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Author: J P Shim
Publisher:
ISBN: 9781680836967
Category :
Languages : en
Pages : 72
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Book Description
Speech analytics utilizes speech recognition, predictive analytics, and authentication of the data streams while assessing customers' complaints in real-time. Assessment occurs through the collection and analysis of current data mixed with historical facts to determine patterns and to predict trends. In the current research, the authors have chosen to focus primarily on speech analytics, serving as an umbrella term encompassing speech analytics, audio-mining technologies. The use of speech analytics typically refers to a broader range of speech products, such as analyzing voice identification, emotion detection, and phonetics/speech analysis. Speech Analytics for Actionable Insights proceeds with the discussion of an overview of enterprise needs for speech analytics, a brief history of the speech recognition, the infrastructure of phonetic versus transcription approaches and real-time versus post-call solutions, major speech analytics vendors and their features, applications found within case studies, and recommendations and guidance. The primary goal of this monograph is to help business decision-makers educate themselves on the burgeoning field of speech analytics as well as to understand how it impacts the broader enterprise landscape.
Author: J P Shim
Publisher:
ISBN: 9781680836967
Category :
Languages : en
Pages : 72
Get Book Here
Book Description
Speech analytics utilizes speech recognition, predictive analytics, and authentication of the data streams while assessing customers' complaints in real-time. Assessment occurs through the collection and analysis of current data mixed with historical facts to determine patterns and to predict trends. In the current research, the authors have chosen to focus primarily on speech analytics, serving as an umbrella term encompassing speech analytics, audio-mining technologies. The use of speech analytics typically refers to a broader range of speech products, such as analyzing voice identification, emotion detection, and phonetics/speech analysis. Speech Analytics for Actionable Insights proceeds with the discussion of an overview of enterprise needs for speech analytics, a brief history of the speech recognition, the infrastructure of phonetic versus transcription approaches and real-time versus post-call solutions, major speech analytics vendors and their features, applications found within case studies, and recommendations and guidance. The primary goal of this monograph is to help business decision-makers educate themselves on the burgeoning field of speech analytics as well as to understand how it impacts the broader enterprise landscape.
Author: Wei-Dong (Jackie) Zhu
Publisher: IBM Redbooks
ISBN: 0738439428
Category : Computers
Languages : en
Pages : 598
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Book Description
IBM® WatsonTM Content Analytics (Content Analytics) Version 3.0 (formerly known as IBM Content Analytics with Enterprise Search (ICAwES)) helps you to unlock the value of unstructured content to gain new actionable business insight and provides the enterprise search capability all in one product. Content Analytics comes with a set of tools and a robust user interface to empower you to better identify new revenue opportunities, improve customer satisfaction, detect problems early, and improve products, services, and offerings. To help you gain the most benefits from your unstructured content, this IBM Redbooks® publication provides in-depth information about the features and capabilities of Content Analytics, how the content analytics works, and how to perform effective and efficient content analytics on your content to discover actionable business insights. This book covers key concepts in content analytics, such as facets, frequency, deviation, correlation, trend, and sentimental analysis. It describes the content analytics miner, and guides you on performing content analytics using views, dictionary lookup, and customization. The book also covers using IBM Content Analytics Studio for domain-specific content analytics, integrating with IBM Content Classification to get categories and new metadata, and interfacing with IBM Cognos® Business Intelligence (BI) to add values in BI reporting and analysis, and customizing the content analytics miner with APIs. In addition, the book describes how to use the enterprise search capability for the discovery and retrieval of documents using various query and visual navigation techniques, and customization of crawling, parsing, indexing, and runtime search to improve search results. The target audience of this book is decision makers, business users, and IT architects and specialists who want to understand and analyze their enterprise content to improve and enhance their business operations. It is also intended as a technical how-to guide for use with the online IBM Knowledge Center for configuring and performing content analytics and enterprise search with Content Analytics.
Author: Mrs.B.KALA
Publisher: SK Research Group of Companies
ISBN: 8119980115
Category : Mathematics
Languages : en
Pages : 124
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Book Description
Mrs.B.KALA, Assistant Professor, Department of Education, PSN College of Education, Melathidiyoor, Tirunelveli, Tamil Nadu, India. Dr.S.PRIYA, Assistant Professor, Department of Tamil, Vaigai Arts & Science Women's College, Muthampatty, Valappady, Salem, Tamil Nadu, India. Dr.P.VENKATESAN, Assistant Professor, Department of Tamil, Kandaswami Kandar's College, P. Velur, Namakkal, Tamil Nadu, India. Dr.R.BHAVANI, Professor, Institute of Computer Science and Engineering, Saveetha School of Engineering - SIMATS University, Chennai, Tamil Nadu, India. Dr.H.ANWER BASHA, Associate Professor, Department of Computer Science, Saveetha College of Liberal Arts and Sciences, SIMATS University, Chennai, Tamil Nadu, India.
