Data Mining and Big Data

Data Mining and Big Data Front Cover
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2016-06-14
569 pages

Book Description

Data Mining and Big Data: First International Conference, DMBD 2016, Bali, Indonesia, June 25-30, 2016. Proceedings (Lecture Notes in Computer Science)

The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016.

The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions. The theme of DMBD 2016 is "Serving Life with Data Science". Data mining refers to the activity of going through big data sets to look for relevant or pertinent information.

The papers are organized in 10 cohesive sections covering all major topics of the research and development of data mining and big data and one Workshop on Computational Aspects of Pattern Recognition and Computer Vision.

Table of Contents

Chapter 1. Challenges in Data Mining and Big Data
Chapter 2. Evolutionary Computation and Big Data: Key Challenges and Future Directions
Chapter 3. Prospects and Challenges in Online Data Mining
Chapter 4. Data Mining
Chapter 5. Enhance AdaBoost by Integrating LDA Topic Model
Chapter 6. An Improved Algorithm for MicroRNA Profiling from Next Generation Sequencing Data
Chapter 7. Utilising the Cross Industry Standard Process for Data Mining to Reduce Uncertainty in the Measurement and Verification of Energy Savings
Chapter 8. Implementing Majority Voting Rule to Classify Corporate Value Based on Environmental Efforts
Chapter 9. Model Proposal of Knowledge Management for Technology Based Companies
Chapter 10. Frequent Itemset Mining
Chapter 11. Oracle and Vertica for Frequent Itemset Mining
Chapter 12. Reconstructing Positive Surveys from Negative Surveys with Background Knowledge
Chapter 13. Spatial Data Mining
Chapter 14. Application of the Spatial Data Mining Methodology and Gamification for the Optimisation of Solving the Transport Issues of the “Varsovian Mordor”
Chapter 15. A Geo-Social Data Model for Moving Objects
Chapter 16. Optimization on Arrangement of Precaution Areas Serving for Ships’ Routeing in the Taiwan Strait Based on Massive AIS Data
Chapter 17. Prediction
Chapter 18. Bulk Price Forecasting Using Spark over NSE Data Set
Chapter 19. Prediction and Survival Analysis of Patients After Liver Transplantation Using RBF Networks
Chapter 20. Link Prediction by Utilizing Correlations Between Link Types and Path Types in Heterogeneous Information Networks
Chapter 21. Advanced Predictive Methods of Artificial Intelligence in Intelligent Transport Systems
Chapter 22. Range Prediction Models for E-Vehicles in Urban Freight Logistics Based on Machine Learning
Chapter 23. Feature Selection
Chapter 24. Partitioning Based N-Gram Feature Selection for Classification
Chapter 25. A Supervised Biclustering Optimization Model for Feature Selection in Biomedical Dataset Classification
Chapter 26. Term Space Partition Based Ensemble Feature Construction for Spam Detection
Chapter 27. Information Extraction
Chapter 28. Term Extraction from German Computer Science Textbooks
Chapter 29. An FW-DTSS Based Approach for News Page Information Extraction
Chapter 30. A Linear Regression Approach to Multi-criteria Recommender System
Chapter 31. Classification
Chapter 32. Classification of Power Quality Disturbances Using Forest Algorithm
Chapter 33. A Sequential k-Nearest Neighbor Classification Approach for Data-Driven Fault Diagnosis Using Distance- and Density-Based Affinity Measures
Chapter 34. A Model Combining SOMs with SVRs for Patent Quality Analysis and Classification
Chapter 35. Mining Best Strategy for Multi-view Classification
Chapter 36. Anomaly Pattern and Diagnosis
Chapter 37. Detecting Variable Length Anomaly in Time Series Data
Chapter 38. Bigger Data Is Better for Molecular Diagnosis Tests Based on Decision Trees
Chapter 39. Waiting Time Screening in Diagnostic Medical Imaging – A Case-Based View
Chapter 40. Data Visualization Analysis
Chapter 41. Real-Time Data Analytics: An Algorithmic Perspective
Chapter 42. High-Dimensional Data Visualization Based on User Knowledge
Chapter 43. A Data Mining and Visual Analytics Perspective on Sustainability-Oriented Infrastructure Planning
Chapter 44. Visual Interactive Approach for Mining Twitter's Networks
Chapter 45. Privacy Policy
Chapter 46. Key Indicators for Data Sharing - In Relation with Digital Services
Chapter 47. Efficient Probabilistic Methods for Proof of Possession in Clouds
Chapter 48. Cloud-Based Storage Model with Strong User Privacy Assurance
Chapter 49. Social Media
Chapter 50. The Role of Social Media in Innovation and Creativity: The Case of Chinese Social Media
Chapter 51. Malay Word Stemmer to Stem Standard and Slang Word Patterns on Social Media
Chapter 52. Two-Phase Computing Model for Chinese Microblog Sentimental Analysis
Chapter 53. Local Community Detection Based on Bridges Ideas
Chapter 54. Environment for Data Transfer Measurement
Chapter 55. Query Optimization and Processing Algorithm
Chapter 56. Ant Colony-Based Approach for Query Optimization
Chapter 57. A Range Query Processing Algorithm Hiding Data Access Patterns in Outsourced Environment
Chapter 58. Big Data
Chapter 59. Big Data Tools: Haddop, MongoDB and Weka
Chapter 60. Big Data Meaning in the Architecture of IoT for Smart Cities
Chapter 61. Linear TV Recommender Through Big Data
Chapter 62. Data Models in NoSQL Databases for Big Data Contexts
Chapter 63. Probabilistic Mining in Large Transaction Databases
Chapter 64. Computational Aspects of Pattern Recognition and Computer Vision
Chapter 65. A First Attempt on Online Data Stream Classifier Usi

Book Details

  • Title: Data Mining and Big Data
  • Author: ,
  • Length: 569 pages
  • Edition: 1st ed. 2016
  • Language: English
  • Publisher:
  • Publication Date: 2016-06-14
  • ISBN-10: 3319409727
  • ISBN-13: 9783319409726
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