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Sentiment Analysis and Knowledge Discovery in Contemporary Business

who are using them to collect vital data. Sentiment Analysis and Knowledge Discovery in Contemporary Business is an essential reference;

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Big Data Analytics and Knowledge Discovery

; advanced programming paradigms; non-functional requirements satisfaction; machine learning; social media and twitter analysis; sentiment analysis;

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Business Intelligence

to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge;

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Advances in Knowledge Discovery and Data Mining

methods and algorithms; opinion mining and sentiment analysis; clustering; feature extraction and pattern mining; graph and network data;

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Advances in Knowledge Discovery and Data Mining

methods and algorithms; opinion mining and sentiment analysis; clustering; feature extraction and pattern mining; graph and network data;

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Sentiment Analysis and Opinion Mining

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and;

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Advances in Knowledge Discovery and Data Mining

learning; applications; novel methods and algorithms; opinion mining and sentiment analysis; clustering; outlier and anomaly detection; mining;

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Advances in Knowledge Discovery and Data Mining

learning; applications; novel methods and algorithms; opinion mining and sentiment analysis; clustering; outlier and anomaly detection; mining;

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Data Mining Methods for Knowledge Discovery

of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets;

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Technology Supporting Business Solutions

integration, as well as data analysis and knowledge discovery. This book is a showcase of recent, significant advances in web-based information;

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Trends and Applications in Knowledge Discovery and Data Mining

Pacific-Asia Conference on Knowledge Discovery and Data Mining in Auckland, New Zealand, in April 2016. The 23 revised papers presented;

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Knowledge Discovery Process and Methods to Enhance Organizational Performance

Although the terms data mining and knowledge discovery and data mining (KDDM) are sometimes used interchangeably, data mining;

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Sentiment Analysis in Social Networks

. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an;

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Sentiment Analysis and Opinion Mining

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and;

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Trends and Applications in Knowledge Discovery and Data Mining

Pacific-Asia Conference on Knowledge Discovery and Data Mining in May 2017 in Jeju, South Korea. The 17 revised papers presented were carefully;

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SOA Modeling Patterns for Service-Oriented Discovery and Analysis

analysisFocusing on the Service-Oriented Discovery and Analysis Life Cycle Stage, this book will help you acquire a broad SOA Modeling knowledge base and;

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Advances in Knowledge Discovery and Data Mining

, unstructured and semi-structured data; sentiment analysis; statistical/graphical model; multi-source/distributed/parallel/cloud computing.;

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Advances in Knowledge Discovery and Data Mining

, unstructured and semi-structured data; sentiment analysis; statistical/graphical model; multi-source/distributed/parallel/cloud computing.;

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Business Information Systems

data and ontologies, recommendations and content analysis, knowledge discovery, and IT frameworks and systems architecture.;

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Sentimental Analysis and Deep Learning

analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated;

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery;

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Artificial Intelligence for Business

competitive. Chapter 5 features natural language processing (NLP) for sentiment analysis focused on emotions. With the help of sentiment analysis;

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Machine Learning for Predictive Analysis

This book gathers papers addressing state-of-the-art research in the areas of machine learning and predictive analysis, presented virtually;

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Multimodal Sentiment Analysis

extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment;

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Mastering QlikView Data Visualization

Take your QlikView skills to the next level and master the art of creating visual data analysis for real business needs About This Book;

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The Sentiment of Reality

Originally published in 1983, The Sentiment of Reality covers the rise and decline of the realist novel from the mid-eighteenth century to;

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Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks

highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis. The mathematical abstraction of the;

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