Real Computer Science begins where we almost stop reading ...: Data and Text Mining

Wednesday, 3 April 2013

Data and Text Mining

Read and Download Links are at near the bottom of the page.

Title Theory and Applications for Advanced Text Mining
Author(s) Shigeaki Sakurai
Publisher: InTech (November 21, 2012)
Hardcover 218 pages
eBook PDF Files, and a zipped PDF, 3.94 MB; Kindle (4301 KB)
Language: English
ISBN-10/ASIN: B00ABDHNB0
ISBN-13: 978-953-51-0852-8

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Chapter 1 Survey on Kernel-Based Relation Extractionby Hanmin Jung, Sung-Pil Choi, Seungwoo Lee and Sa-Kwang Song
Chapter 2 Analysis for Finding Innovative Concepts Based on Temporal Patterns of Terms in Documentsby Hidenao Abe
Chapter 3 Text Clumping for Technical Intelligenceby Alan Porter and Yi Zhang
Chapter 4 A Semantic-Based Framework for Summarization and Page Segmentation in Web Miningby Alessio Leoncini, Fabio Sangiacomo, Paolo Gastaldo and Rodolfo Zunino
Chapter 5 Ontology Learning Using Word Net Lexical Expansion and Text Miningby Hiep Luong, Susan Gauch and Qiang Wang
Chapter 6 Automatic Compilation of Travel Information from Texts: A Surveyby Hidetsugu Nanba, Aya Ishino and Toshiyuki Takezawa
Chapter 7 Analyses on Text Data Related to the Safety of Drug Use Based on Text Mining Techniquesby Masaomi Kimura
Chapter 8 Biomedical Named Entity Recognition: A Survey of Machine-Learning Toolsby David Campos, Sérgio Matos and José Luís Oliveira
Chapter 9 Toward Computational Processing of Less Resourced Languages: Primarily Experiments for Moroccan Amazigh Languageby Fadoua Ataa Allah and Siham Boulaknadel

Title Introduction to Data Science
Author(s) Jeffrey Stanton
Publisher: InTech (November 21, 2012)
Hardcover/Paperback N/A
eBook PDF, 157 pages, 18.46 MB
Language: English

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Advances in Data Mining Knowledge Discovery and Applications aims to help data miners, researchers, scholars, and PhD students who wish to apply data mining techniques. The primary contribution of this book is highlighting frontier fields and implementations of the knowledge discovery and data mining. It seems to be same things are repeated again. But in general, same approach and techniques may help us in different fields and expertise areas. This book presents knowledge discovery and data mining applications in two different sections. As known that, data mining covers areas of statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, and other areas. In this book, most of the areas are covered with different data mining applications. The eighteen chapters have been classified in two parts: Knowledge Discovery and Data Mining Applications.

