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20th KDD 2014: New York City, USA
- Sofus A. Macskassy, Claudia Perlich, Jure Leskovec, Wei Wang, Rayid Ghani:
The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '14, New York, NY, USA - August 24 - 27, 2014. ACM 2014, ISBN 978-1-4503-2956-9
Keynote talks
- Oren Etzioni:
The battle for the future of data mining. 1 - Eric Horvitz:
Data, predictions, and decisions in support of people and society. 2 - Eric E. Schadt:
A data driven approach to diagnosing and treating disease. 3 - Sendhil Mullainathan:
Bugbears or legitimate threats?: (social) scientists' criticisms of machine learning? 4
Research session 1: location-based services
- Xuan Song
, Quanshi Zhang, Yoshihide Sekimoto, Ryosuke Shibasaki:
Prediction of human emergency behavior and their mobility following large-scale disaster. 5-14 - Yuxiao Dong, Yang Yang, Jie Tang, Yang Yang, Nitesh V. Chawla
Inferring user demographics and social strategies in mobile social networks. 15-24 - Yilun Wang, Yu Zheng, Yexiang Xue:
Travel time estimation of a path using sparse trajectories. 25-34 - Moshe Lichman, Padhraic Smyth
Modeling human location data with mixtures of kernel densities. 35-44 - Meng Qu, Hengshu Zhu
A cost-effective recommender system for taxi drivers. 45-54
Research session 2: applications to healthcare and medicine I
- Yubin Park, Joydeep Ghosh:
LUDIA: an aggregate-constrained low-rank reconstruction algorithm to leverage publicly released health data. 55-64 - Subhabrata Mukherjee, Gerhard Weikum, Cristian Danescu-Niculescu-Mizil:
People on drugs: credibility of user statements in health communities. 65-74 - Marzyeh Ghassemi, Tristan Naumann
Unfolding physiological state: mortality modelling in intensive care units. 75-84 - Xiang Wang, David A. Sontag, Fei Wang:
Unsupervised learning of disease progression models. 85-94 - Evangelos E. Papalexakis
Good-enough brain model: challenges, algorithms and discoveries in multi-subject experiments. 95-104
Research session 3: applications to healthcare and medicine II
- Yasuko Matsubara, Yasushi Sakurai, Willem G. van Panhuis
FUNNEL: automatic mining of spatially coevolving epidemics. 105-114 - Joyce C. Ho, Joydeep Ghosh, Jimeng Sun
Marble: high-throughput phenotyping from electronic health records via sparse nonnegative tensor factorization. 115-124 - Chih-Chun Chia, Zeeshan Syed:
Scalable noise mining in long-term electrocardiographic time-series to predict death following heart attacks. 125-134 - Jiayu Zhou, Fei Wang, Jianying Hu, Jieping Ye:
From micro to macro: data driven phenotyping by densification of longitudinal electronic medical records. 135-144 - Fei Wang, Ping Zhang
Clinical risk prediction with multilinear sparse logistic regression. 145-154 - James C. Ross, Peter J. Castaldi, Michael H. Cho, Jennifer G. Dy:
Dual beta process priors for latent cluster discovery in chronic obstructive pulmonary disease. 155-162
Research session 4: recommender systems
- Quan Yuan, Gao Cong
COM: a generative model for group recommendation. 163-172 - Laurent Charlin, Richard S. Zemel, Hugo Larochelle:
Leveraging user libraries to bootstrap collaborative filtering. 173-182 - Yupeng Gu, Yizhou Sun, Ning Jiang, Bingyu Wang, Ting Chen:
Topic-factorized ideal point estimation model for legislative voting network. 183-192 - Qiming Diao, Minghui Qiu, Chao-Yuan Wu, Alexander J. Smola, Jing Jiang, Chong Wang:
Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS). 193-202 - Mahbub Hasan, Abhijith Kashyap, Vagelis Hristidis
User effort minimization through adaptive diversification. 203-212
Research session 5: clustering
- Xiao He, Jing Feng, Bettina Konte, Son T. Mai, Claudia Plant
Relevant overlapping subspace clusters on categorical data. 213-222 - Murat Dundar, Halid Ziya Yerebakan, Bartek Rajwa
Batch discovery of recurring rare classes toward identifying anomalous samples. 223-232 - Jianhua Yin
A dirichlet multinomial mixture model-based approach for short text clustering. 233-242 - Andreas Züfle, Tobias Emrich, Klaus Arthur Schmid, Nikos Mamoulis, Arthur Zimek
Representative clustering of uncertain data. 243-252 - Stephan Günnemann, Ines Färber, Matthias Sebastian Rüdiger
SMVC: semi-supervised multi-view clustering in subspace projections. 253-262
Research session 6: supervised learning I
- Yashoteja Prabhu, Manik Varma:
FastXML: a fast, accurate and stable tree-classifier for extreme multi-label learning. 263-272 - Shaodan Zhai, Tian Xia, Shaojun Wang:
A multi-class boosting method with direct optimization. 273-282 - Yashu Liu, Jie Wang, Jieping Ye:
An efficient algorithm for weak hierarchical lasso. 283-292 - Doyen Sahoo, Steven C. H. Hoi
Online multiple kernel regression. 293-302 - Sihong Xie, Jing Gao, Wei Fan, Deepak S. Turaga, Philip S. Yu:
Class-distribution regularized consensus maximization for alleviating overfitting in model combination. 303-312
Research session 7: supervised learning II
- Teng Zhang, Zhi-Hua Zhou:
Large margin distribution machine. 313-322 - Qi Qian, Juhua Hu, Rong Jin, Jian Pei
Distance metric learning using dropout: a structured regularization approach. 323-332 - Siong Thye Goh
Box drawings for learning with imbalanced data. 333-342 - Cheng-Hao Tsai, Chieh-Yen Lin, Chih-Jen Lin:
Incremental and decremental training for linear classification. 343-352 - Junbo Zhang, Guangjian Tian, Yadong Mu, Wei Fan:
Supervised deep learning with auxiliary networks. 353-361
Research session 8: trend, anomaly and novelty detection
- Tahereh Babaie, Sanjay Chawla, Romesh G. Abeysuriya
Sleep analytics and online selective anomaly detection. 362-371 - Qi Rose Yu, Xinran He, Yan Liu:
GLAD: group anomaly detection in social media analysis. 372-381 - Dehua Cheng, Mohammad Taha Bahadori, Yan Liu:
FBLG: a simple and effective approach for temporal dependence discovery from time series data. 382-391 - Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme
Learning time-series shapelets. 392-401 - Mohamed F. Ghalwash
Utilizing temporal patterns for estimating uncertainty in interpretable early decision making. 402-411
Research session 9: data streams
- Junming Shao, Zahra Ahmadi
Prototype-based learning on concept-drifting data streams. 412-421 - Yanwei Yu, Lei Cao
Detecting moving object outliers in massive-scale trajectory streams. 422-431 - Charu C. Aggarwal:
The setwise stream classification problem. 432-441 - Daniel Ting:
Streamed approximate counting of distinct elements: beating optimal batch methods. 442-451 - Andrew S. Lan, Christoph Studer, Richard G. Baraniuk:
Time-varying learning and content analytics via sparse factor analysis. 452-461
Research session 10: active learning
- Dan Kushnir:
Active-transductive learning with label-adapted kernels. 462-471 - Deepak Vasisht, Andreas C. Damianou, Manik Varma, Ashish Kapoor:
Active learning for sparse bayesian multilabel classification. 472-481 - De Wang, Feiping Nie, Heng Huang:
Large-scale adaptive semi-supervised learning via unified inductive and transductive model. 482-491 - Akshay Gadde, Aamir Anis, Antonio Ortega:
Active semi-supervised learning using sampling theory for graph signals. 492-501 - Jialei Wang, Nathan Srebro, James Evans:
Active collaborative permutation learning. 502-511
Research session 11: feature selection
- Xuan Vinh Nguyen
Effective global approaches for mutual information based feature selection. 512-521 - Zhixiang Eddie Xu, Gao Huang, Kilian Q. Weinberger, Alice X. Zheng:
Gradient boosted feature selection. 522-531 - Shuo Xiang, Tao Yang, Jieping Ye:
Simultaneous feature and feature group selection through hard thresholding. 532-541 - Zheng Zhao, Jun Liu, James Cox:
Safe and efficient screening for sparse support vector machine. 542-551 - Sanjay Purushotham, Martin Renqiang Min
Factorized sparse learning models with interpretable high order feature interactions. 552-561
Research session 12: statistical techniques for big data
- Dehua Cheng, Yan Liu:
Parallel gibbs sampling for hierarchical dirichlet processes via gamma processes equivalence. 562-571 - Tamraparni Dasu, Ji Meng Loh, Divesh Srivastava:
Empirical glitch explanations. 572-581 - Hongxia Yang, Jingrui He:
Learning with dual heterogeneity: a nonparametric bayes model. 582-590 - Chien-Liang Liu
Online chinese restaurant process. 591-600 - Xin Dong, Evgeniy Gabrilovich
Knowledge vault: a web-scale approach to probabilistic knowledge fusion. 601-610
Research session 13: scaling-up methods for big data
- Shusen Wang
Improving the modified nyström method using spectral shifting. 611-620 - Wenlin Chen, Yixin Chen, Kilian Q. Weinberger:
Fast flux discriminant for large-scale sparse nonlinear classification. 621-630 - Mingwang Tang, Feifei Li:
Scalable histograms on large probabilistic data. 631-640 - Flavio Chierichetti, Nilesh N. Dalvi, Ravi Kumar:
Correlation clustering in MapReduce. 641-650 - Christos Anagnostopoulos
Scaling out big data missing value imputations: pythia vs. godzilla. 651-660
Research session 14: large-scale optimization and learning
- Mu Li, Tong Zhang, Yuqiang Chen, Alexander J. Smola:
Efficient mini-batch training for stochastic optimization. 661-670 - Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause:
Streaming submodular maximization: massive data summarization on the fly. 671-680 - Edith Cohen:
Distance queries from sampled data: accurate and efficient. 681-690 - Yi Li
Improved testing of low rank matrices. 691-700 - Bryan Perozzi, Rami Al-Rfou, Steven Skiena:
DeepWalk: online learning of social representations. 701-710
Research session 15: web mining
- Sunita Sarawagi, Soumen Chakrabarti:
Open-domain quantity queries on web tables: annotation, response, and consensus models. 711-720 - Bin Wu, Erheng Zhong, Ben Tan, Andrew Horner, Qiang Yang:
Crowdsourced time-sync video tagging using temporal and personalized topic modeling. 721-730 - Liangda Li, Hongbo Deng, Anlei Dong, Yi Chang
Identifying and labeling search tasks via query-based hawkes processes. 731-740 - Oleksandr Polozov
LaSEWeb: automating search strategies over semi-structured web data. 741-750 - Shangsong Liang, Zhaochun Ren, Maarten de Rijke
Personalized search result diversification via structured learning. 751-760
Research session 16: transfer learning
- Pinghua Gong, Jiayu Zhou, Wei Fan, Jieping Ye:
Efficient multi-task feature learning with calibration. 761-770 - Tianyi Zhou
Multi-task copula by sparse graph regression. 771-780 - Mianwei Zhou, Kevin Chen-Chuan Chang:
Unifying learning to rank and domain adaptation: enabling cross-task document scoring. 781-790 - Ying Wei
Scalable heterogeneous translated hashing. 791-800 - Chung-Yi Li, Shou-De Lin
Matching users and items across domains to improve the recommendation quality. 801-810
Research session 17: recommendations and ratings
- Wei Lu, Stratis Ioannidis
Optimal recommendations under attraction, aversion, and social influence. 811-820 - Xiang Ren, Jialu Liu, Xiao Yu, Urvashi Khandelwal, Quanquan Gu, Lidan Wang, Jiawei Han:
ClusCite: effective citation recommendation by information network-based clustering. 821-830 - Defu Lian
GeoMF: joint geographical modeling and matrix factorization for point-of-interest recommendation. 831-840 - Stephan Günnemann, Nikou Günnemann, Christos Faloutsos
Detecting anomalies in dynamic rating data: a robust probabilistic model for rating evolution. 841-850 - Silei Xu, John Chi-Shing Lui:
Product selection problem: improve market share by learning consumer behavior. 851-860
Research session 18: topic modeling
- Yongxin Tong
TCS: efficient topic discovery over crowd-oriented service data. 861-870 - Erich Schubert
SigniTrend: scalable detection of emerging topics in textual streams by hashed significance thresholds. 871-880 - Wray L. Buntine
Experiments with non-parametric topic models. 881-890 - Aaron Q. Li, Amr Ahmed, Sujith Ravi, Alexander J. Smola:
Reducing the sampling complexity of topic models. 891-900 - Mikalai Tsytsarau, Themis Palpanas, Malú Castellanos:
Dynamics of news events and social media reaction. 901-910
Research session 19: security and privacy
- Qian Xiao
Differentially private network data release via structural inference. 911-920 - Wentian Lu, Gerome Miklau:
Exponential random graph estimation under differential privacy. 921-930 - Jaewoo Lee, Christopher W. Clifton:
Top-k frequent itemsets via differentially private FP-trees. 931-940 - Meng Jiang
CatchSync: catching synchronized behavior in large directed graphs. 941-950 - Hengshu Zhu
Mobile app recommendations with security and privacy awareness. 951-960
Research session 20: dimensionality reduction
- Xiaomin Fang
Fast DTT: a near linear algorithm for decomposing a tensor into factor tensors. 967-976 - Feiping Nie, Xiaoqian Wang, Heng Huang:
Clustering and projected clustering with adaptive neighbors. 977-986 - Xilun Chen, K. Selçuk Candan:
LWI-SVD: low-rank, windowed, incremental singular value decompositions on time-evolving data sets. 987-996 - Dimitris S. Papailiopoulos, Anastasios Kyrillidis, Christos Boutsidis:
Provable deterministic leverage score sampling. 997-1006 - Tuan M. V. Le, Hady Wirawan Lauw
Semantic visualization for spherical representation. 1007-1016
Research session 21: novel applications
- Rakesh Agrawal, Behzad Golshan, Evimaria Terzi:
Grouping students in educational settings. 1017-1026 - Jingbo Shang, Yu Zheng, Wenzhu Tong, Eric Chang, Yong Yu:
Inferring gas consumption and pollution emission of vehicles throughout a city. 1027-1036 - Karthik Raman, Thorsten Joachims:
Methods for ordinal peer grading. 1037-1046 - Yanjie Fu, Hui Xiong, Yong Ge, Zijun Yao, Yu Zheng, Zhi-Hua Zhou:
Exploiting geographic dependencies for real estate appraisal: a mutual perspective of ranking and clustering. 1047-1056 - Bo Zong, Yinghui Wu, Jie Song, Ambuj K. Singh, Hasan Çam, Jiawei Han, Xifeng Yan:
Towards scalable critical alert mining. 1057-1066
Research session 22: crowds and markets
- Caleb Chen Cao, Lei Chen
From labor to trader: opinion elicitation via online crowds as a market. 1067-1076 - Weinan Zhang, Shuai Yuan, Jun Wang:
Optimal real-time bidding for display advertising. 1077-1086 - Ting Wang, Dashun Wang
Quantifying herding effects in crowd wisdom. 1087-1096 - Olivier Chapelle:
Modeling delayed feedback in display advertising. 1097-1105 - Meng Fang, Dacheng Tao:
Networked bandits with disjoint linear payoffs. 1106-1115
Research session 23: text mining
- Zhiyuan Chen, Bing Liu:
Mining topics in documents: standing on the shoulders of big data. 1116-1125 - Zhe Chen, Michael J. Cafarella:
Integrating spreadsheet data via accurate and low-effort extraction. 1126-1135 - Moritz Sudhof, Andrés Goméz Emilsson, Andrew L. Maas, Christopher Potts:
Sentiment expression conditioned by affective transitions and social forces. 1136-1145 - Furong Li, Mong-Li Lee
Entity profiling with varying source reliabilities. 1146-1155 - Anthony Fader, Luke Zettlemoyer, Oren Etzioni:
Open question answering over curated and extracted knowledge bases. 1156-1165
Research session 24: dynamic graph analysis
- Feng Chen, Daniel B. Neill
Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs. 1166-1175 - Polina Rozenshtein, Aris Anagnostopoulos
Event detection in activity networks. 1176-1185 - Meng Jiang
FEMA: flexible evolutionary multi-faceted analysis for dynamic behavioral pattern discovery. 1186-1195 - Behzad Golshan, Theodoros Lappas
Profit-maximizing cluster hires. 1196-1205 - Keqian Li, Wei Lu, Smriti Bhagat, Laks V. S. Lakshmanan, Cong Yu:
On social event organization. 1206-1215
Research session 25: diffusion in social and information networks
- Varun R. Embar, Rama Kumar Pasumarthi, Indrajit Bhattacharya:
A bayesian framework for estimating properties of network diffusions. 1216-1225 - Elias Boutros Khalil
Scalable diffusion-aware optimization of network topology. 1226-1235 - Takeshi Kurashima, Tomoharu Iwata, Noriko Takaya, Hiroshi Sawada:
Probabilistic latent network visualization: inferring and embedding diffusion networks. 1236-1245 - Senzhang Wang, Xia Hu, Philip S. Yu, Zhoujun Li
MMRate: inferring multi-aspect diffusion networks with multi-pattern cascades. 1246-1255 - Xinran He, David Kempe:
Stability of influence maximization. 1256-1265
Research session 26: social and information networks
- Nicola Barbieri, Francesco Bonchi, Giuseppe Manco
Who to follow and why: link prediction with explanations. 1266-1275 - Yang Zhou, Ling Liu:
Activity-edge centric multi-label classification for mining heterogeneous information networks. 1276-1285 - Jiawei Zhang, Philip S. Yu, Zhi-Hua Zhou:
Meta-path based multi-network collective link prediction. 1286-1295 - Manish Purohit, B. Aditya Prakash, Chanhyun Kang, Yao Zhang, V. S. Subrahmanian:
Fast influence-based coarsening for large networks. 1296-1305 - Peng Zhang, Wei Chen
Minimizing seed set selection with probabilistic coverage guarantee in a social network. 1306-1315
Research session 27: graph mining and modeling
- Francesco Bonchi, Francesco Gullo
Core decomposition of uncertain graphs. 1316-1325 - Austin R. Benson
Learning multifractal structure in large networks. 1326-1335 - Chuanren Liu
Temporal skeletonization on sequential data: patterns, categorization, and visualization. 1336-1345 - Bryan Perozzi, Leman Akoglu, Patricia Iglesias Sánchez, Emmanuel Müller
Focused clustering and outlier detection in large attributed graphs. 1346-1355 - Jingchao Ni, Hanghang Tong
Inside the atoms: ranking on a network of networks. 1356-1365
Research session 28: network community detection
- Isabel M. Kloumann, Jon M. Kleinberg:
Community membership identification from small seed sets. 1366-1375 - Lian Duan
Community detection in graphs through correlation. 1376-1385 - Kyle Kloster, David F. Gleich
Heat kernel based community detection. 1386-1395 - Tanmoy Chakraborty
On the permanence of vertices in network communities. 1396-1405 - Rumi Ghosh, Shang-Hua Teng, Kristina Lerman, Xiaoran Yan
The interplay between dynamics and networks: centrality, communities, and cheeger inequality. 1406-1415
Research session 29: scaling-up graph algorithms
- Yuichi Yoshida:
Almost linear-time algorithms for adaptive betweenness centrality using hypergraph sketches. 1416-1425 - Takanori Maehara, Mitsuru Kusumoto, Ken-ichi Kawarabayashi:
Efficient SimRank computation via linearizationPublication of this article pending inquiry. 1426-1435 - Peter Lofgren, Siddhartha Banerjee, Ashish Goel, Seshadhri Comandur:
FAST-PPR: scaling personalized pagerank estimation for large graphs. 1436-1445 - Nesreen K. Ahmed, Nick G. Duffield
Graph sample and hold: a framework for big-graph analytics. 1446-1455 - Florian Bourse, Marc Lelarge, Milan Vojnovic:
Balanced graph edge partition. 1456-1465
Research session 30: social network analysis
- Stavros Sintos, Panayiotis Tsaparas
Using strong triadic closure to characterize ties in social networks. 1466-1475 - Takuya Akiba, Takanori Maehara, Ken-ichi Kawarabayashi:
Network structural analysis via core-tree-decomposition Publication of this article pending inquiry. 1476-1485 - Huan Sun, Mudhakar Srivatsa, Shulong Tan, Yang Li, Lance M. Kaplan, Shu Tao, Xifeng Yan:
Analyzing expert behaviors in collaborative networks. 1486-1495 - Yuan Yao, Hanghang Tong
Predicting long-term impact of CQA posts: a comprehensive viewpoint. 1496-1505 - Bin Bi, Ben Kao, Chang Wan, Junghoo Cho:
Who are experts specializing in landscape photography?: analyzing topic-specific authority on content sharing services. 1506-1515
Industry & government invited talks
- Sri Subramaniam:
Frontiers in E-commerce personalization. 1516 - Tracy De Poalo, Jeremy Howard:
Predictive modeling in practice: a case study from sprint. 1517 - Nigam Shah:
Medicine in the age of electronic health records. 1518 - Cynthia Rudin:
Algorithms for interpretable machine learning. 1519 - Drew Conway:
Data science through the lens of social science. 1520 - Rand Waltzman:
Information environment security. 1521 - Nathan Eagle:
Big data for social good. 1522 - Robert Munro:
Bringing data science to the speakers of every language. 1523
Industry & government
- Acar Tamersoy, Kevin A. Roundy, Duen Horng Chau
Guilt by association: large scale malware detection by mining file-relation graphs. 1524-1533 - Anitha Kannan, Simon Baker, Krishnan Ramnath, Juliet Fiss, Dahua Lin
Mining text snippets for images on the web. 1534-1543 - Ashay Tamhane, Shajith Ikbal, Bikram Sengupta, Mayuri Duggirala, James Appleton:
Predicting student risks through longitudinal analysis. 1544-1552 - Bingsheng Wang, Jinjun Xiong
Novel geospatial interpolation analytics for general meteorological measurements. 1553-1562 - Brian Abelson, Kush R. Varshney, Joy Sun:
Targeting direct cash transfers to the extremely poor. 1563-1572 - Brian Dalessandro, Daizhuo Chen, Troy Raeder, Claudia Perlich, Melinda Han Williams, Foster J. Provost:
Scalable hands-free transfer learning for online advertising. 1573-1582 - Chen Luo, Jian-Guang Lou, Qingwei Lin, Qiang Fu, Rui Ding, Dongmei Zhang, Zhe Wang:
Correlating events with time series for incident diagnosis. 1583-1592 - Chuanren Liu
Proactive workflow modeling by stochastic processes with application to healthcare operation and management. 1593-1602 - Deepak Agarwal, Bee-Chung Chen, Rupesh Gupta, Joshua Hartman, Qi He
Activity ranking in LinkedIn feed. 1603-1612 - Deepak Agarwal, Souvik Ghosh, Kai Wei, Siyu You:
Budget pacing for targeted online advertisements at LinkedIn. 1613-1619 - Dejan Radosavljevik, Peter van der Putten:
Large scale predictive modeling for micro-simulation of 3G air interface load. 1620-1629 - Derek Lin, Rashmi Raghu, Vivek Ramamurthy, Jin Yu, Regunathan Radhakrishnan, Joseph Fernandez:
Unveiling clusters of events for alert and incident management in large-scale enterprise it. 1630-1639 - Diane Hu, Rob Hall, Josh Attenberg:
Style in the long tail: discovering unique interests with latent variable models in large scale social E-commerce. 1640-1649 - Enric Junqué de Fortuny, Marija Stankova, Julie Moeyersoms
Corporate residence fraud detection. 1650-1659 - Fang Jin
Modeling mass protest adoption in social network communities using geometric brownian motion. 1660-1669 - Gabor Melli:
Shallow semantic parsing of product offering titles (for better automatic hyperlink insertion). 1670-1678 - Gergely Ács, Claude Castelluccia:
A case study: privacy preserving release of spatio-temporal density in paris. 1679-1688 - Herodotos Herodotou
Scalable near real-time failure localization of data center networks. 1689-1698 - Jian Xu, Thanuka L. Wickramarathne, Nitesh V. Chawla
Improving management of aquatic invasions by integrating shipping network, ecological, and environmental data: data mining for social good. 1699-1708 - Kiran Kate, Sneha Chaudhari, Andy Prapanca, Jayant Kalagnanam:
FoodSIS: a text mining system to improve the state of food safety in singapore. 1709-1718 - Komal Kapoor, Mingxuan Sun, Jaideep Srivastava
A hazard based approach to user return time prediction. 1719-1728 - Kush R. Varshney, Vijil Chenthamarakshan, Scott W. Fancher, Jun Wang, DongPing Fang, Aleksandra Mojsilovic:
Predicting employee expertise for talent management in the enterprise. 1729-1738 - Li Zheng, Chunqiu Zeng, Lei Li
Applying data mining techniques to address critical process optimization needs in advanced manufacturing. 1739-1748 - Marco Avvenuti, Stefano Cresci
EARS (earthquake alert and report system): a real time decision support system for earthquake crisis management. 1749-1758 - