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CIDM 2014: Orlando, FL, USA
- 2014 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2014, Orlando, FL, USA, December 9-12, 2014. IEEE 2014, ISBN 978-1-4799-4519-1
CIDM'14 Session 1: Advances in clustering
- Rocco Langone
, Raghvendra Mall
Clustering data over time using kernel spectral clustering with memory. 1-8 - Raghvendra Mall
Agglomerative hierarchical kernel spectral data clustering. 9-16 - Ding Liu, Minghu Jiang, Xiaofang Yang:
Quantum clustering - A novel method for text analysis. 17-23 - Yang Lei, James C. Bezdek, Jeffrey Chan
Generalized information theoretic cluster validity indices for soft clusterings. 24-31 - Leonardo Enzo Brito da Silva
A density-based clustering of the Self-Organizing Map using graph cut. 32-40
CIDM'14 Session 2: Multitask and Metalearning
- Vilen Jumutc
New bilinear formulation to semi-supervised classification based on Kernel Spectral Clustering. 41-47 - Evgeni Aizenberg
Batch linear least squares-based learning algorithm for MLMVN with soft margins. 48-55 - Jakub Smíd, Roman Neruda
Comparing datasets by attribute alignment. 56-62 - Anveshi Charuvaka, Huzefa Rangwala:
Convex multi-task relationship learning using hinge loss. 63-70 - Thomas Villmann, Marika Kaden, Mandy Lange, Paul Sturmer, Wieland Hermann:
Precision-Recall-Optimization in Learning Vector Quantization Classifiers for Improved Medical Classification Systems. 71-77
Special Session: CIDM'14 Session 3: Computational Intelligence for Health and Wellbeing
- Kamal Taha
BioHCDP: A Hybrid Constituency-Dependency Parser for Biological NLP information extraction. 78-85 - Henry Joutsijoki, Jyrki Rasku, Markus Haponen, Ivan Baldin, Yulia Gizatdinova, Michelangelo Paci, Jyri Saarikoski, Kirsi Varpa, Harri Siirtola, Jorge Avalos-Salguero, Kati Iltanen, Jorma Laurikkala, Kirsi Penttinen, Jari A. K. Hyttinen
Classification of iPSC colony images using hierarchical strategies with support vector machines. 86-92 - Sandra Ortega-Martorell
Semi-supervised source extraction methodology for the nosological imaging of glioblastoma response to therapy. 93-98 - Sandra Ortega-Martorell
Automatic relevance source determination in human brain tumors using Bayesian NMF. 99-104 - Giulia Fiscon
Alzheimer's disease patients classification through EEG signals processing. 105-112
CIDM'14 Session 4: Mining Relational and Networked data
- Lawrence O. Hall, Alireza Chakeri:
Relational data partitioning using evolutionary game theory. 113-120 - Oliver Schulte, Kurt Routley:
Aggregating predictions vs. aggregating features for relational classification. 121-128 - Banage T. G. S. Kumara
Ontology learning with complex data type for Web service clustering. 129-136 - Anil Kumar
Semantic clustering-based cross-domain recommendation. 137-141 - Mustafa H. Hajeer, Dipankar Dasgupta, Alexander Semenov, Jari Veijalainen:
Distributed evolutionary approach to data clustering and modeling. 142-148
Special Session: CIDM'14 Session 5: High Dimensional Data Analysis
- Benoît Frénay
Valid interpretation of feature relevance for linear data mappings. 149-156 - Joset A. Etzel, Todd S. Braver:
High dimensional exploration: A comparison of PCA, distance concentration, and classification performance in two fMRI datasets. 157-162 - John Aldo Lee
Two key properties of dimensionality reduction methods. 163-170 - Diego Hernán Peluffo-Ordóñez
Generalized kernel framework for unsupervised spectral methods of dimensionality reduction. 171-177 - Vineet Mehta, Rajmonda Sulo Caceres, Kevin M. Carter:
Evaluating topic quality using model clustering. 178-185
CIDM'14 Session 6: Rule based Modelling, Model Performance, and Interpretability
- Jesus Soto, Patricia Melin
Optimization of the type-1 and interval type-2 fuzzy integrators in Ensembles of ANFIS models for prediction of the Dow Jones time series. 186-193 - Ulf Johansson, Cecilia Sönströd, Rikard König:
Accurate and interpretable regression trees using oracle coaching. 194-201 - Xing Hu, Sukanya Manna, Brian N. Truong:
Product aspect identification: Analyzing role of different classifiers. 202-209 - Rikard König, Ulf Johansson:
Rule extraction using genetic programming for accurate sales forecasting. 210-216 - Georgios Orfanidis, Anastasios Tefas
Facial image clustering in stereo videos using local binary patterns and double spectral analysis. 217-221
Poster Session: SSCI'14 Poster Session
- Penugonda Ravikumar
Weighted feature-based classification of time series data. 222-228 - Tomoyuki Hiroyasu, Kenya Hanawa, Utako Yamamoto:
Gender classification of subjects from cerebral blood flow changes using Deep Learning. 229-233 - Tomoyuki Hiroyasu, Toshihide Shiraishi, Tomoya Yoshida, Utako Yamamoto:
A feature transformation method using genetic programming for two-class classification. 234-240 - Fabio Fabris
