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Advances in Knowledge Discovery and Data Mining

Overview of attention for book
Cover of 'Advances in Knowledge Discovery and Data Mining'

Table of Contents

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    Book Overview
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    Chapter 1 Emotion Cause Detection for Chinese Micro-Blogs Based on ECOCC Model
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    Chapter 2 Parallel Recursive Deep Model for Sentiment Analysis
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    Chapter 3 Sentiment Analysis in Transcribed Utterances
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    Chapter 4 Rating Entities and Aspects Using a Hierarchical Model
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    Chapter 5 Sentiment Analysis on Microblogging by Integrating Text and Image Features
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    Chapter 6 TSum4act: A Framework for Retrieving and Summarizing Actionable Tweets During a Disaster for Reaction
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    Chapter 7 Evolving Chinese Restaurant Processes for Modeling Evolutionary Traces in Temporal Data
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    Chapter 8 Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints
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    Chapter 9 Spectral Clustering for Large-Scale Social Networks via a Pre-Coarsening Sampling based NystrÖm Method
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    Chapter 10 pcStream: A Stream Clustering Algorithm for Dynamically Detecting and Managing Temporal Contexts
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    Chapter 11 Clustering Over Data Streams Based on Growing Neural Gas
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    Chapter 12 Computing and Mining ClustCube Cubes Efficiently
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    Chapter 13 Contextual Anomaly Detection Using Log-Linear Tensor Factorization
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    Chapter 14 A Semi-Supervised Framework for Social Spammer Detection
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    Chapter 15 Fast One-Class Support Vector Machine for Novelty Detection
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    Chapter 16 ND-Sync: Detecting Synchronized Fraud Activities
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    Chapter 17 An Embedding Scheme for Detecting Anomalous Block Structured Graphs
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    Chapter 18 A Core-Attach Based Method for Identifying Protein Complexes in Dynamic PPI Networks
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    Chapter 19 Mining Uncertain Sequential Patterns in Iterative MapReduce
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    Chapter 20 Quality Control for Crowdsourced POI Collection
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    Chapter 21 Towards Efficient Sequential Pattern Mining in Temporal Uncertain Databases
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    Chapter 22 Preference-Based Top-k Representative Skyline Queries on Uncertain Databases
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    Chapter 23 Cluster Sequence Mining: Causal Inference with Time and Space Proximity Under Uncertainty
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    Chapter 24 Achieving Accuracy Guarantee for Answering Batch Queries with Differential Privacy
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    Chapter 25 Automated Classification of Passing in Football
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    Chapter 26 Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records
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    Chapter 27 Predicting Next Locations with Object Clustering and Trajectory Clustering
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    Chapter 28 A Plane Moving Average Algorithm for Short-Term Traffic Flow Prediction
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    Chapter 29 Recommending Profitable Taxi Travel Routes Based on Big Taxi Trajectories Data
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    Chapter 30 Semi Supervised Adaptive Framework for Classifying Evolving Data Stream
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    Chapter 31 Cost-Sensitive Feature Selection on Heterogeneous Data
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    Chapter 32 A Feature Extraction Method for Multivariate Time Series Classification Using Temporal Patterns
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    Chapter 33 Scalable Outlying-Inlying Aspects Discovery via Feature Ranking
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    Chapter 34 A DC Programming Approach for Sparse Optimal Scoring
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    Chapter 35 Graph Based Relational Features for Collective Classification
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    Chapter 36 A New Feature Sampling Method in Random Forests for Predicting High-Dimensional Data
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    Chapter 37 Seamlessly Integrating Effective Links with Attributes for Networked Data Classification
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    Chapter 38 Clustering on Multi-source Incomplete Data via Tensor Modeling and Factorization
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    Chapter 39 Locally Optimized Hashing for Nearest Neighbor Search
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    Chapter 40 Advances in Knowledge Discovery and Data Mining
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    Chapter 41 Efficient Discovery of Recurrent Routine Behaviours in Smart Meter Time Series by Growing Subsequences
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    Chapter 42 Convolutional Nonlinear Neighbourhood Components Analysis for Time Series Classification
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    Chapter 43 Clustering-Based Scalable Indexing for Multi-party Privacy-Preserving Record Linkage
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    Chapter 44 Efficient Interactive Training Selection for Large-Scale Entity Resolution
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    Chapter 45 Unsupervised Blocking Key Selection for Real-Time Entity Resolution
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    Chapter 46 Incorporating Probabilistic Knowledge into Topic Models
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    Chapter 47 Learning Focused Hierarchical Topic Models with Semi-Supervision in Microblogs
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    Chapter 48 Predicting Future Links Between Disjoint Research Areas Using Heterogeneous Bibliographic Information Network
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    Chapter 49 CPT+: Decreasing the Time/Space Complexity of the Compact Prediction Tree
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    Chapter 50 Mining Association Rules in Graphs Based on Frequent Cohesive Itemsets
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    Chapter 51 Mining High Utility Itemsets in Big Data
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    Chapter 52 Decomposition Based SAT Encodings for Itemset Mining Problems
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    Chapter 53 A Comparative Study on Parallel LDA Algorithms in MapReduce Framework
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    Chapter 54 Distributed Newton Methods for Regularized Logistic Regression
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    Chapter 55 Coupled Matrix Factorization Within Non-IID Context
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    Chapter 56 Complementary Usage of Tips and Reviews for Location Recommendation in Yelp
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    Chapter 57 Coupling Multiple Views of Relations for Recommendation
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    Chapter 58 Pairwise One Class Recommendation Algorithm
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    Chapter 59 RIT: Enhancing Recommendation with Inferred Trust
Overall attention for this book and its chapters
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Mentioned by

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13 tweeters
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1 patent

Citations

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2 Dimensions

Readers on

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91 Mendeley
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Title
Advances in Knowledge Discovery and Data Mining
Published by
Springer International Publishing, May 2015
DOI 10.1007/978-3-319-18032-8
ISBNs
978-3-31-918031-1, 978-3-31-918032-8
Editors

Cao, Tru, Lim, Ee-Peng, Zhou, Zhi-Hua, Ho, Tu-Bao, Cheung, David, Motoda, Hiroshi

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 91 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 13%
Student > Master 11 12%
Researcher 7 8%
Student > Postgraduate 4 4%
Student > Doctoral Student 3 3%
Other 7 8%
Unknown 47 52%
Readers by discipline Count As %
Computer Science 29 32%
Engineering 4 4%
Business, Management and Accounting 2 2%
Mathematics 2 2%
Psychology 1 1%
Other 4 4%
Unknown 49 54%