Description
Book SynopsisKnowledge Discovery in the Social Scienceshelps readers findvalid, meaningful, and useful information. It is written for researchers and data analysts as well as studentswho have no prior experience in statistics or computer science. Suitable for a variety of classesincluding upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methodsthe book guides readers in the application of data mining techniques and illustrates the significance ofnewlydiscovered knowledge. Readers will learn to: appreciate the role of data mining in scientific research develop an understanding of fundamental concepts of data mining and knowledge discovery use software to carry out data mining tasks select and assess appropriate models to ensure findings are valid and meaningful develop basic skills in data preparation, data mining, model selection, and validation apply concepts with end-of-chapter exercises and review summ
Table of ContentsPART I. KNOWLEDGE DISCOVERY AND DATA MINING IN
SOCIAL SCIENCE RESEARCH
Chapter 1. Introduction
Chapter 2. New Contributions and Challenges
PART II. DATA PREPROCESSING
Chapter 3. Data Issues
Chapter 4. Data Visualization
PART III. MODEL ASSESSMENT
Chapter 5. Assessment of Models
PART IV. DATA MINING: UNSUPERVISED LEARNING
Chapter 6. Cluster Analysis
Chapter 7. Associations
PART V. DATA MINING: SUPERVISED LEARNING
Chapter 8. Generalized Regression
Chapter 9. Classification and Decision Trees
Chapter 10. Artificial Neural Networks
PART VI. DATA MINING: TEXT DATA AND NETWORK DATA
Chapter 11. Web Mining and Text Mining
Chapter 12. Network or Link Analysis
Index