Author: Dipanjan Sarkar
Publisher: Apress
ISBN: 1484223888
Category : Computers
Languages : en
Pages : 397
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Book Description
Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. What You Will Learn: Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern Who This Book Is For : IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data
Author: Gregory S. Nelson
Publisher: John Wiley & Sons
ISBN: 1119425093
Category : Business & Economics
Languages : en
Pages : 468
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Book Description
An evidence-based organizational framework for exceptional analytics team results The Analytics Lifecycle Toolkit provides managers with a practical manual for integrating data management and analytic technologies into their organization. Author Gregory Nelson has encountered hundreds of unique perspectives on analytics optimization from across industries; over the years, successful strategies have proven to share certain practices, skillsets, expertise, and structural traits. In this book, he details the concepts, people and processes that contribute to exemplary results, and shares an organizational framework for analytics team functions and roles. By merging analytic culture with data and technology strategies, this framework creates understanding for analytics leaders and a toolbox for practitioners. Focused on team effectiveness and the design thinking surrounding product creation, the framework is illustrated by real-world case studies to show how effective analytics team leadership works on the ground. Tools and templates include best practices for process improvement, workforce enablement, and leadership support, while guidance includes both conceptual discussion of the analytics life cycle and detailed process descriptions. Readers will be equipped to: Master fundamental concepts and practices of the analytics life cycle Understand the knowledge domains and best practices for each stage Delve into the details of analytical team processes and process optimization Utilize a robust toolkit designed to support analytic team effectiveness The analytics life cycle includes a diverse set of considerations involving the people, processes, culture, data, and technology, and managers needing stellar analytics performance must understand their unique role in the process of winnowing the big picture down to meaningful action. The Analytics Lifecycle Toolkit provides expert perspective and much-needed insight to managers, while providing practitioners with a new set of tools for optimizing results.
Author: Gerardus Blokdyk
Publisher: 5starcooks
ISBN: 9780655836100
Category :
Languages : en
Pages : 310
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Book Description
How do customer interactions affect your organizations overall performance? What does that mean? Can your system store index files in a compressed format, or must they be in a non-compressed format for the speech analytics process? Do you require call and screen recording capability for playback? What is the average payback/ROI from your real-time speech analytics application, in months? This premium Speech Analytics Applications self-assessment will make you the dependable Speech Analytics Applications domain standout by revealing just what you need to know to be fluent and ready for any Speech Analytics Applications challenge. How do I reduce the effort in the Speech Analytics Applications work to be done to get problems solved? How can I ensure that plans of action include every Speech Analytics Applications task and that every Speech Analytics Applications outcome is in place? How will I save time investigating strategic and tactical options and ensuring Speech Analytics Applications costs are low? How can I deliver tailored Speech Analytics Applications advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Speech Analytics Applications essentials are covered, from every angle: the Speech Analytics Applications self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Speech Analytics Applications outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Speech Analytics Applications practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Speech Analytics Applications are maximized with professional results. Your purchase includes access details to the Speech Analytics Applications self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Speech Analytics Applications Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Author: Tycoon Success
Publisher: Tycoon Success
ISBN:
Category : Biography & Autobiography
Languages : en
Pages : 36
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Book Description
Discover the future of business innovation with "The 10 Most Disruptive Business Leaders to Watch in 2022." This captivating book takes you on a journey through the groundbreaking achievements of visionary entrepreneurs who are reshaping industries and redefining success. Uncover the stories behind ten remarkable individuals who have revolutionized their respective fields, leaving an indelible mark on the business landscape. From tech titans disrupting traditional business models to social impact pioneers changing the world, these game-changing leaders are at the forefront of innovation. Through insightful profiles, you'll delve into the minds of these disruptors and explore the strategies and philosophies that have propelled them to the top. Gain unique insights into their bold visions, relentless determination, and groundbreaking ideas that are reshaping the future of commerce. "The 10 Most Disruptive Business Leaders to Watch in 2022" offers invaluable lessons and inspiration for aspiring entrepreneurs, business professionals, and anyone passionate about staying ahead in a rapidly evolving world. Whether you're seeking inspiration, looking to learn from the best, or simply fascinated by the power of disruptive innovation, this book is a must-read. Join us on this thrilling exploration of the most influential business minds of our time. Get ready to be inspired, motivated, and equipped with the knowledge to navigate the dynamic and ever-changing business landscape. Embrace the future and discover the visionaries shaping tomorrow's world today.