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Chapter 1 Towards the Formulation of a Unified Data Mining Theory, Implemented by Means of Multiagent Systems (MASs)by Dost Muhammad Khan, Nawaz Mohamudally and D. K. R. Babajee
Chapter 2 Selecting Representative Data Setsby Tomas Borovicka, Marcel Jirina Jr., Pavel Kordik and Marcel Jirina
Chapter 3 Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Miningby Carmelo Cassisi, Placido Montalto, Marco Aliotta, Andrea Cannata and Alfredo Pulvirenti
Chapter 4 Data Mining and Neural Networks: The Impact of Data Representationby Fadzilah Siraj, Ehab A. Omer A. Omer and Md. Rajib Hasan
Chapter 5 Inconsistent Decision System: Rough Set Data Mining Strategy to Extract Decision Algorithm of a Numerical Distance Relay - Tutorialby Mohammad Lutfi Othman and Ishak Aris
Chapter 6 An Unsupervised Classification Method for Hyperspectral Remote Sensing Image Based on Spectral Data Miningby Xingping Wen and Xiaofeng Yang
Chapter 7 Visualization Techniques: Which is the Most Appropriate in the Process of Knowledge Discovery in Data Base?by Maria Madalena Dias, Juliana Keiko Yamaguchi, Emerson Rabelo and Clélia Franco
Chapter 8 Analysis and Learning Frameworks for Large-Scale Data Miningby Kohsuke Yanai and Toshihiko Yanase
Chapter 9 Data Mining Applied to Cognitive Radio Systemsby Lilian Freitas, Yomara Pires, Jefferson Morais, João Costa and Aldebaro Klautau
Chapter 10 Short-Term Energy Price Prediction Multi-Step-Ahead in the Brazilian Market Using Data Miningby José C. Reston Filho, Carolina de M. Affonso and Roberto Célio L. de Oliveira
Chapter 11 Electricity Load Forecasting Using Data Mining Techniqueby Intan Azmira binti Wan Abdul Razak, Shah bin Majid, Mohd Shahrieel bin Mohd. Aras and Arfah binti Ahmad
Chapter 12 Mining and Adaptivity in Automated Teller Machinesby Ghulam Mujtaba Shaikh and Tariq Mahmood
Chapter 14 The Performance Evaluation of Speech Recognition by Comparative Approachby R.L.K. Venkateswarlu, R. Raviteja and R. Rajeev
Chapter 15 Data Mining from Remote Sensing Snow and Vegetation Productby Gao Jie
Chapter 16 Mining Complex Network Data for Adaptive Intrusion Detectionby Dewan Md. Farid, Mohammad Zahidur Rahman and Chowdhury Mofizur Rahman
Chapter 17 BotNet Detection: Enhancing Analysis by Using Data Mining Techniquesby Erdem Alparslan, Adem Karahoca and Dilek Karahoca
Chapter 18 Improving Decision Support Systems with Data Mining Techniques"by Adela Bâra and Ion Lungu

Title Getting Started with Data Warehousing
Author(s) Neeraj Sharma, Abhishek Iyer, Rajib Bhattacharya, Niraj Modi and Wagner Crivelini
Publisher: IBM Corporation (Draft, September, 2012)
Hardcover/Paperback N/A
eBook PDF, 157 pages, 3.13 MB
Language: English

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Title Mining of Massive Datasets
Author(s) Anand Rajaraman, Jeffrey D. Ullman
Publisher: Cambridge University Press (November 30, 2011)
Hardcover 336 pages
Language: English
ISBN-10: 1107015359
ISBN-13: 978-1107015357

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Title Knowledge-Oriented Applications in Data Mining
Author(s) Kimito Funatsu
Publisher: IN-TECH (January 2011)
Hardcover 442 pages
eBook Online, HTML
Language: English
ISBN-10: N/A
ISBN-13: 978-953-307-154-1

