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Author: Warington Wilkinson Smyth
Publisher:
ISBN:
Category :
Languages : en
Pages : 18
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Author: Warington Wilkinson Smyth
Publisher:
ISBN:
Category :
Languages : en
Pages : 18
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Book Description
Author: Mohammed J. Zaki
Publisher: Cambridge University Press
ISBN: 1108473989
Category : Business & Economics
Languages : en
Pages : 779
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Book Description
New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.
Author: Michael W. Berry
Publisher: World Scientific
ISBN: 9812773630
Category : Computers
Languages : en
Pages : 238
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Book Description
The continual explosion of information technology and the need for better data collection and management methods has made data mining an even more relevant topic of study. Books on data mining tend to be either broad and introductory or focus on some very specific technical aspect of the field. This book is a series of seventeen edited OC student-authored lecturesOCO which explore in depth the core of data mining (classification, clustering and association rules) by offering overviews that include both analysis and insight. The initial chapters lay a framework of data mining techniques by explaining some of the basics such as applications of Bayes Theorem, similarity measures, and decision trees. Before focusing on the pillars of classification, clustering and association rules, the book also considers alternative candidates such as point estimation and genetic algorithms. The book''s discussion of classification includes an introduction to decision tree algorithms, rule-based algorithms (a popular alternative to decision trees) and distance-based algorithms. Five of the lecture-chapters are devoted to the concept of clustering or unsupervised classification. The functionality of hierarchical and partitional clustering algorithms is also covered as well as the efficient and scalable clustering algorithms used in large databases. The concept of association rules in terms of basic algorithms, parallel and distributive algorithms and advanced measures that help determine the value of association rules are discussed. The final chapter discusses algorithms for spatial data mining. Sample Chapter(s). Chapter 1: Point Estimation Algorithms (397 KB). Contents: Point Estimation Algorithms; Applications of Bayes Theorem; Similarity Measures; Decision Trees; Genetic Algorithms; Classification: Distance Based Algorithms; Decision Tree-Based Algorithms; Covering (Rule-Based) Algorithms; Clustering: An Overview; Clustering Hierarchical Algorithms; Clustering Partitional Algorithms; Clustering: Large Databases; Clustering Categorical Attributes; Association Rules: An Overview; Association Rules: Parallel and Distributed Algorithms; Association Rules: Advanced Techniques and Measures; Spatial Mining: Techniques and Algorithms. Readership: An introductory data mining textbook or a technical data mining book for an upper level undergraduate or graduate level course."
Author: Giuseppe Carenini
Publisher: Morgan & Claypool Publishers
ISBN: 160845391X
Category : Technology & Engineering
Languages : en
Pages : 132
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Book Description
Due to the Internet Revolution, human conversational data -- in written forms -- are accumulating at a phenomenal rate. At the same time, improvements in speech technology enable many spoken conversations to be transcribed. Individuals and organizations engage in email exchanges, face-to-face meetings, blogging, texting and other social media activities. The advances in natural language processing provide ample opportunities for these "informal documents" to be analyzed and mined, thus creating numerous new and valuable applications. This book presents a set of computational methods to extract information from conversational data, and to provide natural language summaries of the data. The book begins with an overview of basic concepts, such as the differences between extractive and abstractive summaries, and metrics for evaluating the effectiveness of summarization and various extraction tasks. It also describes some of the benchmark corpora used in the literature. The book introduces extraction and mining methods for performing subjectivity and sentiment detection, topic segmentation and modeling, and the extraction of conversational structure. It also describes frameworks for conducting dialogue act recognition, decision and action item detection, and extraction of thread structure. There is a specific focus on performing all these tasks on conversational data, such as meeting transcripts (which exemplify synchronous conversations) and emails (which exemplify asynchronous conversations). Very recent approaches to deal with blogs, discussion forums and microblogs (e.g., Twitter) are also discussed. The second half of this book focuses on natural language summarization of conversational data. It gives an overview of several extractive and abstractive summarizers developed for emails, meetings, blogs and forums. It also describes attempts for building multi-modal summarizers. Last but not least, the book concludes with thoughts on topics for further development. Table of Contents: Introduction / Background: Corpora and Evaluation Methods / Mining Text Conversations / Summarizing Text Conversations / Conclusions / Final Thoughts
Author: Bristol Trade and Mining Schools, afterwards Merchant Venturers' Technical College (Bristol)
Publisher:
ISBN:
Category :
Languages : en
Pages : 310
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Book Description
Author: Bristol merchant venturers' techn. coll
Publisher:
ISBN:
Category :
Languages : en
Pages : 312
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Book Description
Author: Deepayan Chakrabarti
Publisher: Morgan & Claypool Publishers
ISBN: 160845116X
Category : Computers
Languages : en
Pages : 209
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Book Description
What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints. Table of Contents: Introduction / Patterns in Static Graphs / Patterns in Evolving Graphs / Patterns in Weighted Graphs / Discussion: The Structure of Specific Graphs / Discussion: Power Laws and Deviations / Summary of Patterns / Graph Generators / Preferential Attachment and Variants / Incorporating Geographical Information / The RMat / Graph Generation by Kronecker Multiplication / Summary and Practitioner's Guide / SVD, Random Walks, and Tensors / Tensors / Community Detection / Influence/Virus Propagation and Immunization / Case Studies / Social Networks / Other Related Work / Conclusions
Author: Bing Liu
Publisher: Morgan & Claypool Publishers
ISBN: 1608458849
Category : Computers
Languages : en
Pages : 185
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Book Description
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography
Author: Jure Leskovec
Publisher: Cambridge University Press
ISBN: 1107077230
Category : Computers
Languages : en
Pages : 480
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Book Description
Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Author: Bristol Mining School
Publisher:
ISBN:
Category : Geology
Languages : en
Pages : 318
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Book Description
