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Opinion Mining Using Domain Relevance

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Extracting Knowledge From Opinion Mining

opinion mining. Extracting Knowledge From Opinion Mining is an essential resource that presents detailed information on web mining, business;

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From Opinion Mining to Financial Argument Mining

Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most;

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Sentiment Analysis in the Bio Medical Domain

health community to use these sources for opinion mining. This book presents a lexicon-based approach to sentiment analysis in the bio-medical;

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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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Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data

; semantics; text mining, open-domain information extraction and machine reading of the Web; sentiment analysis, opinion mining and text;

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Computational Medicine in Data Mining and Modeling

further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets;

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Sentic Computing

reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and;

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Opinion Mining im Web 2 0

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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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Cambodia's Contested Forest Domain

Tells the story of Cambodia's contested forest domain and details the competing economic forces that are transforming the forests;

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Domain Driven Data Mining

outputs. This monograph, Domain Driven Data Mining, is motivated by the real-world challenges to and complexities of the current KDD methodologies;

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Advanced Data Mining and Applications

Mining and Applications, ADMA 2013, held in Hangzhou, China, in December 2013. The 32 regular papers and 64 short papers presented in these two;

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Knowledge Mining Using Intelligent Agents

Knowledge Mining Using Intelligent Agents explores the concept of knowledge discovery processes and enhances decision-making capability;

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Mining Rights on the Public Domain. Lode and Placer Claims, Tunnels, Mill Sites and Water Rights, St

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Web Mining

: - Literature review of research work in the area of web mining - Business websites domain researched, and data collected using site-analyzer tool;

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Exploratory Data Mining and Data Cleaning

* Written for practitioners of data mining, data cleaning and database management. * Presents a technical treatment of data quality;

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Biomedical Data Mining Using Machine Learning

text mining in any domain.;

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Advances in Knowledge Discovery and Data Mining

; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms;

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Advances in Knowledge Discovery and Data Mining

; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms;

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Mining Data for Financial Applications

This book constitutes revised selected papers from the 4th Workshop on Mining Data for Financial Applications, MIDAS 2019, held;

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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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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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Educational Data Mining with R and Rattle

mining implementation using R and Rattle open source data mining tools. . Technical topics discussed in the book include: * Emerging Research;

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Information and Knowledge Engineering

Mining, Opinion Management, Software Quality Issues, Bioinformatics, and Applications;

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