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Chapter 1 Data Mining Classification Techniques for Human Talent Forecastingby Hamidah Jantan, Abdul Razak Hamdan and Zulaiha Ali Othman
Chapter 2 New Implementations of Data Mining in a Plethora of Human Activitiesby Alberto Ochoa, Julio Ponce, Francisco Ornelas, Rubén Jaramillo, Ramón Zataraín, María Barrón, Claudia Gómez, José Martínez and Arturo Elias
Chapter 3 Data Mining Techniques for Explaining Social Eventsby Krivec Jana and Gams Matjaz
Chapter 4 Mining Enrollment Data Using Descriptive and Predictive Approachesby Fadzilah Siraj and Mansour Ali Abdoulha
Chapter 5 Online Insurance Consumer Targeting and Lifetime Value Evaluating - A Mathematics and Data Mining Approachby Yuanya Li, Gail Cook and Oliver Wreford
Chapter 6 Data Mining Using RFM Analysisby Derya Birant
Chapter 7 Seasonal Climate Prediction for the Australian Sugar Industry Using Data Mining Techniquesby Lachlan Mckinna and Yvette Everingham
Chapter 8 Monthly River Flow Forecasting by Data Mining Processby Özlem Terzi
Chapter 9 Monitoring of Water Quality Using Remote Sensing Data Miningby Xing-Ping Wen and Xiao-Feng Yang
Chapter 10 Applications of Data Mining to Diagnosis and Control of Manufacturing Processesby Marcin Perzyk, Robert Biernacki, Andrzej Kochanski, Jacek Kozlowski and Artur Soroczynski
Chapter 11 Atom Coloring for Chemical Interpretation and De Novo Design for Molecular Designby Kiyoshi Hasegawa, Keiya Migita and Kimito Funatsu
Chapter 12 Hyperspectral Data Analysis and Visualizationby Maarten A. Hogervorst and Piet B.W. Schwering
Chapter 13 Data Retrieval and Visualization for Setting Research Priorities in Biomedical Researchby Hailin Chen and Vincent VanBuren
Chapter 14 DNA Microarray Applied to Data Mining of Bradyrhizobium Elkanii Genome and Prospection of Active Genesby Jackson Marcondes and Eliana G. M. Lemos
Chapter 15 Visual Gene Ontology Based Knowledge Discovery in Functional Genomicsby Stefan Götz and Ana Conesa
Chapter 16 Data Mining in Neurologyby Antonio Candelieri, Giuliano Dolce, Francesco Riganello and Walter G Sannita
Chapter 17 Glucose Prediction in Type 1 and Type 2 Diabetic Patients Using Data Driven Techniquesby Eleni I. Georga, Vasilios C. Protopappas and Dimitrios I. Fotiadis
Chapter 18 Data Mining Based Establishment and Evaluation of Porcine Model for Syndrome in Traditional Chinese Medicine in the Context of Unstable Angina (Myocardial Ischemia)by Huihui Zhao, Jianxin Chen, Qi Shi and Wei Wang
Chapter 19 Results of Data Mining Technique Applied to a Home Enteral Nutrition Databaseby Maria Eliana M. Shieferdecker, Carlos Henrique Kuretzki, José Simão de Paula Pinto, Antônio Carlos Ligoki Campos and Osvaldo Malafaia
Chapter 20 Data Mining in Personalized Speech Disorders Therapy Optimizationby Danubianu Mirela, Tobolcea Iolanda and Stefan Gheorghe Pentiuc
Chapter 21 Data Mining Method For Energy System Aplicationsby Reşat Selbaş, Arzu Şencan and Ecir U. Küçüksille
Chapter 22 Regressionby Mohsen Hajsalehi Sichani and Saeed khalafinejad
Chapter 23 Data Mining: Machine Learning and Statistical Techniquesby Alfonso Palmer, Rafael Jiménez and Elena Gervilla
Chapter 24 Dynamic Data Mining: Synergy of Bio-Inspired Clustering Methodsby Elena N. Benderskaya and Sofya V. Zhukova
Chapter 25 Exploiting Inter-Sample Information and Exploring Visualization in Data Mining: from Bioinformatics to Anthropology and Aesthetics Disciplinesby Kuan-Ming Lin and Jung-Hua Liu
Chapter 26 Data Mining Industrial Applicationsby Waldemar Wójcik and Konrad Gromaszek

Title Data Mining and Knowledge Discovery in Real Life Applications
Author(s) Julio Ponce and Adem Karahoca
Publisher: IN-TECH (January 2009)
Paperback 436 pages
eBook Online, HTML
Language: English
ISBN-10: N/A
ISBN-13: 978-3902613530

