject . We hope you find this book useful in shaping your future career & Business.
Developing a successful game in today’s market is a challenging endeavor. Thousands of titles are published yearly, all competing for players’ time and attention. Game analytics has emerged in the past few years as one of the main resources for ensuring game quality, maximizing success, understanding player behavior and enhancing the quality of the player experience. It has led to a paradigm shift in the development and design strategies of digital games, bringing data-driven intelligence practices into the fray for informing decision making at operational, tactical and strategic levels. Game Analytics - Maximizing the Value of Player Data is the first book on the topic of game analytics; the process of discovering and communicating patterns in data towards evaluating and driving action, improving performance and solving problems in game development and game research. Written by over 50 international experts from industry and research, it covers a comprehensive range of topics across more than 30 chapters, providing an in-depth discussion of game analytics and its practical applications. Topics covered include monetization strategies, design of telemetry systems, analytics for iterative production, game data mining and big data in game development, spatial analytics, visualization and reporting of analysis, player behavior analysis, quantitative user testing and game user research. This state-of-the-art volume is an essential source of reference for game developers and researchers. Key takeaways include: Thorough introduction to game analytics; covering analytics applied to data on players, processes and performance throughout the game lifecycle. In-depth coverage and advice on setting up analytics systems and developing good practices for integrating analytics in game-development and -management. Contributions by leading researchers and experienced professionals from the industry, including Ubisoft, Sony, EA, Bioware, Square Enix, THQ, Volition, and PlayableGames. Interviews with experienced industry professionals on how they use analytics to create hit games.
Presents information on machine learning through the use of Apache Mahout, covering such topics as using group data to make individual recommendations, finding logical clusters, and filtering classifications.
The information trapped in text files, PDFs, and other digital content is a valuable information asset that can be very difficult to discover and use. Apache Tika is an open source toolkit that makes it easy for search engines, content management systems and other applications to detect and extract content from digital documents in all major file formats. Tika in Actionis a hands-on guide for developers working with search engines, content management systems and other similar applications who want to exploit the information locked in digital documents. It introduces the world of mining text and binary documents as well as other information sources. The book shows where Tika fits within this landscape and how readers can use Tika to build and extend applications. The book's many case studies give real-world experience from domains ranging from search engines to digital asset management and scientific data processing.
This book teaches you how to master the subtle art of multilingual text processing and prevent text data corruption. It provides an introduction to natural language processing using Lucene and Solr. It gives you tools and techniques to manage large collections of text data, whether they come from news feeds, databases, or legacy documents. Each chapter contains executable programs that can also be used for text data forensics. Topics covered: Unicode code points Character encodings from ASCII and Big5 to UTF-8 and UTF-32LE Character normalization using International Components for Unicode (ICU) Java I/O, including working directly with zip, gzip, and tar files Regular expressions in Java Transporting text data via HTTP Parsing and generating XML, HTML, and JSON Using Lucene 4 for natural language search and text classification Search, spelling correction, and clustering with Solr 4 Other books on text processing presuppose much of the material covered in this book. They gloss over the details of transforming text from one format to another and assume perfect input data. The messy reality of raw text will have you reaching for this book again and again.
There’s no easier, faster, or more practical way to learn the really tough subjects UML Demystified explains how to read, model, and use UML to create well-structured, stable software products. This self-teaching guide comes complete with key points, background information, quizzes at the end of each chapter, and even a final exam. Simple enough for beginners but challenging enough for advanced students, this is a lively and entertaining brush-up, introductory text, or classroom supplement.
Author: Michael McCandless,Erik Hatcher,Otis Gospodnetić
Publisher: Manning Publications
Lucene remains an indispensable part of most enterprise applications. This search engine now powers Web options in diverse companies, including Netflix, LinkedIn, and the Mayo Clinic. This updated edition is the definitive guide to developing with Lucene.
