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ORCID20th ICDM 2020: Sorrento, Italy - Workshops
- Giuseppe Di Fatta, Victor S. Sheng, Alfredo Cuzzocrea, Carlo Zaniolo, Xindong Wu:
20th International Conference on Data Mining Workshops, ICDM Workshops 2020, Sorrento, Italy, November 17-20, 2020. IEEE 2020, ISBN 978-1-7281-9012-9
Sentiment Elicitation from Natural Text for Information Retrieval and Extraction (SENTIRE)
- Alfredo Cuzzocrea, Carlo Zaniolo:
Message from the ICDM 2020 General Chairs. xxi - Nasser Alsadhan, David B. Skillicorn:
Sentiment is an Attitude not a Feeling. 1-6 - Jonathan Kevin Chandra, Erik Cambria
, Andrea Nanetti:
One Belt, One Road, One Sentiment? A Hybrid Approach to Gauging Public Opinions on the New Silk Road Initiative. 7-14 - Iti Chaturvedi, Edoardo Ragusa, Paolo Gastaldo, Erik Cambria:
COAL: Convolutional Online Adaptation Learning for Opinion Mining. 15-22 - Tim Draws, Jody Liu, Nava Tintarev:
Helping users discover perspectives: Enhancing opinion mining with joint topic models. 23-30 - Giuseppe Di Fatta, Victor S. Sheng, Alfredo Cuzzocrea:
The IEEE ICDM 2020 Workshops. 26-29 - Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani:
MEET: A Method for Embeddings Evaluation for Taxonomic Data. 31-38 - Devjyoti Nath, Anirban Roy, Sumitra Kumari Shaw, Amlan Ghorai, Shanta Phani:
Textual Lyrics Based Emotion Analysis of Bengali Songs. 39-44 - Diana Nurbakova, Liana Ermakova, Irina Ovchinnikova:
Understanding the Personality of Contributors to Information Cascades in Social Media in Response to the COVID-19 Pandemic. 45-52 - Matthias Pohl, Ali Hashaam, Sascha Bosse, Daniel Gunnar Staegemann, Matthias Volk, Frederik Kramer, Klaus Turowski:
Application of NLP to determine the State of Issues in Bug Tracking Systems. 53-61 - Marco Siino, Marco La Cascia, Ilenia Tinnirello:
WhoSNext: Recommending Twitter Users to Follow Using a Spreading Activation Network Based Approach. 62-70 - L. D. C. S. Subhashini, Yuefeng Li, Jinglan Zhang, Ajantha S. Atukorale:
Integration of Fuzzy and Deep Learning in Three-Way Decisions. 71-78
IEEE International Workshop on Data Mining for Service (DMS 2020)
- Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff:
CAMTA: Causal Attention Model for Multi-touch Attribution. 79-86 - Diana Nurbakova, Timothée Saumet:
Deal Closure Prediction based on User's Browsing Behaviour of Sales Content. 87-92 - Amit Neil Ramkissoon, Shareeda Mohammed:
An Experimental Evaluation of Data Classification Models for Credibility Based Fake News Detection. 93-100 - Natsuki Sano:
Synthetic Data by Principal Component Analysis. 101-105 - Wenwen Xia, Fangqi Li, Shenghong Li:
Gaussian Process Bandits for Online Influence Maximization. 106-113 - Katsutoshi Yada, Ken Ishibashi, Taku Ohashi, Danhua Wang, Shusaku Tsumoto:
How Shoppers Walk and Shop in a Supermarket. 114-118
ICDM NeuRec Workshop 2020
- Qinghong Chen, Huobin Tan, Guangyan Lin, Ze Wang:
A Hierarchical Knowledge and Interest Propagation Network for Recommender Systems. 119-126 - Yuting Chen, Yanshi Wang, Yabo Ni, Anxiang Zeng, Lanfen Lin:
Scenario-aware and Mutual-based approach for Multi-scenario Recommendation in E-Commerce. 127-135 - Kai Deng, Jiajin Huang, Jin Qin:
HybridGNN-SR: Combining Unsupervised and Supervised Graph Learning for Session-based Recommendation. 136-143 - Venkataramana B. Kini, Ashwin Manjunatha:
Revenue Maximization using Multitask Learning for Promotion Recommendation. 144-150 - Zhen Liu, Jingyu Tian, Lingxi Zhao, Yanling Zhang:
Attentive-Feature Transfer based on Mapping for Cross-domain Recommendation. 151-158 - Ying Liufu, Long Jin, Mei Liu, Shuai Li:
A Recommender Algorithm: Gradient Recurrent Neural Network Applied to Yang-Baxter-Like Equation. 159-165 - Zheda Mai, Ga Wu, Kai Luo, Scott Sanner:
Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. 165-172 - Kun Niu, Yicong Yu, Xipeng Cao, Chao Wang:
GCMCSR: A New Graph Convolution Matrix Complete Method with Side-Information Reconstruction. 173-180 - Tomas Sousa Pereira, Tiago Cunha, Carlos Soares:
$\mu-\text{cf}2\text{vec}$: Representation Learning for Personalized Algorithm Selection in Recommender Systems. 181-188 - Marlesson R. O. Santana, Luckeciano C. Melo, Fernando H. F. Camargo, Bruno Brandão, Anderson Soares, Renan M. Oliveira, Sandor Caetano:
MARS-Gym: A Gym framework to model, train, and evaluate Recommender Systems for Marketplaces. 189-197 - Bassem Samir, Neamat El-Tazi:
Enhancing Multi-factor Friend Recommendation in Location-based Social Networks. 198-205 - Ahmad Shahzad, Frans Coenen:
Efficient Distributed MST Based Clustering for Recommender Systems. 206-210 - Li Yang, E. Shijia, Shiyao Xu, Yang Xiang:
Interactive Knowledge Graph Attention Network for Recommender Systems. 211-219 - Rui Ye, Qing Zhang, Hengliang Luo:
Cross-Session Aware Temporal Convolutional Network for Session-based Recommendation. 220-226 - Hangbin Zhang, Raymond K. Wong, Victor W. Chu:
Hybrid Learning with Teacher-student Knowledge Distillation for Recommenders. 227-235 - Yujia Zheng, Siyi Liu, Zekun Li, Shu Wu:
DGTN: Dual-channel Graph Transition Network for Session-based Recommendation. 236-242
Large-scale Industrial Time Series Analysis (LITSA 2020)
- Bhaskar Dhariyal, Thach Le Nguyen, Severin Gsponer, Georgiana Ifrim:
An Examination of the State-of-the-Art for Multivariate Time Series Classification. 243-250 - Jihed Khiari, Cristina Olaverri-Monreal:
Boosting Algorithms for Delivery Time Prediction in Transportation Logistics. 251-258 - Michael Franklin Mbouopda, Engelbert Mephu Nguifo:
Uncertain Time Series Classification with Shapelet Transform. 259-266 - JunYong Tong, Nick Torenvliet:
Temporally-Reweighted Dirichlet Process Mixture Anomaly Detector. 267-274 - Jurgen O. D. van den Hoogen, Stefan Bloemheuvel, Martin Atzmueller:
An Improved Wide-Kernel CNN for Classifying Multivariate Signals in Fault Diagnosis. 275-283
8th ICDM Workshop on High Dimensional Data Mining (HDM 2020)
- Huan He, Yuanzhe Xi, Joyce C. Ho:
Accelerated SGD for Tensor Decomposition of Sparse Count Data. 284-291 - Julie Jiang, Kristina Lerman, Emilio Ferrara:
Individualized Context-Aware Tensor Factorization for Online Games Predictions. 292-299 - Daniyal Kazempour, Peer Kröger, Thomas Seidl:
Towards an Internal Evaluation Measure for Arbitrarily Oriented Subspace Clustering. 300-307 - Daniyal Kazempour, Long Mathias Yan, Peer Kröger, Thomas Seidl:
You see a set of wagons - I see one train: Towards a unified view of local and global arbitrarily oriented subspace clusters. 308-315 - Daniyal Kazempour, Anna Beer, Peer Kröger, Thomas Seidl:
I fold you so! An internal evaluation measure for arbitrary oriented subspace clustering. 316-323 - Dan Lu, Daniel M. Ricciuto:
Efficient Distance-based Global Sensitivity Analysis for Terrestrial Ecosystem Modeling. 324-332
DDIF: Deep Data Intelligence for Finance 2020
- Jacopo Fior, Luca Cagliero:
Exploring the Use of Data at Multiple Granularity Levels in Machine Learning-Based Stock Trading. 333-340 - Bate He, Eisuke Kita:
Stock Price Prediction by Using Hybrid Sequential Generative Adversarial Networks. 341-347 - Anton Kovantsev, Peter Gladilin:
Analysis of multivariate time series predictability based on their features. 348-355 - Ying Liu, Wei Wang, Tianlin Zhang, Zhenyu Cui:
AttentionFM: Incorporating Attention Mechanism and Factorization Machine for Credit Scoring. 356-361 - Geet Shingi:
A federated learning based approach for loan defaults prediction. 362-368 - Kin-Hon Ho, Wai-Han Chiu, Chin Li:
A Short-Term Cryptocurrency Price Movement Prediction Using Centrality Measures. 369-376 - Ajim Uddin, Xinyuan Tao, Chia-Ching Chou, Dantong Yu:
Nonlinear Tensor Completion Using Domain Knowledge: An Application in Analysts' Earnings Forecast. 377-384 - Yiqi Zhao, Matloob Khushi:
Wavelet Denoised-ResNet CNN and LightGBM Method to Predict Forex Rate of Change. 385-391
ICDM Workshop on Continual Learning and Adaptation for Time Evolving Data (CLEATED 2020)
- Sarah Klein, Mathias Verbeke:
An unsupervised methodology for online drift detection in multivariate industrial datasets. 392-399 - Shalini Pandey, Andrew S. Lan, George Karypis, Jaideep Srivastava:
Learning Student Interest Trajectory for MOOC Thread Recommendation. 400-407 - Ricardo Pereira, Bruno Casal Laraña, Nádia Soares, Miguel Araújo:
TEDD: Robust Detection of Unstable Temporal Features. 408-415 - Christian Schreckenberger, Tim Glockner, Heiner Stuckenschmidt, Christian Bartelt:
Restructuring of Hoeffding Trees for Trapezoidal Data Streams. 416-423 - Chang How Tan, Vincent C. S. Lee, Mahsa Salehi:
MIR_MAD: An Efficient and On-line Approach for Anomaly Detection in Dynamic Data Stream. 424-431 - Meng Wang, Zhijun Ding, Meiqin Pan:
LbR: A New Regression Architecture for Automated Feature Engineering. 432-439 - Wernsen Wong, Gillian Dobbie:
Pelican: Continual Adaptation for Phishing Detection. 440-447
2nd IEEE ICDM Workshop on Deep Learning and Clustering (DLC 2020)
- Subhajit Das, Panpan Xu, Zeng Dai, Alex Endert, Liu Ren:
Interpreting Deep Neural Networks through Prototype Factorization. 448-457 - Souradip Chakraborty, Ekansh Verma, Saswata Sahoo, Jyotishka Datta:
FairMixRep: Self-supervised Robust Representation Learning for Heterogeneous Data with Fairness constraints. 458-463 - Yunsheng Pang, Feiyu Chen, Sheng Huang, Yongxin Ge, Wei Wang, Taiping Zhang:
Deep Fuzzy Clustering with Weighted Intra-class Variance and Extended Mutual Information Regularization. 464-471
1st ICDM Workshop on Deep Learning for Cyber Threat Intelligence (DL-CTI)
- Clinton Daniel, Thomas Gill, Alan R. Hevner, Matthew Mullarkey:
A Deep Neural Network Approach to Tracing Paths in Cybersecurity Investigations. 472-479 - Maryam Heidari, James H. Jones, Özlem Uzuner:
Deep Contextualized Word Embedding for Text-based Online User Profiling to Detect Social Bots on Twitter. 480-487 - Fang Yu Lin, Yizhi Liu, Mohammadreza Ebrahimi, Zara Ahmad-Post, James Lee Hu, Jingyu Xin, Sagar Samtani, Weifeng Li, Hsinchun Chen:
Linking Personally Identifiable Information from the Dark Web to the Surface Web: A Deep Entity Resolution Approach. 488-495 - Syed Hasan Amin Mahmood, Ahmed Abbasi:
Using Deep Generative Models to Boost Forecasting: A Phishing Prediction Case Study. 496-505 - Edward Raff, Bobby Filar, James Holt:
Getting Passive Aggressive About False Positives: Patching Deployed Malware Detectors. 506-515 - Md. Rayhanur Rahman, Rezvan Mahdavi-Hezaveh, Laurie A. Williams:
A Literature Review on Mining Cyberthreat Intelligence from Unstructured Texts. 516-525
Deep Learning for Internet of Things (DL-IoT 2020)
- Xin Wang, Yunji Liang, Zhiwen Yu, Bin Guo:
Learning Latent Correlation of Heterogeneous Sensors Using Attention based Temporal Convolutional Network. 526-534 - Qiuyun Zhang, Bin Guo, Sicong Liu, Zhiwen Yu:
CrowdDepict: Know What and How to Generate Personalized and Logical Product Description using Crowd intelligence. 535-542 - Shuo Zhang, Xiaofei Chen, Jiayuan Chen, Qiao Jiang, Hejiao Huang:
Anomaly Detection of Periodic Multivariate Time Series under High Acquisition Frequency Scene in IoT. 543-552 - Yefan Zhou, Zhao Lv, Chaoqun Wang, Shengli Zhang:
A Two-Stream Network For Driving Hand Gesture Recognition. 553-560
1st International Workshop on Multi-Source Data Mining (MSDM)
- Jia Chen, Evangelos E. Papalexakis:
Ensemble Node Embeddings using Tensor Decomposition: A Case-Study on DeepWalk. 561-563 - Haonan Huang, Naiyao Liang, Wei Yan, Zuyuan Yang, Zhenni Li, Weijun Sun:
Partially Shared Semi-supervised Deep Matrix Factorization with Multi-view Data. 564-570 - Zheng Li, Yue Zhao, Jialin Fu:
SynC: A Copula based Framework for Generating Synthetic Data from Aggregated Sources. 571-578 - Denis Maurel, Sylvain Lefebvre, Jérémie Sublime:
Deep Cooperative Reconstruction with Security Constraints in multi-view environments. 579-588 - Krati Saxena, Ashwini Patil, Sagar Sunkle, Vinay Kulkarni:
Mining Heterogeneous Data for Formulation Design. 589-596 - Mickael Wajnberg, Petko Valtchev, Alexandre Blondin Massé, Abderrahim Benmoussa, Maja Krajinovic, Caroline Laverdière, Emile Levy, Daniel Sinnett, Valérie Marcil:
Mining Heterogeneous Associations from Pediatric Cancer Data by Relational Concept Analysis. 597-604 - Chin-Chia Michael Yeh, Dhruv Gelda, Zhongfang Zhuang, Yan Zheng, Liang Gou, Wei Zhang:
Towards a Flexible Embedding Learning Framework. 605-612
The 8th Workshop on Data Mining in Biomedical Informatics and Healthcare (DMBIH 2020)
- Abdulyekeen T. Adebisi, Venkateswarlu Gonuguntla, Ho-Won Lee, Kalyana C. Veluvolu:
Classification of Dementia Associated Disorders Using EEG based Frequent Subgraph Technique. 613-620 - Dijana Kosmajac, Kirstie Smith, Vlado Keselj, Susan Kirkland:
Graph-based Topic Extraction Using Centroid Distance of Phrase Embeddings on Healthy Aging Open-ended Survey Questions. 621-628 - Krzysztof Mnich, Aneta Polewko-Klim, Agnieszka Kitlas Golinska, Wojciech Lesinski, Witold R. Rudnicki:
Super Learning with Repeated Cross Validation. 629-635 - Anindya Moitra, Nicholas O. Malott, Philip A. Wilsey:
Persistent Homology on Streaming Data. 636-643 - Frank Ruis, Shreyasi Pathak, Jeroen Geerdink, Johannes H. Hegeman, Christin Seifert, Maurice van Keulen:
Human-in-the-loop Language-agnostic Extraction of Medication Data from Highly Unstructured Electronic Health Records. 644-650 - Yun Zhao, Franklin Ly, Qinghang Hong, Zhuowei Cheng, Tyler Santander, Henry T. Yang, Paul K. Hansma, Linda R. Petzold:
How Much Does It Hurt: A Deep Learning Framework for Chronic Pain Score Assessment. 651-660
3rd Utility-Driven Mining and Learning (UDML 2020)
- Minh-Son Dao, Ngoc-Thanh Nguyen, R. Uday Kiran, Koji Zettsu:
Insights From Urban Sensing Data: From Chaos to Predicted Congestion Patterns. 661-668 - Tzung-Pei Hong, Meng-Ping Ku, Wei-Ming Huang, Shu-Min Li, Jerry Chun-Wei Lin:
A Tree-based Fuzzy Average-Utility Mining Algorithm. 669-672 - Mourad Nouioua, Ying Wang, Philippe Fournier-Viger, Jerry Chun-Wei Lin, Jimmy Ming-Tai Wu:
TKC: Mining Top-K Cross-Level High Utility Itemsets. 673-682 - Abhay Shukla, Jairaj Sathyanarayana, Dipyaman Banerjee:
Sample-Rank: Weak Multi-Objective Recommendations Using Rejection Sampling. 683-689 - Jimmy Ming-Tai Wu, Qian Teng, Gautam Srivastava, Matin Pirouz, Jerry Chun-Wei Lin:
Efficient Mining of Non-Dominated High Quantity-Utility Patterns. 690-695
The 4th International Workshop on Big Data Analysis for Smart Energy (BigData4SmartEnergy 2020)
- Alfredo Cuzzocrea:
Scalable Distributed Pivot Analysis over Massive Big Data: Models, Paradigms, New Advancements. 696-700 - ChangHwan Kim, Se-Young Yun:
Precipitation Nowcasting Using Grid-based Data in South Korea Region. 701-706 - Hyunjin Kim, Dongseop Lee, Jaecheol Ryou:
User Authentication Method using FIDO based Password Management for Smart Energy Environment. 707-710 - Jin-Young Kim, Sung-Bae Cho:
Electric Energy Demand Forecasting with Explainable Time-series Modeling. 711-716 - Changha Lee, Seong-Hwan Kim, Chan-Hyun Youn:
An Accelerated Continual Learning with Demand Prediction based Scheduling in Edge-Cloud Computing. 717-722 - Eunju Yang, Changha Lee, Ji-Hwan Kim, Tuan Manh Tao, Chan-Hyun Youn:
StreamDL: Deep Learning Serving Platform for AMI Stream Forecasting. 723-728 - Gihun Lee, Sangmin Bae, Jaehoon Oh, Se-Young Yun:
SIPA: A Simple Framework for Efficient Networks. 729-736 - Hyoungwoo Lee, Jaegul Choo:
Data analysis and processing for spatio-temporal forecasting. 737-739 - Kyeong-Min Lee, InA Kim, Kyu-Chul Lee:
DQN-based Join Order Optimization by Learning Experiences of Running Queries on Spark SQL. 740-742 - Nyoungwoo Lee, Jehyun Nam, Ho-Jin Choi:
Anomaly Detection and Visualization for Electricity Consumption Data. 743-749 - Sue Hyang Lim, Seon Hyeog Kim, Hyeong Min Lee, Si Joong Kim, Yong-June Shin:
Design of Neural Network-based Boost Charging for Reducing the Charging Time of Li-ion Battery. 750-756 - Hyung-Jun Moon, Seok-Jun Bu, Sung-Bae Cho:
Learning Disentangled Representation of Residential Power Demand Peak via Convolutional-Recurrent Triplet Network. 757-761 - Sungwoo Park, Jihoon Moon, Eenjun Hwang:
Explainable Anomaly Detection for District Heating Based on Shapley Additive Explanations. 762-765
International Workshop on Mining and Learning in the Legal Domain (MLLD-2020)
- Elliott Ash, Jeff Jacobs, W. Bentley MacLeod, Suresh Naidu, Dominik Stammbach:
Unsupervised Extraction of Workplace Rights and Duties from Collective Bargaining Agreements. 766-774 - Alfredo Montelongo, João Luiz Becker:
Tasks performed in the legal domain through Deep Learning: A bibliometric review (1987-2020). 775-781 - Sourav Mukherjee, Tim Oates, Vince DiMascio, Huguens Jean, Rob Ares, David Widmark, Jaclyn Harder:
Immigration Document Classification and Automated Response Generation. 782-789 - Ritika Pandey, P. Jeffrey Brantingham, Craig D. Uchida, George O. Mohler:
Building knowledge graphs of homicide investigation chronologies. 790-798 - George Sanchez:
Using Unlabeled Data for US Supreme Court Case Classification. 799-804
15th International Workshop on Spatial and Spatiotemporal Data Mining (SSTDM-20)
- Andrea Brunello, Martin Kraft, Angelo Montanari, Federico Pittino, Andrea Urgolo:
Virtual Sensing of Temperatures in Indoor Environments: A Case Study. 805-810 - Akira Kusaba, Kilho Shin, Dave Shepard, Tetsuji Kuboyama:
Predictive Nonlinear Modeling by Koopman Mode Decomposition. 811-819 - Pierre-Antoine Laharotte, Romain Billot, Nour-Eddin El Faouzi:
Detecting Dynamic Critical Links within Large Scale Network for Traffic State Prediction. 820-827 - Parashuram Shourya Rajulapati, Nivedita Nukavarapu, Surya S. Durbha:
Deep Learning-based Critical Infrastructure Simulation Model for Disaster Monitoring. 828-835
IncrLearn - Incremental classification and clustering, concept drift, novelty detection in big/fast data context
- Alexandre Abraham, Léo Dreyfus-Schmidt:
Rebuilding Trust in Active Learning with Actionable Metrics. 836-843 - Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Incremental Rebalancing Learning on Evolving Data Streams. 844-850 - Tengyue Li, Simon Fong, Yaoyang Wu, Antonio J. Tallón-Ballesteros:
Kennard-Stone Balance Algorithm for Time-series Big Data Stream Mining. 851-858 - Zoltán Puha, Maurits Kaptein, Aurélie Lemmens:
Batch Mode Active Learning for Individual Treatment Effect Estimation. 859-866 - Parsa Vafaie, Herna L. Viktor, Wojtek Michalowski:
Multi-class imbalanced semi-supervised learning from streams through online ensembles. 867-874 - Shujie Yin, Guanjun Liu, Zhenchuan Li, Chungang Yan, Changjun Jiang:
An Accuracy-and-Diversity-based Ensemble Method for Concept Drift and Its application in Fraud Detection. 875-882 - Giacomo Ziffer, Alessio Bernardo, Emanuele Della Valle, Albert Bifet:
Fast Incremental Naïve Bayes with Kalman Filtering. 883-889
Blockchain Systems for Decentralized Mining (BSDM 2020)
- Yulia Kostyuchenko, Qingshan Jiang:
Blockchain Applications to combat the global trade of falsified drugs. 890-894 - Gejun Le, Qifeng Gu, Qingshan Jiang, Weiyi Lin:
TrustedChain: A Blockchain-based Data Sharing Scheme for Supply Chain. 895-901 - Qinqi Xu, Yimin Lin, Qingshan Jiang, Mengqiu Zhang:
Cache-based Optimization for Block Commit of Hyperledger Fabric. 902-906 - Chenxue Yang, Zhiguo Sun:
Data Management System based on Blockchain Technology for Agricultural Supply Chain. 907-911
Deep Learning for Knowledge Transfer (DLKT 2020)
- Souradip Chakraborty, Aritra Roy Gosthipaty, Sayak Paul:
G-SimCLR: Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling. 912-916 - Zekai Chen, Jiaze E, Xiao Zhang, Hao Sheng, Xiuzheng Cheng:
Multi-Task Time Series Forecasting With Shared Attention. 917-925 - Maria-Cristina V. Marinescu, Artem Reshetnikov, Joaquim Moré López:
Improving object detection in paintings based on time contexts. 926-932 - Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta, Ramesh Raskar:
NoPeek: Information leakage reduction to share activations in distributed deep learning. 933-942
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