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Chapter 1 A Data Mining & Knowledge Discovery Process Modelby Óscar Marbán, Gonzalo Mariscal and Javier Segovia
Chapter 2 Knowledge Discovery on the Gridby Lamine Aouad, An Le-Khac and Tahar Kechadi
Chapter 3 Rough Set Theory — Fundamental Concepts, Principals, Data Extraction, and Applicationsby Silvia Rissino and Germano Lambert-Torres
Chapter 4 Robust Data Mining: An Integrated Approachby Sangmun Shin, Le Yang, Kyungjin Park and Yongsun Choi
Chapter 5 On the Selection of Meaningful Association Rulesby Rangsipan Marukatat
Chapter 6 Hybrid Clustering for Validation and Improvement of Subject-Classification Schemesby Frizo Janssens, Lin Zhang and Wolfgang Glänzel
Chapter 7 Automatic Product Classification Control System Using RFID Tag Information and Data Miningby Cheonshik Kim, Eun-Jun Yoon, Injung Park and and Taek-Young
Chapter 8 Hyperspectral Remote Sensing Data Mining Using Multiple Classifiers Combinationby Xing-Ping Wen, Xiao-Feng Yang and Guang-Dao Hu
Chapter 9 Content-based Image Classification via Visual Learningby Hiroki Nomiya and Kuniaki Uehara
Chapter 10 Clustering Parallel Data Streamsby Yixin Chen
Chapter 11 Mining Multiple-level Association Rules Based on Pre-large Conceptsby Tzung-Pei Hong, Tzu-Jung Huang and Chao-Sheng Chang
Chapter 12 Data Mining Applications: Promise and Challengesby Rukshan Athauda, Menik Tissera and Chandrika Fernando
Chapter 13 Mining Spatio-Temporal Datasets: Relevance, Challenges and Current Research Directionsby M-Tahar Kechadi, Michela Bertolotto, Filomena Ferrucci and Sergio Di Martino
Chapter 14 Benchmarking the Data Mining Algorithms with Adaptive Neuro-Fuzzy Inference System in GSM Churn Managementby Adem Karahoca, Dilek Karahoca and Nizamettin Aydın
Chapter 15 Using Data Mining to Investigate the Behavior of Video Rental Customersby Tai-Chang Hsia and An-Jin Shie
Chapter 16 A Novel Model for Global Customer Retention Using Data Mining Technologyby Jie Lin and Xu Xu
Chapter 17 Data Mining in Web Applicationsby Julio Ponce, Alberto Hernández, Alberto Ochoa, Felipe Padilla, Alejandro Padilla, Francisco Álvarez and Eunice Ponce de León
Chapter 18 Application of Data Mining Techniques to the Data Analyses to Ensure Safety of Medicine Usageby Masaomi Kimura
Chapter 19 Data Mining in the Molecular Biology Era — A Study Directed to Carbohydrates Biosynthesis and Accumulation in Plantsby Renato Vicentini and Marcelo Menossi
Chapter 20 Microarray Data Mining for Biological Pathway Analysisby Miyoung Shin and Jaeyoung Kim
Chapter 21 Development of Microsatellite Markers by Data Mining from DNA Sequencesby Jingou Tong, Dan Wang and Lei Cheng
Chapter 22 Quality Improvement using Data Mining in Manufacturing Processesby Shu-guang He, Zhen He, G. Alan Wang and Li Li
Chapter 23 The Deployment of Data Mining into Operational Business Processesby Rok Rupnik and Jurij Jaklič
Chapter 24 Data Mining Applied to the Instrumentation Data Analysis of a Large Damby Rosangela Villwock, Maria Teresinha Arns Steiner, Andrea Sell Dyminski and Anselmo Chaves Neto
Chapter 25 A Data Mining Algorithm for Monitoring PCB Assembly Qualityby Feng Zhang
Chapter 26 An Overview of Data Mining Techniques Applied to Power Systemsby Jefferson Morais, Yomara Pires, Claudomir Cardoso and Aldebaro Klautau

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Inspiring Quotes

An inspiring quote may be just what you need to turn your day around. Here are some of the most inspiring quotes ever spoken or written.

I hated every minute of training, but I said, “Don’t quit. Suffer now and live the rest of your life as a champion.”

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–Anonymous

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–Eleanor Roosevelt

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–Vince Lombardi

“It is never too late to be what you might have been.”
–George Eliot

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–John Wooden

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–Andrew Jackson

“Failure is the opportunity to begin again more intelligently.”
–Henry Ford

“Try not to become a man of success but rather try to become a man of value.”
–Albert Einstein

“The mind is its own place, and in itself can make a heaven of Hell, a hell of Heaven.”

–John Milton

"If u are student, working and preparing give a little extra effort after regular work. A small sacrifice of TV time, fun time, or facebook time can bring a lot of better things to life than you ever imagined."

-- Naam likhna jaroori nai samajhta.

Thank you for reading, be sure to pass this along!

Wednesday, 3 April 2013

Data and Text Mining

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