Techniques for building machine learning and neural network models for NLP, 2nd Edition
Author: Richard M. Reese,AshishSingh Bhatia
Publisher: Packt Publishing Ltd
Explore various approaches to organize and extract useful text from unstructured data using Java Key Features Use deep learning and NLP techniques in Java to discover hidden insights in text Work with popular Java libraries such as CoreNLP, OpenNLP, and Mallet Explore machine translation, identifying parts of speech, and topic modeling Book Description Natural Language Processing (NLP) allows you to take any sentence and identify patterns, special names, company names, and more. The second edition of Natural Language Processing with Java teaches you how to perform language analysis with the help of Java libraries, while constantly gaining insights from the outcomes. You’ll start by understanding how NLP and its various concepts work. Having got to grips with the basics, you’ll explore important tools and libraries in Java for NLP, such as CoreNLP, OpenNLP, Neuroph, and Mallet. You’ll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts-of-speech and parsing trees. You’ll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and more. By the end of this book, you’ll have learned more about NLP, neural networks, and various other trained models in Java for enhancing the performance of NLP applications. What you will learn Understand basic NLP tasks and how they relate to one another Discover and use the available tokenization engines Apply search techniques to find people, as well as things, within a document Construct solutions to identify parts of speech within sentences Use parsers to extract relationships between elements of a document Identify topics in a set of documents Explore topic modeling from a document Who this book is for Natural Language Processing with Java is for you if you are a data analyst, data scientist, or machine learning engineer who wants to extract information from a language using Java. Knowledge of Java programming is needed, while a basic understanding of statistics will be useful but not mandatory.
Users expect search to be simple: They enter a few terms and expect perfectly-organized, relevant results instantly. But behind this simple user experience, complex machinery is at work. Whether using Elasticsearch, Solr, or another search technology, the solution is never one size fits all. Returning the right search results requires conveying domain knowledge and business rules in the search engine's data structures, text analytics, and results ranking capabilities. Relevant Search demystifies relevance work. Using Elasticsearch, it tells how to return engaging search results to users, helping readers understand and leverage the internals of Lucene-based search engines. The book walks through several real-world problems using a cohesive philosophy that combines text analysis, query building, and score shaping to express business ranking rules to the search engine. It outlines how to guide the engineering process by monitoring search user behavior and shifting the enterprise to a search-first culture focused on humans, not computers. It also shows how the search engine provides a deeply pluggable platform for integrating search ranking with machine learning, ontologies, personalization, domain-specific expertise, and other enriching sources. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Apache Nutch helps you to create your own search engine and customize it according to your needs. You can integrate Apache Nutch very easily with your existing application and get the maximum benefit from it. It can be easily integrated with different components like Apache Hadoop, Eclipse, and MySQL. 'Web Crawling and Data Mining with Apache Nutch' shows you all the necessary steps to help you in crawling webpages for your application and using them to make your application searching more efficient. You will create your own search engine and will be able to improve your application page rank in searching.
Is your organization rapidly accumulating more information than you know how to manage? This updated edition of Enterprise Search helps you create an enterprise search solution based on more than just technology. Author Martin White shows you how to plan and implement a managed search environment that meets the needs of your business and your employees. You'll learn why it’s absolutely vital to have a dedicated staff manage your search technology and support your users. New material for this second edition includes material on SharePoint 2013 search, managing open source search development, website search, designing the search user, and assessing search performance. Chapters now include a Further Reading section for computer science and information science students. Topics include: 10 critical success factors to assess organizational search maturity Essential skills needed to support a successful search application How to specify and manage open source search development How to manage SharePoint 2013 search Methods to assess the business impact of search Best practices in user interface design The importance of search for websites What to include in a search strategy
This book is a step-by-step guide for readers who would like to learn how to build complete enterprise search solutions, with ample real-world examples and case studies. If you are a developer, designer, or architect who would like to build enterprise search solutions for your customers or organization, but have no prior knowledge of Apache Solr/Lucene technologies, this is the book for you.
One of the few plays that survived intact from the heyday of ancient Grecian drama, Lysistrata is an enormously influential work of satirical comedy. In order to bring an end to a destructive and never-ending war, the women of Greece take a temporary vow of chastity, pledging to remain abstinent until the conflict ends. As can be expected, mayhem -- and hilarity -- ensues.
A Practical Introduction to Information Retrieval and Text Mining
Author: ChengXiang Zhai,Sean Massung
Publisher: Morgan & Claypool
Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic. This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.
A Hands-on Guide to Begin Developing Applications Using Spring Framework
Author: Ashish Sarin,J Sharma
Getting started with Spring Framework is a hands-on guide to begin developing applications using Spring Framework. This book is meant for Java developers with little or no knowledge of Spring Framework. All the examples shown in this book use Spring 3.2. Chapter 1 - Spring Framework basics Chapter 2 - Configuring beans Chapter 3 - Dependency injection Chapter 4 - Customizing beans and bean definitions Chapter 5 - Annotation-driven development with Spring Chapter 6 - Database interaction using Spring Chapter 7 - Messaging, emailing, asynchronous method execution, and caching using Spring Chapter 8 - Aspect-oriented programming
This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.