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Advanced Data Mining and Applications

10th International Conference, ADMA 2014, Guilin, China, December 19-21, 2014, Proceedings

  • Conference proceedings
  • © 2014

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Editors:
  1. Xudong Luo

    1. Sun Yat-sen University, Guangzhou, P.R. China

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  2. Jeffrey Xu Yu

    1. The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

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    You can also search for this editor in PubMed   Google Scholar

  3. Zhi Li

    1. Guanxi Normal University, Guilin, P.R. China

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8933)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ADMA 2014.

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About this book

This book constitutes the proceedings of the 10th International Conference on Advanced Data Mining and Applications, ADMA 2014, held in Guilin, China during December 2014. The 48 regular papers and 10 workshop papers presented in this volume were carefully reviewed and selected from 90 submissions. They deal with the following topics: data mining, social network and social media, recommend systems, database, dimensionality reduction, advance machine learning techniques, classification, big data and applications, clustering methods, machine learning, and data mining and database.

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Table of contents (58 papers)

  1. Front Matter

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  2. Data Mining

    1. A New Improved Apriori Algorithm Based on Compression Matrix

      • Taoshen Li, Dan Luo
      Pages 1-15

    2. FHN: Efficient Mining of High-Utility Itemsets with Negative Unit Profits

      • Philippe Fournier-Viger
      Pages 16-29

    3. Novel Concise Representations of High Utility Itemsets Using Generator Patterns

      • Philippe Fournier-Viger, Cheng-Wei Wu, Vincent S. Tseng
      Pages 30-43

    4. Incrementally Updating High-Utility Itemsets with Transaction Insertion

      • Jerry Chun-Wei Lin, Wensheng Gan, Tzung-Pei Hong, Jeng-Shyang Pan
      Pages 44-56

    5. Mining Frequent Closed Sequential Patterns with Non-user-defined Gap Constraints

      • Wentao Wang, Lei Duan, Jyrki Nummenmaa, Song Deng, Zhongqi Li, Hao Yang et al.
      Pages 57-70

    6. High Utility Episode Mining Made Practical and Fast

      • Guangming Guo, Lei Zhang, Qi Liu, Enhong Chen, Feida Zhu, Chu Guan
      Pages 71-84

  3. Social Network and Social Media

    1. Community Dynamics: Event and Role Analysis in Social Network Analysis

      • Justin Fagnan, Reihaneh Rabbany, Mansoureh Takaffoli, Eric Verbeek, Osmar R. Zaïane
      Pages 85-97

    2. Local Community Extraction for Non-overlapping and Overlapping Community Detection

      • Zhan Bu, Guangliang Gao, Zhiang Wu, Jie Cao, Xiao Zheng
      Pages 98-111

    3. Discovery of Tampered Image with Robust Hashing

      • Zhenjun Tang, Junwei Yu, Xianquan Zhang, Shichao Zhang
      Pages 112-122

    4. TweeProfiles: Detection of Spatio-temporal Patterns on Twitter

      • Tiago Cunha, Carlos Soares, Eduarda Mendes Rodrigues
      Pages 123-136

    5. Real-Time Event Detection Based on Geo Extraction and Temporal Analysis

      • Xiao Feng, Shuwu Zhang, Wei Liang, Zhe Tu
      Pages 137-150

    6. An Automatic Unsupervised Method Based on Context-Sensitive Spectral Angle Mapper for Change Detection of Remote Sensing Images

      • Tauqir Ahmed Moughal, Fusheng Yu
      Pages 151-162

  4. Recommend System

    1. A Personalized Travel System Based on Crowdsourcing Model

      • Yi Zhuang, Fei Zhuge, Dickson K. W. Chiu, Chunhua Ju, Bo Jiang
      Pages 163-174

    2. Difference Factor’ KNN Collaborative Filtering Recommendation Algorithm

      • Wenzhong Liang, Guangquan Lu, Xiaoyu Ji, Jian Li, Dingrong Yuan
      Pages 175-184

    3. A Reputation-Enhanced Recommender System

      • Ahmad Abdel-Hafez, Xiaoyu Tang, Nan Tian, Yue Xu
      Pages 185-198

    4. An Empirical Methodology to Analyze the Behavior of Bagging

      • Fábio Pinto, Carlos Soares, João Mendes-Moreira
      Pages 199-212

    5. Context-Aware Recommendation Using GPU Based Parallel Tensor Decomposition

      • Benyou Zou, Mengwei Lan, Cuiping Li, Liwen Tan, Hong Chen
      Pages 213-226

    6. Location-Based Recommendation Using Incremental Tensor Factorization Model

      • Benyou Zou, Cuiping Li, Liwen Tan, Hong Chen
      Pages 227-238

  5. Database

    1. Mining Continuous Activity Patterns from Animal Trajectory Data

      • Yuwei Wang, Ze Luo, Baoping Yan, John Takekawa, Diann Prosser, Scott Newman
      Pages 239-252
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Other volumes

  1. Advanced Data Mining and Applications

Editors and Affiliations

  • Sun Yat-sen University, Guangzhou, P.R. China

    Xudong Luo

  • The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    Jeffrey Xu Yu

  • Guanxi Normal University, Guilin, P.R. China

    Zhi Li

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