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ORCIDBigData Conference 2018: Seattle, WA, USA
- Naoki Abe, Huan Liu, Calton Pu, Xiaohua Hu, Nesreen K. Ahmed, Mu Qiao, Yang Song, Donald Kossmann, Bing Liu, Kisung Lee, Jiliang Tang, Jingrui He, Jeffrey S. Saltz:
IEEE International Conference on Big Data (IEEE BigData 2018), Seattle, WA, USA, December 10-13, 2018. IEEE 2018, ISBN 978-1-5386-5035-6 - Jin-Woo Lee, Seok-Won Chang:
Detailed Configuration of Spatial Hadoop-based Spatial Big Data System and Main Service Status. 1 - Blaise Agüera y Arcas:
Decentralized Machine Learning. 1 - Xuedong Huang:
Big Data for Speech and Language Processing. 2 - Masaru Kitsuregawa:
Transformational Role of Big Data in Society 5.0. 3 - Bin Yu:
Three principles of data science: predictability, computability, and stability (PCS). 4 - Aidong Zhang:
On Metric Learning for Complex Data Analysis. 5 - Soukaina Filali Boubrahimi, Rafal A. Angryk
:
Heuristics Significance of Neuro-Ensemble-based Time Series Classification. 6-15 - Walid Chaabene, Bert Huang:
Best-Choice Edge Grafting for Efficient Structure Learning of Markov Random Fields. 16-25 - So Hirai, Kenji Yamanishi:
Detecting Latent Structure Uncertainty with Structural Entropy. 26-35 - Nikhil Muralidhar, Mohammad Raihanul Islam, Manish Marwah, Anuj Karpatne, Naren Ramakrishnan:
Incorporating Prior Domain Knowledge into Deep Neural Networks. 36-45 - Mona Nashaat, Aindrila Ghosh, James Miller, Shaikh Quader, Chad Marston, Jean-François Puget:
Hybridization of Active Learning and Data Programming for Labeling Large Industrial Datasets. 46-55 - Vahid Noroozi, Sara Bahaadini, Lei Zheng, Sihong Xie, Weixiang Shao, Philip S. Yu:
Semi-supervised Deep Representation Learning for Multi-View Problems. 56-64 - Edward Raff, Booz Allen Hamilton, Jared Sylvester:
Linear Models with Many Cores and CPUs: A Stochastic Atomic Update Scheme. 65-73 - Dinesh Singh, C. Krishna Mohan:
Projection-SVM: Distributed Kernel Support Vector Machine for Big Data using Subspace Partitioning. 74-83 - Sara Amini, Vahid Noroozi, Sara Bahaadini, Philip S. Yu, Chris Kanich:
DeepFP: A Deep Learning Framework For User Fingerprinting via Mobile Motion Sensors. 84-91 - Dimitris Berberidis, Athanasios N. Nikolakopoulos, Georgios B. Giannakis:
AdaDIF: Adaptive Diffusions for Efficient Semi-supervised Learning over Graphs. 92-99 - Yu-Min Chung, Chuan-Shen Hu, Austin Lawson, Clifford D. Smyth:
Topological approaches to skin disease image analysis. 100-105 - Minh Tuan Doan, Jianzhong Qi, Sutharshan Rajasegarar, Christopher Leckie:
Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data. 106-111 - Shuaijun Ge, Guixiang Ma, Sihong Xie, Philip S. Yu:
Securing Behavior-based Opinion Spam Detection. 112-117 - Mohammad Maminur Islam, Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal:
Scaling up Inference in MLNs with Spark. 118-125 - Dingcheng Li, Jingyuan Zhang, Ping Li:
Representation Learning for Question Classification via Topic Sparse Autoencoder and Entity Embedding. 126-133 - Sha Lu, Lin Liu, Jiuyong Li, Thuc Duy Le:
Effective Outlier Detection based on Bayesian Network and Proximity. 134-139 - Arun Reddy Nelakurthi, Ross Maciejewski, Jingrui He:
Source Free Domain Adaptation Using an Off-the-Shelf Classifier. 140-145 - Michael Nelson, Sridhar Radhakrishnan, Chandra N. Sekharan:
Queryable Compression on Time-Evolving Social Networks with Streaming. 146-151 - Rameshwar Pratap, Raghav Kulkarni, Ishan Sohony:
Efficient Dimensionality Reduction for Sparse Binary Data. 152-157 - Edward Raff, Booz Allen Hamilton, Mark McLean:
Hash-Grams On Many-Cores and Skewed Distributions. 158-165 - Sotiris K. Tasoulis, Aristidis G. Vrahatis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos:
Biomedical Data Ensemble Classification using Random Projections. 166-172 - Fan Yang, Alina Vereshchaka, Wen Dong:
Predicting and Optimizing City-Scale Road Traffic Dynamics Using Trajectories of Individual Vehicles. 173-180 - Liang Bao, Xin Liu, Weizhao Chen:
Learning-based Automatic Parameter Tuning for Big Data Analytics Frameworks. 181-190 - Wenqi Cao, Ling Liu:
Dynamic and Transparent Memory Sharing for Accelerating Big Data Analytics Workloads in Virtualized Cloud. 191-200 - Zhong Chen, Zhide Fang, Jiabin Zhao, Wei Fan, Andrea Edwards, Kun Zhang:
Online Density Estimation over Streaming Data: A Local Adaptive Solution. 201-210 - Bin Dong, Teng Wang, Houjun Tang, Quincey Koziol, Kesheng Wu, Suren Byna:
ARCHIE: Data Analysis Acceleration with Array Caching in Hierarchical Storage. 211-220 - Huadong Feng, Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn:
A Method-Level Test Generation Framework for Debugging Big Data Applications. 221-230 - Michael Kaufmann, Kornilios Kourtis, Adrian Schüpbach, Martina Zitterbart:
Mira: Sharing Resources for Distributed Analytics at Small Timescales. 231-241 - Siyuan Liu, Arijit Khan:
An Empirical Analysis on Expressibility of Vertex Centric Graph Processing Paradigm. 242-251 - Zixia Liu, Hong Zhang, BingBing Rao, Liqiang Wang:
A Reinforcement Learning Based Resource Management Approach for Time-critical Workloads in Distributed Computing Environment. 252-261 - Craig Mustard, Alexandra Fedorova:
Practical Cross Program Memoization with KeyChain. 262-271 - Frank Schoeneman, Jaroslaw Zola:
Scalable Manifold Learning for Big Data with Apache Spark. 272-281 - Takeshi Yoshimura, Tatsuhiro Chiba, Hiroshi Horii:
Column Cache: Buffer Cache for Columnar Storage on HDFS. 282-291 - Yue Cheng, Ali Anwar, Xuejing Duan:
Analyzing Alibaba's Co-located Datacenter Workloads. 292-297 - Vipul Gupta, Shusen Wang, Thomas A. Courtade, Kannan Ramchandran:
OverSketch: Approximate Matrix Multiplication for the Cloud. 298-304 - Dianwei Han, Ankit Agrawal, Wei-keng Liao, Alok N. Choudhary:
Parallel DBSCAN Algorithm Using a Data Partitioning Strategy with Spark Implementation. 305-312 - Sachini Jayasekara, Xunyun Liu, Shanika Karunasekera, Aaron Harwood:
Communication Model for Parallel Iterative Stream Processing. 313-320 - Xiaoyi Lu, Dipti Shankar, Haiyang Shi, Dhabaleswar K. Panda:
Spark-uDAPL: Cost-Saving Big Data Analytics on Microsoft Azure Cloud with RDMA Networks*. 321-326 - Anindya Moitra, Nicholas O. Malott, Philip A. Wilsey:
Cluster-based Data Reduction for Persistent Homology. 327-334 - Md. S. Q. Zulkar Nine, Luigi Di Tacchio, Asif Imran, Tevfik Kosar, Muhammed Fatih Bulut, Jinho Hwang:
GreenDataFlow: Minimizing the Energy Footprint of Global Data Movement. 335-342 - Quanchang Qi, Guangming Lu, Jun Zhang, Lichun Yang, Haishan Liu:
Parallel Large-Scale Neural Network Training For Online Advertising. 343-350 - Maria A. Voinea, Alexandru Uta, Alexandru Iosup:
POSUM: A Portfolio Scheduler for MapReduce Workloads. 351-357 - Sebastian Werner, Jörn Kuhlenkamp, Markus Klems, Johannes Müller, Stefan Tai:
Serverless Big Data Processing using Matrix Multiplication as Example. 358-365 - Po-Yen Wu, Pangfeng Liu, Jan-Jan Wu:
Versatile Communication Optimization for Deep Learning by Modularized Parameter Server. 366-371 - Yanzhao Wu, Wenqi Cao, Semih Sahin, Ling Liu:
Experimental Characterizations and Analysis of Deep Learning Frameworks. 372-377 - Nikos Zacheilas, Dimitris Dedousis, Vana Kalogeraki:
Scalable Distributed Top-k Join Queries in Topic-Based Pub/Sub Systems. 378-383 - Ayman Zeidan, Eemil Lagerspetz, Kai Zhao, Petteri Nurmi, Sasu Tarkoma, Huy T. Vo:
GeoMatch: Efficient Large-Scale Map Matching on Apache Spark. 384-391 - Guoyi Zhao, Lixin Gao, David E. Irwin:
Sync-on-the-fly: A Parallel Framework for Gradient Descent Algorithms on Transient Resources. 392-397 - Chen Zheng, Lei Wang, Sally A. McKee, Lixin Zhang, Hainan Ye, Jianfeng Zhan:
XOS: An Application-Defined Operating System for Datacenter Computing. 398-407 - Kareem S. Aggour, Alex Gittens, Bülent Yener:
Accelerating a Distributed CPD Algorithm for Large Dense, Skewed Tensors. 408-417 - Nikos R. Katsipoulakis, Alexandros Labrinidis, Panos K. Chrysanthis:
Concept-Driven Load Shedding: Reducing Size and Error of Voluminous and Variable Data Streams. 418-427 - Sihuan Li, Sheng Di, Xin Liang, Zizhong Chen, Franck Cappello:
Optimizing Lossy Compression with Adjacent Snapshots for N-body Simulation Data. 428-437 - Xin Liang, Sheng Di, Dingwen Tao, Sihuan Li, Shaomeng Li, Hanqi Guo, Zizhong Chen, Franck Cappello:
Error-Controlled Lossy Compression Optimized for High Compression Ratios of Scientific Datasets. 438-447 - Iouliana Litou, Vana Kalogeraki:
Influence Maximization in Evolving Multi-Campaign Environments. 448-457 - Christian Mayer, Ruben Mayer, Sukanya Bhowmik, Lukas Epple, Kurt Rothermel:
HYPE: Massive Hypergraph Partitioning with Neighborhood Expansion. 458-467 - Daniel Rammer, Walid Budgaga, Thilina Buddhika, Shrideep Pallickara, Sangmi Lee Pallickara:
Alleviating I/O Inefficiencies to Enable Effective Model Training Over Voluminous, High-Dimensional Datasets. 468-477 - Fotis Savva, Christos Anagnostopoulos, Peter Triantafillou:
Explaining Aggregates for Exploratory Analytics. 478-487 - Haipei Sun, Boxiang Dong, Wendy Hui Wang, Ting Yu, Zhan Qin:
Truth Inference on Sparse Crowdsourcing Data with Local Differential Privacy. 488-497 - Chen Yang, Xiaofeng Meng, Zhihui Du:
Cloud based Real-Time and Low Latency Scientific Event Analysis. 498-507 - Debasish Chakroborti, Manishankar Mondal, Banani Roy, Chanchal K. Roy, Kevin A. Schneider:
Optimized Storing of Workflow Outputs through Mining Association Rules. 508-515 - Hsing-bung Chen:
A Universal Namespace Approach to Support Metadata Management and Efficient Data Convergence of HPC and Cloud Scientific Workflows. 516-521 - Nuno Freire, Enno Meijers, Sjors de Valk, René Voorburg, Antoine Isaac, Roland Cornelissen:
Aggregation of Linked Data : A case study in the cultural heritage domain. 522-527 - Konstantinos Giannousis, Konstantina Bereta, Nikolaos Karalis, Manolis Koubarakis:
Distributed Execution of Spatial SQL Queries. 528-533 - J. Kade Gibson, Dongeun Lee, Jaesik Choi, Alex Sim:
Dynamic Online Performance Optimization in Streaming Data Compression. 534-541 - Hamza Mustafa, Eleazar Leal, Le Gruenwald:
FastTopK: A Fast Top-K Trajectory Similarity Query Processing Algorithm for GPUs. 542-547 - Lukas Probst, Fabian Rauschenbach, Heiko Schuldt, Philipp Seidenschwarz, Martin Rumo:
Integrated Real-Time Data Stream Analysis and Sketch-Based Video Retrieval in Team Sports. 548-555 - Zohreh Raghebi, Farnoush Banaei Kashani:
Efficient Processing of Probabilistic Single and Batch Reachability Queries in Large and Evolving Spatiotemporal Contact Networks. 556-561 - Keven Richly:
A Survey on Trajectory Data Management for Hybrid Transactional and Analytical Workloads. 562-569 - Depeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu:
FairGAN: Fairness-aware Generative Adversarial Networks. 570-575 - Vijaya Krishna Yalavarthi, Arijit Khan:
Steering Top-k Influencers in Dynamic Graphs via Local Updates. 576-583 - Uchenna Akujuobi, Ke Sun, Xiangliang Zhang:
Mining top-k Popular Datasets via a Deep Generative Model. 584-593 - Abdullah Alfarrarjeh, Seon Ho Kim, Shivnesh Rajan, Akshay Deshmukh, Cyrus Shahabi:
A Data-Centric Approach for Image Scene Localization. 594-603 - Maroua Bahri, Silviu Maniu, Albert Bifet:
A Sketch-Based Naive Bayes Algorithms for Evolving Data Streams. 604-613 - Christian Beecks, Max Berrendorf:
Optimal k-Nearest-Neighbor Query Processing via Multiple Lower Bound Approximations. 614-623 - Ayan Kumar Bhowmick, G. Sai Bharath Chandra, Yogesh Singh, Bivas Mitra:
Constructing Influence Trees from Temporal Sequence of Retweets: An Analytical Approach. 624-633 - Timo Bingmann, Simon Gog, Florian Kurpicz:
Scalable Construction of Text Indexes with Thrill. 634-643 - Scott Buffett:
Candidate List Maintenance in High Utility Sequential Pattern Mining. 644-652 - Atoshum Cahsai, Christos Anagnostopoulos, Nikos Ntarmos, Peter Triantafillou:
Revisiting Exact kNN Query Processing with Probabilistic Data Space Transformations. 653-662 - Michele Coscia, Luca Rossi:
Benchmarking API Costs of Network Sampling Strategies. 663-672 - Xuan-Hong Dang, Omid Askarisichani, Ambuj K. Singh:
Learning Multiclassifiers with Predictive Features that Vary with Data Distribution. 673-682 - Yasuhiro Fujiwara, Junya Arai, Sekitoshi Kanai, Yasutoshi Ida, Naonori Ueda:
Adaptive Data Pruning for Support Vector Machines. 683-692 - Damien Graux, Louis Jachiet, Pierre Genevès, Nabil Layaïda:
A Multi-Criteria Experimental Ranking of Distributed SPARQL Evaluators. 693-702 - Aparna Joshi, Yu Zhang, Petko Bogdanov, Jeong-Hyon Hwang:
An Efficient System for Subgraph Discovery. 703-712 - Jian Kang, Meijia Wang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong:
AURORA: Auditing PageRank on Large Graphs. 713-722 - R. Uday Kiran, Amulya Kotni, P. Krishna Reddy, Masashi Toyoda, Subhash Bhalla, Masaru Kitsuregawa:
Efficient Discovery of Weighted Frequent Itemsets in Very Large Transactional Databases: A Re-visit. 723-732 - Yuanchun Li, Ziyue Yang, Yao Guo, Xiangqun Chen, Yuvraj Agarwal, Jason I. Hong:
Automated Extraction of Personal Knowledge from Smartphone Push Notifications. 733-742 - Hongfu Liu, Ziming Huang, Qi Chen, Mingqin Li, Yun Fu, Lintao Zhang:
Fast Clustering with Flexible Balance Constraints. 743-750 - Pei-Chi Lo, Ee-Peng Lim:
On Learning Psycholinguistics Tools for English-based Creole Languages using Social Media Data. 751-760 - Panagiotis Nikitopoulos, Aris-Iakovos Paraskevopoulos, Christos Doulkeridis, Nikos Pelekis, Yannis Theodoridis:
Hot Spot Analysis over Big Trajectory Data. 761-770 - Madhavan R. Padmanabhan, Naresh Somisetty, Samik Basu, A. Pavan:
Influence Maximization in Social Networks With Non-Target Constraints. 771-780 - Tilemachos Pechlivanoglou, Manos Papagelis:
Fast and Accurate Mining of Node Importance in Trajectory Networks. 781-790 - Botao Peng, Panagiota Fatourou, Themis Palpanas:
ParIS: The Next Destination for Fast Data Series Indexing and Query Answering. 791-800 - Anh T. Pham, Jing Xi:
Differentially Private Semi-Supervised Learning With Known Class Priors. 801-810 - Xiangnan Ren, Olivier Curé, Hubert Naacke, Guohui Xiao:
BigSR: real-time expressive RDF stream reasoning on modern Big Data platforms. 811-820 - Michal Siedlaczek, Qi Wang, Yen-Yu Chen, Torsten Suel:
Fast Bag-Of-Words Candidate Selection in Content-Based Instance Retrieval Systems. 821-830 - Xiancai Tian, Baihua Zheng:
Using Smart Card Data to Model Commuters' Responses Upon Unexpected Train Delays. 831-840 - Yao Wan, Wenqiang Yan, Jianwei Gao, Zhou Zhao, Jian Wu, Philip S. Yu:
Improved Dynamic Memory Network for Dialogue Act Classification with Adversarial Training. 841-850 - Junxiang Wang, Liang Zhao, Yanfang Ye:
Semi-supervised Multi-instance Interpretable Models for Flu Shot Adverse Event Detection. 851-860 - Shuai Wang, Guangyi Lv, Sahisnu Mazumder, Geli Fei, Bing Liu:
Lifelong Learning Memory Networks for Aspect Sentiment Classification. 861-870 - Jun Wu, Jingrui He, Yongming Liu:
ImVerde: Vertex-Diminished Random Walk for Learning Imbalanced Network Representation. 871-880 - Takahiro Yabe, Kota Tsubouchi, Yoshihide Sekimoto:
Fusion of Terrain Information and Mobile Phone Location Data for Flood Area Detection in Rural Areas. 881-890 - Daniel Yue Zhang, Lanyu Shang, Biao Geng, Shuyue Lai, Ke Li, Hongmin Zhu, Md. Tanvir Al Amin, Dong Wang:
FauxBuster: A Content-free Fauxtography Detector Using Social Media Comments. 891-900 - Daniel Yue Zhang, Lixing Song, Qi Li, Yang Zhang, Dong Wang:
StreamGuard: A Bayesian Network Approach to Copyright Infringement Detection Problem in Large-scale Live Video Sharing Systems. 901-910 - Lei Zheng, Yixue Wang, Lifang He, Sihong Xie, Fengjiao Wang, Philip S. Yu:
PER: A Probabilistic Attentional Model for Personalized Text Recommendations. 911-920 - Zhongfang Zhuang, Xiangnan Kong, Elke A. Rundensteiner, Aditya Arora, Jihane Zouaoui:
One-Shot Learning on Attributed Sequences. 921-930 - Ebad Ahmadzadeh, Philip K. Chan:
Identifying Pros and Cons of Product Aspects Based on Customer Reviews. 931-936 - Basmah Altaf, Lu Yu, Xiangliang Zhang:
Spatio-Temporal Attention based Recurrent Neural Network for Next Location Prediction. 937-942 - Soudabeh Barghi, Lalet Scaria, Ali Salari, Tristan Glatard:
Predicting computational reproducibility of data analysis pipelines in large population studies using collaborative filtering. 943-950 - Edmon Begoli, Kris Brown, Sudarshan Srinivas, Suzanne Tamang:
SynthNotes: A Generator Framework for High-volume, High-fidelity Synthetic Mental Health Notes. 951-958 - Sreyasee Das Bhattacharjee, William J. Tolone, Mohammed Elshambakey, Isaac Cho, Ashish Mahabal, S. George Djorgovski:
Context-Aware Deep Sequence Learning with Multi-View Factor Pooling for Time Series Classification. 959-966