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ORCIDBigData Conference 2017: Boston, MA, USA
- Jian-Yun Nie, Zoran Obradovic, Toyotaro Suzumura, Rumi Ghosh, Raghunath Nambiar, Chonggang Wang, Hui Zang, Ricardo Baeza-Yates, Xiaohua Hu, Jeremy Kepner, Alfredo Cuzzocrea, Jian Tang, Masashi Toyoda:
2017 IEEE International Conference on Big Data, BigData 2017, Boston, MA, USA, December 11-14, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-2715-0 - Carla E. Brodley:
Human-in-the-loop applied machine learning. 1 - Alan Edelman:
A more open efficient future for AI development and data science with an introduction to Julia. 2 - John Langford:
Contextual reinforcement learning. 3 - Jure Leskovec:
Large-scale graph representation learning. 4 - Satoshi Matsuoka:
Being "BYTES-oriented" in HPC leads to an open big data/AI ecosystem and further advances into the post-moore era. 5 - ChengXiang Zhai:
TextScope: Enhance human perception via text mining. 6 - Feng Chen, Chunpai Wang, Jin-Hee Cho:
Collective subjective logic: Scalable uncertainty-based opinion inference. 7-16 - Natascha Harth
, Christos Anagnostopoulos:
Quality-aware aggregation & predictive analytics at the edge. 17-26 - Sheng Li, Yun Fu:
Robust multi-label semi-supervised classification. 27-36 - Xiaoli Li, Sai Nivedita Chandrasekaran, Jun Huan:
Lifelong multi-task multi-view learning using latent spaces. 37-46 - Natalia Ponomareva, Thomas Colthurst, Gilbert Hendry, Salem Haykal, Soroush Radpour:
Compact multi-class boosted trees. 47-56 - Daniel Yue Zhang, Dong Wang, Yang Zhang:
Constraint-aware dynamic truth discovery in big data social media sensing. 57-66 - Peter Baumann:
Standardizing big earth datacubes. 67-73 - Salima Benbernou, Mourad Ouziri:
Enhancing data quality by cleaning inconsistent big RDF data. 74-79 - Byron J. Gao, Robert Tung, Yong Yang:
Iterative matrix correlation for bisection clustering. 80-87 - Diego Granziol, Stephen J. Roberts:
Entropic determinants of massive matrices. 88-93 - Er-Chen Huang, Hsing-Kuo Pao, Yuh-Jye Lee:
Big active learning. 94-101 - Hasan Kurban, Mehmet M. Dalkilic:
A novel approach to optimization of iterative machine learning algorithms: Over heap structure. 102-109 - Sheng Li, Hongfu Liu, Zhiqiang Tao, Yun Fu:
Multi-view graph learning with adaptive label propagation. 110-115 - Christian S. Schmid, Bruce A. Desmarais:
Exponential random graph models with big networks: Maximum pseudolikelihood estimation and the parametric bootstrap. 116-121 - Sam Wood, Rohit Muthyala, Yi Jin, Yixing Qin, Nilaj Rukadikar, Amit Rai, Hua Gao:
Automated industry classification with deep learning. 122-129 - Jonghyun Bae, Hakbeom Jang, Wenjing Jin, Jun Heo, Jaeyoung Jang, Joo Young Hwang, Sangyeun Cho, Jae W. Lee:
Jointly optimizing task granularity and concurrency for in-memory mapreduce frameworks. 130-140 - Nathanael Cheriere, Gabriel Antoniu:
How fast can one scale down a distributed file system? 141-150 - Thomas Swearingen, Will Drevo, Bennett Cyphers, Alfredo Cuesta-Infante, Arun Ross, Kalyan Veeramachaneni:
ATM: A distributed, collaborative, scalable system for automated machine learning. 151-162 - Ioannis Giannakopoulos, Dimitrios Tsoumakos, Nectarios Koziris:
A decision tree based approach towards adaptive modeling of big data applications. 163-172 - Shashank Gugnani, Xiaoyi Lu, Houliang Qi, Li Zha, Dhabaleswar K. Panda:
Characterizing and accelerating indexing techniques on distributed ordered tables. 173-182 - Yuki Ito, Ryo Matsumiya, Toshio Endo:
ooc_cuDNN: Accommodating convolutional neural networks over GPU memory capacity. 183-192 - HyeongSik Kim, Padmashree Ravindra, Kemafor Anyanwu:
A semantics-aware storage framework for scalable processing of knowledge graphs on Hadoop. 193-202 - Konstantinos Lolos, Ioannis Konstantinou, Verena Kantere, Nectarios Koziris:
Elastic management of cloud applications using adaptive reinforcement learning. 203-212 - Xiaoyi Lu, Haiyang Shi, Dipti Shankar, Dhabaleswar K. Panda:
Performance characterization and acceleration of big data workloads on OpenPOWER system. 213-222 - Diego Marron, Eduard Ayguadé, José R. Herrero, Jesse Read, Albert Bifet:
Low-latency multi-threaded ensemble learning for dynamic big data streams. 223-232 - Arnab Kumar Paul, Arpit Goyal, Feiyi Wang, Sarp Oral, Ali Raza Butt, Michael J. Brim, Sangeetha B. Srinivasa:
I/O load balancing for big data HPC applications. 233-242 - Bo Peng, Bingjing Zhang, Langshi Chen, Mihai Avram, Robert Henschel, Craig A. Stewart, Shaojuan Zhu, Emily McCallum, Lisa Smith, Tom Zahniser, Jon Omer, Judy Qiu:
HarpLDA+: Optimizing latent dirichlet allocation for parallel efficiency. 243-252 - Jim Pivarski, Peter Elmer, Brian Bockelman, Zhe Zhang:
Fast access to columnar, hierarchically nested data via code transformation. 253-262 - Alex Watson, Deepigha Shree Vittal Babu, Suprio Ray:
Sanzu: A data science benchmark. 263-272 - Luna Xu, Seung-Hwan Lim, Min Li, Ali Raza Butt, Ramakrishnan Kannan:
Scaling up data-parallel analytics platforms: Linear algebraic operation cases. 273-282 - Xiaodong Yu, Kaixi Hou, Hao Wang, Wu-chun Feng:
Robotomata: A framework for approximate pattern matching of big data on an automata processor. 283-292 - Yunming Zhang, Vladimir Kiriansky, Charith Mendis, Saman P. Amarasinghe, Matei Zaharia:
Making caches work for graph analytics. 293-302 - Bilal Akil, Ying Zhou, Uwe Röhm:
On the usability of Hadoop MapReduce, Apache Spark & Apache flink for data science. 303-310 - Mohammed Alawad, Hong-Jun Yoon, Georgia D. Tourassi:
Energy efficient stochastic-based deep spiking neural networks for sparse datasets. 311-318 - Lars Arge, Mathias Rav, Svend C. Svendsen, Jakob Truelsen:
External memory pipelining made easy with TPIE. 319-324 - Dapeng Dong, John Herbert:
Compressed domain-specific data processing and analysis. 325-330 - Celestine Dünner, Thomas P. Parnell, Kubilay Atasu, Manolis Sifalakis, Haralampos Pozidis:
Understanding and optimizing the performance of distributed machine learning applications on apache spark. 331-338 - Xiao Meng, Lukasz Golab:
Optimal reducer placement to minimize data transfer in MapReduce-style processing. 339-346 - Michael Mercier, David Glesser, Yiannis Georgiou, Olivier Richard:
Big data and HPC collocation: Using HPC idle resources for Big Data analytics. 347-352 - Axel Oehmichen, Florian Guitton, Kai Sun, Jean Grizet, Thomas Heinis, Yike Guo:
eTRIKS analytical environment: A modular high performance framework for medical data analysis. 353-360 - Ilia Pietri, Yannis Chronis, Yannis E. Ioannidis:
Multi-objective optimization of scheduling dataflows on heterogeneous cloud resources. 361-368 - Md. Wasi-ur-Rahman, Nusrat Sharmin Islam, Xiaoyi Lu, Dhabaleswar K. Panda:
NVMD: Non-volatile memory assisted design for accelerating MapReduce and DAG execution frameworks on HPC systems. 369-374 - Xinhui Tian, Yuanqing Guo, Jianfeng Zhan, Lei Wang:
Towards memory and computation efficient graph processing on spark. 375-382 - Alexander Ulanov, Manish Marwah, Mijung Kim, Roshan Dathathri, Carlos Zubieta, Jun Li:
Sandpiper: Scaling probabilistic inferencing to large scale graphical models. 383-388 - Nikos Zacheilas, Stathis Maroulis, Vana Kalogeraki:
Dione: Profiling spark applications exploiting graph similarity. 389-394 - Mohammad Asghari, Cyrus Shahabi:
On on-line task assignment in spatial crowdsourcing. 395-404 - Ilir Fetai, Alexander Stiemer, Heiko Schuldt:
QuAD: A quorum protocol for adaptive data management in the cloud. 405-414 - Valérie Hayot-Sasson, Yongping Gao, Yuhong Yan, Tristan Glatard:
Sequential algorithms to split and merge ultra-high resolution 3D images. 415-424 - Shahab Helmi, Farnoush Banaei Kashani:
Spatiotemporal range pattern queries on large-scale co-movement pattern datasets. 425-434 - Srinivasan Venkatramanan, Sichao Wu, Bowen Shi, Achla Marathe, Madhav Marathe, Stephen G. Eubank, Lalit P. Sah, A. P. Giri, Luke A. Colavito, K. S. Nitin, V. Sridhar, R. Asokan, Rangaswamy Muniappan, G. Norton, Abhijin Adiga:
Towards robust models of food flows and their role in invasive species spread. 435-444 - Juan A. Colmenares, Reza Dorrigiv, Daniel G. Waddington:
A single-node datastore for high-velocity multidimensional sensor data. 445-452 - Isabelle Comyn-Wattiau, Jacky Akoka:
Model driven reverse engineering of NoSQL property graph databases: The case of Neo4j. 453-458 - Helge Holzmann, Vinay Goel, Emily Novak Gustainis:
Universal distant reading through metadata proxies with archivespark. 459-464 - Md. S. Q. Zulkar Nine, Kemal Guner, Ziyun Huang, Xiangyu Wang, Jinhui Xu, Tevfik Kosar:
Big data transfer optimization based on offline knowledge discovery and adaptive sampling. 465-472 - Ramyar Saeedi, Skyler Norgaard, Assefaw Hadish Gebremedhin:
A closed-loop deep learning architecture for robust activity recognition using wearable sensors. 473-479 - Haiying Shen, Heng Zhou:
CStorage: An efficient classification-based image storage system in cloud datacenters. 480-485 - Dingwen Tao, Sheng Di, Zizhong Chen, Franck Cappello:
In-depth exploration of single-snapshot lossy compression techniques for N-body simulations. 486-493 - Xian Wu, Yuxiao Dong, Jun Tao, Chao Huang, Nitesh V. Chawla:
Reliable fake review detection via modeling temporal and behavioral patterns. 494-499 - Masahiro Yokoyama, Takahiro Hara, Sanjay Kumar Madria:
Efficient diversified set monitoring for mobile sensor stream environments. 500-507 - Yangwen Yu, James Jian Qiao Yu, Victor O. K. Li, Jacqueline C. K. Lam:
Low-rank singular value thresholding for recovering missing air quality data. 508-513 - Lina Yu, Michael L. Rilee, Yu Pan, Feiyu Zhu, Kwo-Sen Kuo, Hongfeng Yu:
Visual analytics with unparalleled variety scaling for big earth data. 514-521 - Ming Zeng, Tong Yu, Xiao Wang, Le T. Nguyen, Ole J. Mengshoel, Ian R. Lane:
Semi-supervised convolutional neural networks for human activity recognition. 522-529 - Xibo Zhou, Ye Ding, Fengchao Peng, Qiong Luo, Lionel M. Ni:
Detecting unmetered taxi rides from trajectory data. 530-535 - Giambattista Amati, Simone Angelini, Giorgio Gambosi, Gianluca Rossi, Paola Vocca:
Estimation of distance-based metrics for very large graphs with MinHash Signatures. 536-545 - Philipp Baumann, Dorit S. Hochbaum, Quico Spaen:
High-performance geometric algorithms for sparse computation in big data analytics. 546-555 - Sreyasee Das Bhattacharjee, Ashit Talukder, Bala Venkatram Balantrapu:
Active learning based news veracity detection with feature weighting and deep-shallow fusion. 556-565 - Chandramani Chaudhary, Poonam Goyal, Yi-Ping Phoebe Chen:
Exploiting visual and textual neighborhood information to improve image-tag relevance. 566-575 - Limeng Cui, Jiawei Zhang, Zhensong Chen, Yong Shi, Philip S. Yu:
Inverse extreme learning machine for learning with label proportions. 576-585 - Vachik S. Dave, Nesreen K. Ahmed, Mohammad Al Hasan:
E-CLoG: Counting edge-centric local graphlets. 586-595 - Bo Dong, Yifan Li, Yang Gao, Ahsanul Haque, Latifur Khan, Mohammad M. Masud:
Multistream regression with asynchronous concept drift detection. 596-605 - Roohollah Etemadi, Jianguo Lu:
Bias correction in clustering coefficient estimation. 606-615 - Guyue Han, Harish Sethu:
Closed walk sampler: An efficient method for estimating the spectral radius of large graphs. 616-625 - Jun Hu, Yuxin Wang, Ping Li:
Online city-scale hyper-local event detection via analysis of social media and human mobility. 626-635 - Jianfeng Jia, Chen Li, Michael J. Carey:
Drum: A rhythmic approach to interactive analytics on large data. 636-645 - Ryoya Kaneko, Kohei Miyaguchi, Kenji Yamanishi:
Detecting changes in streaming data with information-theoretic windowing. 646-655 - Foteini Katsarou, Nikos Ntarmos, Peter Triantafillou:
Hybrid algorithms for subgraph pattern queries in graph databases. 656-665 - Sarasi Lalithsena, Sujan Perera, Pavan Kapanipathi, Amit P. Sheth:
Domain-specific hierarchical subgraph extraction: A recommendation use case. 666-675 - Panagiotis Liakos, Alexandros Ntoulas, Alex Delis:
COEUS: Community detection via seed-set expansion on graph streams. 676-685 - Panagiotis Liakos, Alexandros Ntoulas, Alex Delis:
Rhea: Adaptively sampling authoritative content from social activity streams. 686-695 - Ismini Lourentzou, Alex Morales, ChengXiang Zhai:
Text-based geolocation prediction of social media users with neural networks. 696-705 - Alessandro Lulli, Luca Oneto, Davide Anguita:
Crack random forest for arbitrary large datasets. 706-715 - Suchismit Mahapatra, Varun Chandola:
S-Isomap++: Multi manifold learning from streaming data. 716-725 - Sheikh Motahar Naim, Arnold P. Boedihardjo, Mahmud Shahriar Hossain:
A scalable model for tracking topical evolution in large document collections. 726-735 - Mehrnaz Najafi, Lifang He, Philip S. Yu:
Error-robust multi-view clustering. 736-745 - Axel-Cyrille Ngonga Ngomo, Michael Hoffmann, Ricardo Usbeck, Kunal Jha:
Holistic and scalable ranking of RDF data. 746-755 - Haekyu Park, Jinhong Jung, U Kang:
A comparative study of matrix factorization and random walk with restart in recommender systems. 756-765 - Chao Shang, Aaron Palmer, Jiangwen Sun, Ko-Shin Chen, Jin Lu, Jinbo Bi:
VIGAN: Missing view imputation with generative adversarial networks. 766-775 - Lorenzo De Stefani, Erisa Terolli, Eli Upfal:
Tiered sampling: An efficient method for approximate counting sparse motifs in massive graph streams. 776-786 - Cheng-Chin Tu, Mi-Yen Yeh, Tei-Wei Kuo:
A fast non-volatile memory aware algorithm for generating random scale-free networks. 787-796 - Nguyen Vo, Kyumin Lee, Thanh Tran:
MRAttractor: Detecting communities from large-scale graphs. 797-806 - Yueyao Wang, Qinmin Hu, Yang Song, Liang He:
Potentiality of healthcare big data: Improving search by automatic query reformulation. 807-816 - Ichitaro Yamazaki, Stanimire Tomov, Jack J. Dongarra:
Sampling algorithms to update truncated SVD. 817-826 - Yizhou Yan, Lei Cao, Elke A. Rundensteiner:
Distributed Top-N local outlier detection in big data. 827-836 - Tong Yang, Binchao Yin, Hang Li, Muhammad Shahzad, Steve Uhlig, Bin Cm, Xiaoming Li:
Rectangular hash table: Bloom filter and bitmap assisted hash table with high speed. 837-846 - Xinli Yu, Zheng Chen, Wei-Shih Yang, Xiaohua Hu, Erjia Yan, Guangrong Li:
Large-scale joint topic, sentiment & user preference analysis for online reviews. 847-856 - Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla:
ImWalkMF: Joint matrix factorization and implicit walk integrative learning for recommendation. 857-866 - Lei Zheng, Bokai Cao, Vahid Noroozi, Philip S. Yu, Nianzu Ma:
Hierarchical collaborative embedding for context-aware recommendations. 867-876 - Ebad Ahmadzadeh, Philip K. Chan:
Mining pros and cons of actions from social media for decision support. 877-882 - Masato Asahara, Ryohei Fujimaki:
Distributed Bayesian piecewise sparse linear models. 883-888 - Kubilay Atasu, Thomas P. Parnell, Celestine Dünner, Manolis Sifalakis, Haralampos Pozidis, Vasileios Vasileiadis, Michail Vlachos, Cesar Berrospi, Abdel Labbi:
Linear-complexity relaxed word Mover's distance with GPU acceleration. 889-896 - Ricardo Baeza-Yates, Zeinab Liaghat:
Quality-efficiency trade-offs in machine learning for text processing. 897-904 - Jose Cadena, Saliya Ekanayake, Anil Vullikanti:
Fast graph scan statistics optimization using algebraic fingerprints. 905-910 - Zaineb Chelly Dagdia, Christine Zarges, Gaël Beck, Mustapha Lebbah:
A distributed rough set theory based algorithm for an efficient big data pre-processing under the spark framework. 911-916 - Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Eamonn J. Keogh:
Judicious setting of Dynamic Time Warping's window width allows more accurate classification of time series. 917-922 - Alexander Denzler, Michael Kaufmann:
Toward granular knowledge analytics for data intelligence: Extracting granular entity-relationship graphs for knowledge profiling. 923-928 - Ankit Desai, Sanjay Chaudhary:
Distributed decision tree v.2.0. 929-934 - Mohammad M. Ghassemi, Willow Jarvis, Tuka Alhanai, Emery N. Brown, Roger G. Mark, M. Brandon Westover:
An open-source tool for the transcription of paper-spreadsheet data: Code and supplemental materials available online: Https: //github.com/deskool/images to spreadsheets. 935-941 - Poonam Goyal, Jagat Sesh Challa, Shivin Shrivastava, Navneet Goyal:
AnyFI: An anytime frequent itemset mining algorithm for data streams. 942-947 - Tatsuru Kobayashi, Shin Matsushima, Taito Lee, Kenji Yamanishi:
Discovering potential traffic risks in Japan using a supervised learning approach. 948-955 - Martin Koehler, Alex Bogatu, Cristina Civili, Nikolaos Konstantinou, Edward Abel, Alvaro A. A. Fernandes, John A. Keane, Leonid Libkin, Norman W. Paton:
Data context informed data wrangling. 956-963 - Naama Kraus, David Carmel, Idit Keidar:
Fishing in the stream: Similarity search over endless data. 964-969 - Liang Ma, Guohong Cao, Lance M. Kaplan:
Graphical approach for influence maximization in social networks under generic threshold-based non-submodular model. 970-975 - Aritra Mandal, Mohammad Al Hasan:
A distributed k-core decomposition algorithm on spark. 976-981 - Mohammad Hossein Namaki, Peng Lin, Yinghui Wu:
Event pattern discovery by keywords in graph streams. 982-987 - Michael Nelson, Sridhar Radhakrishnan, Amlan Chatterjee, Chandra N. Sekharan:
Queryable compression on streaming social networks. 988-993 - Fengchao Peng, Yudian Ji, Qiong Luo, Lionel M. Ni:
Event-based non-parametric clustering of team sport trajectories. 994-999 - Sumit Purohit, Sutanay Choudhury, Lawrence B. Holder:
Application-specific graph sampling for frequent subgraph mining and community detection. 1000-1005 - Hung Tran-The, Koji Zettsu:
Discovering co-occurrence patterns of heterogeneous events from unevenly-distributed spatiotemporal data. 1006-1011 - Takeaki Uno, Hiroki Maegawa, Takanobu Nakahara, Yukinobu Hamuro, Ryo Yoshinaka, Makoto Tatsuta:
Micro-clustering by data polishing. 1012-1018