Author: Gerardus Blokdyk
Publisher: 5starcooks
ISBN: 9780655193418
Category :
Languages : en
Pages : 126
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Book Description
Are assumptions made in Speech analytics stated explicitly? What are the Essentials of Internal Speech analytics Management? What are the key elements of your Speech analytics performance improvement system, including your evaluation, organizational learning, and innovation processes? Is there a critical path to deliver Speech analytics results? What about Speech analytics Analysis of results? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Speech analytics investments work better. This Speech analytics All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Speech analytics Self-Assessment. Featuring 701 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Speech analytics improvements can be made. In using the questions you will be better able to: - diagnose Speech analytics projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Speech analytics and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Speech analytics Scorecard, you will develop a clear picture of which Speech analytics areas need attention. Your purchase includes access details to the Speech analytics self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.
Author: Jillur Quddus
Publisher: Packt Publishing Ltd
ISBN: 1789349370
Category : Computers
Languages : en
Pages : 233
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Book Description
Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-time Key FeaturesMake a hands-on start in the fields of Big Data, Distributed Technologies and Machine LearningLearn how to design, develop and interpret the results of common Machine Learning algorithmsUncover hidden patterns in your data in order to derive real actionable insights and business valueBook Description Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data. What you will learnUnderstand how Spark fits in the context of the big data ecosystemUnderstand how to deploy and configure a local development environment using Apache SparkUnderstand how to design supervised and unsupervised learning modelsBuild models to perform NLP, deep learning, and cognitive services using Spark ML librariesDesign real-time machine learning pipelines in Apache SparkBecome familiar with advanced techniques for processing a large volume of data by applying machine learning algorithmsWho this book is for This book is aimed at Business Analysts, Data Analysts and Data Scientists who wish to make a hands-on start in order to take advantage of modern Big Data technologies combined with Advanced Analytics.
Author: Raghav Bali
Publisher: Packt Publishing Ltd
ISBN: 1787125467
Category : Computers
Languages : en
Pages : 394
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Book Description
Tap into the realm of social media and unleash the power of analytics for data-driven insights using R About This Book A practical guide written to help leverage the power of the R eco-system to extract, process, analyze, visualize and model social media data Learn about data access, retrieval, cleaning, and curation methods for data originating from various social media platforms. Visualize and analyze data from social media platforms to understand and model complex relationships using various concepts and techniques such as Sentiment Analysis, Topic Modeling, Text Summarization, Recommendation Systems, Social Network Analysis, Classification, and Clustering. Who This Book Is For It is targeted at IT professionals, Data Scientists, Analysts, Developers, Machine Learning Enthusiasts, social media marketers and anyone with a keen interest in data, analytics, and generating insights from social data. Some background experience in R would be helpful, but not necessary, since this book is written keeping in mind, that readers can have varying levels of expertise. What You Will Learn Learn how to tap into data from diverse social media platforms using the R ecosystem Use social media data to formulate and solve real-world problems Analyze user social networks and communities using concepts from graph theory and network analysis Learn to detect opinion and sentiment, extract themes, topics, and trends from unstructured noisy text data from diverse social media channels Understand the art of representing actionable insights with effective visualizations Analyze data from major social media channels such as Twitter, Facebook, Flickr, Foursquare, Github, StackExchange, and so on Learn to leverage popular R packages such as ggplot2, topicmodels, caret, e1071, tm, wordcloud, twittR, Rfacebook, dplyr, reshape2, and many more In Detail The Internet has truly become humongous, especially with the rise of various forms of social media in the last decade, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the reader to understand the current social media landscape and to learn how analytics can be leveraged to derive insights from it. This data can be analyzed to gain valuable insights into the behavior and engagement of users, organizations, businesses, and brands. It will help readers frame business problems and solve them using social data. The book will also cover several practical real-world use cases on social media using R and its advanced packages to utilize data science methodologies such as sentiment analysis, topic modeling, text summarization, recommendation systems, social network analysis, classification, and clustering. This will enable readers to learn different hands-on approaches to obtain data from diverse social media sources such as Twitter and Facebook. It will also show readers how to establish detailed workflows to process, visualize, and analyze data to transform social data into actionable insights. Style and approach This book follows a step-by-step approach with detailed strategies for understanding, extracting, analyzing, visualizing, and modeling data from several major social network platforms such as Facebook, Twitter, Foursquare, Flickr, Github, and StackExchange. The chapters cover several real-world use cases and leverage data science, machine learning, network analysis, and graph theory concepts along with the R ecosystem, including popular packages such as ggplot2, caret,dplyr, topicmodels, tm, and so on.
