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Advanced Data Mining and Applications : 7th International Conference, ADMA 2011, Beijing, China, December 17-19, 2011, Proceedings, Part II

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Cover of 'Advanced Data Mining and Applications : 7th International Conference, ADMA 2011, Beijing, China, December 17-19, 2011, Proceedings, Part II'

Table of Contents

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    Book Overview
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    Chapter 1 Generating Syntactic Tree Templates for Feature-Based Opinion Mining
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    Chapter 2 Handling Concept Drift via Ensemble and Class Distribution Estimation Technique
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    Chapter 3 HUE-Stream: Evolution-Based Clustering Technique for Heterogeneous Data Streams with Uncertainty
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    Chapter 4 Hybrid Artificial Immune Algorithm and CMAC Neural Network Classifier for Supporting Business and Medical Decision Making
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    Chapter 5 Improving Suffix Tree Clustering with New Ranking and Similarity Measures
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    Chapter 6 Individual Doctor Recommendation Model on Medical Social Network
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    Chapter 7 Influence Maximizing and Local Influenced Community Detection Based on Multiple Spread Model
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    Chapter 8 Interactive Predicate Suggestion for Keyword Search on RDF Graphs
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    Chapter 9 Advanced Data Mining and Applications
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    Chapter 10 Learning to Make Social Recommendations: A Model-Based Approach
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    Chapter 11 Microgroup Mining on TSina via Network Structure and User Attribute
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    Chapter 12 Mining Good Sliding Window for Positive Pathogens Prediction in Pathogenic Spectrum Analysis
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    Chapter 13 Mining Patterns from Longitudinal Studies
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    Chapter 14 Mining Top-K Sequential Rules
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    Chapter 15 Mining Uncertain Data Streams Using Clustering Feature Decision Trees
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    Chapter 16 Multi-view Laplacian Support Vector Machines
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    Chapter 17 New Developments of Determinacy Analysis
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    Chapter 18 On Mining Anomalous Patterns in Road Traffic Streams
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    Chapter 19 Ontology Guided Data Linkage Framework for Discovering Meaningful Data Facts
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    Chapter 20 Predicting New User’s Behavior in Online Dating Systems
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    Chapter 21 Sequential Pattern Mining from Stream Data
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    Chapter 22 Social Influence Modeling on Smartphone Usage
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    Chapter 23 Social Network Inference of Smartphone Users Based on Information Diffusion Models
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    Chapter 24 Support Vector Regression with A Priori Knowledge Used in Order Execution Strategies Based on VWAP
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    Chapter 25 Terrorist Organization Behavior Prediction Algorithm Based on Context Subspace
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    Chapter 26 Topic Discovery and Topic-Driven Clustering for Audit Method Datasets
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    Chapter 27 Transportation Modes Identification from Mobile Phone Data Using Probabilistic Models
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    Chapter 28 User Graph Regularized Pairwise Matrix Factorization for Item Recommendation
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    Chapter 29 Using Predicate-Argument Structures for Context-Dependent Opinion Retrieval
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    Chapter 30 XML Document Clustering Using Structure-Preserving Flat Representation of XML Content and Structure
Attention for Chapter 27: Transportation Modes Identification from Mobile Phone Data Using Probabilistic Models
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Chapter title
Transportation Modes Identification from Mobile Phone Data Using Probabilistic Models
Chapter number 27
Book title
Advanced Data Mining and Applications
Published by
Springer, Berlin, Heidelberg, December 2011
DOI 10.1007/978-3-642-25856-5_27
Book ISBNs
978-3-64-225855-8, 978-3-64-225856-5
Authors

Dafeng Xu, Guojie Song, Peng Gao, Rongzeng Cao, Xinwei Nie, Kunqing Xie

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 6%
Unknown 15 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 25%
Student > Master 3 19%
Student > Ph. D. Student 2 13%
Lecturer > Senior Lecturer 1 6%
Student > Bachelor 1 6%
Other 1 6%
Unknown 4 25%
Readers by discipline Count As %
Computer Science 5 31%
Engineering 3 19%
Economics, Econometrics and Finance 1 6%
Medicine and Dentistry 1 6%
Design 1 6%
Other 0 0%
Unknown 5 31%