Data Mining and Big Data

1. Front Matter

   Pages I-XV

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2. Association Analysis

   1. Front Matter

      Pages 1-1

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   2. A Process for Exploring Employees’ Relationships via Social Network and Sentiment Analysis

      • Jeydels Barahona, Hung-Min Sun

      Pages 3-8

   3. Mining Relationship Between User Purposes and Product Features Towards Purpose-Oriented Recommendation

      • Sopheaktra Yong, Yasuhito Asano

      Pages 9-21

   4. Finding Top-k Fuzzy Frequent Itemsets from Databases

      • Haifeng Li, Yue Wang, Ning Zhang, Yuejin Zhang

      Pages 22-30

   5. Association Rule Mining in Healthcare Analytics

      • S. Anand Hareendran, S. S. Vinod Chandra

      Pages 31-39

   6. Does Student’s Diligence to Study Relate to His/Her Academic Performance?

      • Toshiro Minami, Yoko Ohura, Kensuke Baba

      Pages 40-47

   7. Correlation Analysis of Diesel Engine Performance Testing Data Based on Mixed-Copula Method

      • Zha Dongye, Qin Wei, Zhang Jie, Zhuang Zilong

      Pages 48-57

3. Clustering

   1. Front Matter

      Pages 59-59

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   2. Comparative Study of Apache Spark MLlib Clustering Algorithms

      • Sasan Harifi, Ebrahim Byagowi, Madjid Khalilian

      Pages 61-73

   3. L-DP: A Hybrid Density Peaks Clustering Method

      • Mingjing Du, Shifei Ding

      Pages 74-80

4. Prediction

   1. Front Matter

      Pages 81-81

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   2. Incremental Adaptive Time Series Prediction for Power Demand Forecasting

      • Petra Vrablecová, Viera Rozinajová, Anna Bou Ezzeddine

      Pages 83-92

   3. Food Sales Prediction with Meteorological Data — A Case Study of a Japanese Chain Supermarket

      • Xin Liu, Ryutaro Ichise

      Pages 93-104

   4. Cascade Spatial Autoregression for Air Pollution Prediction

      • Yangping Li, Xiaorui Wei, Tianming Hu

      Pages 105-112

   5. Machine Learning Techniques for Prediction of Pre-fetched Objects in Handling Big Data Storage

      • Nur Syahela Hussien, Sarina Sulaiman, Siti Mariyam Shamsuddin

      Pages 113-124

5. Classification

   1. Front Matter

      Pages 125-125

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   2. Spectral-Spatial Mineral Classification of Lunar Surface Using Band Parameters with Active Learning

      • Sukanta Roy, Sujai Subbanna, Srinidhii Venkatesh Channagiri, Sharath R Raj, Omkar S.N

      Pages 127-136

   3. R2CEDM: A Rete-Based RFID Complex Event Detection Method

      • Xiaoli Peng, Linjiang Zheng, Ting Liao

      Pages 137-147

   4. Learning Analytics for SNS-Integrated Virtual Learning Environment

      • Fang-Fang Chua, Chia-Ying Khor, Su-Cheng Haw

      Pages 148-155

This book constitutes the refereed proceedings of the Second International Conference on Data Mining and Big Data, DMBD 2017, held in Fukuoka, Japan, in July/August 2017. 
The 53 papers presented in this volume were carefully reviewed and selected from 96 submissions. They were organized in topical sections named: association analysis; clustering; prediction; classification; schedule and sequence analysis; big data; data analysis; data mining; text mining; deep learning; high performance computing; knowledge base and its framework; and fuzzy control. 

• artificial intelligence
• big data
• classification algorithm
• computer aided instruction
• data communication systems
• data mining
• data stream
• fuzzy systems
• genetic algorithms
• internet
• learning algorithms
• learning systems
• mobile computing
• mobile devices
• neural networks
• social networks (SN)
• support vector machines
• SVM
• telecommunication networks
• world wide web (WWW)

• Peking University, Beijing, China

  Ying Tan

• Kyushu University, Fukuoka, Japan

  Hideyuki Takagi

• Southern University of Science and Technology, Shenzhen, China

  Yuhui Shi

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