Dependency network methods for Hierarchical Multi-label Classification of gene functions. 241-248 - Alessandro Berti, Alessandro Sperduti, Andrea Burattin
A novel criterion for overlapping communities detection and clustering improvement. 249-256 - Hebah ElGibreen
Incremental transfer RULES with incomplete data. 257-264 - Balvant Yadav, V. Susheela Devi:
Novelty detection applied to the classification problem using Probabilistic Neural Network. 265-272 - Simon J. Chambers, Ian H. Jarman, Paulo J. G. Lisboa:
A framework for initialising a dynamic clustering algorithm: ART2-A. 273-280 - Banage T. G. S. Kumara
Recommendation for Web services with domain specific context awareness. 281-287 - Yuan Sun, Wenbin Guo, Xiaobing Zhao:
Tibetan-Chinese cross language named entity extraction based on comparable corpus and naturally annotated resources. 288-295 - Pekka Siirtola
Detecting and profiling sedentary young men using machine learning algorithms. 296-303 - Santosh Tirunagari
Patient level analytics using self-organising maps: A case study on Type-1 Diabetes self-care survey responses. 304-309 - Tobias Ebert, Julian Belz, Oliver Nelles:
Interpolation and extrapolation: Comparison of definitions and survey of algorithms for convex and concave hulls. 310-314 - Kuang-Pen Chou, Mukesh Prasad
Takagi-Sugeno-Kang type collaborative fuzzy rule based system. 315-320 - Heli Koskimäki
Recognizing gym exercises using acceleration data from wearable sensors. 321-328 - Zena Wood:
What can spatial collectives tell us about their environment? 329-336 - Bartosz Krawczyk, Michal Wozniak
Weighted one-class classification for different types of minority class examples in imbalanced data. 337-344 - Jie Yang
A sparsity-based training algorithm for Least Squares SVM. 345-350 - Waleed Yamany, Eid Emary, Aboul Ella Hassanien:
Wolf search algorithm for attribute reduction in classification. 351-358 - Rocco Langone
Alarm prediction in industrial machines using autoregressive LS-SVM models. 359-364 - Julio J. Valdés, Catherine Cheung, Matthew Li:
Sensor dynamics in high dimensional phase spaces via nonlinear transformations: Application to helicopter loads monitoring. 365-372 - Dai Li, Yi Lu Murphey:
Automatic text categorization using a system of high-precision and high-recall models. 373-380
Special Session: CIDM'14 Session 7: Business Process Mining, Market Analysis and Process Big Data
- Niels Martin
The use of process mining in a business process simulation context: Overview and challenges. 381-388 - Mario Luca Bernardi
Discovering cross-organizational business rules from the cloud. 389-396 - Alexandre Pimenta, Frederico Gadelha Guimarães
GoldMiner: A genetic programming based algorithm applied to Brazilian Stock Market. 397-402
CIDM'14 Session 8: Educational Data Mining
- Fiona J. Buckingham, Keeley A. Crockett, Zuhair Bandar, James O'Shea:
FATHOM: A neural network-based non-verbal human comprehension detection system for learning environments. 403-409 - Ahmad Slim, Gregory L. Heileman, Jarred Kozlick, Chaouki T. Abdallah
Predicting student success based on prior performance. 410-415 - Norman Poh, Ian Smythe:
To what extend can we predict students' performance? A case study in colleges in South Africa. 416-421
CIDM'14 Session 9: Modelling and Mining Massive Data Sets
- Mark Rahmes, Kevin L. Fox, John Delay, Gran Roe:
Matching social network biometrics using geo-analytical behavioral modeling. 422-430 - Connie Khor Li Kou, Chao-Hui Huang:
Massively parallelized support vector machines based on GPU-accelerated multiplicative updates. 431-438 - Gregory Ditzler, Matthew Austen, Gail L. Rosen
Scaling a neyman-pearson subset selection approach via heuristics for mining massive data. 439-445 - Ahsanul Haque, Swarup Chandra, Latifur Khan
MapReduce guided approximate inference over graphical models. 446-453 - Erin-Elizabeth A. Durham, Andrew Rosen, Robert W. Harrison
Optimization of relational database usage involving Big Data a model architecture for Big Data applications. 454-462
CIDM'14 Session 10: Advanced signal processing and data analysis
- Jean-Marc Andreoli:
Learning energy consumption profiles from data. 463-470 - Angel Cataron, Razvan Andonie
kNN estimation of the unilateral dependency measure between random variables. 471-478 - Leong Lee, Gregory S. Ridenour:
Using data mining to investigate interaction between channel characteristics and hydraulic geometry channel types. 479-488 - Zhen Ni, Siyao Fu, Bo Tang, Haibo He, Xinming Huang:
Experimental studies on indoor sign recognition and classification. 489-494 - Quan Ding, Steven Kay, Xiaorong Zhang:
High-SNR model order selection using exponentially embedded family and its applications to curve fitting and clustering. 495-500
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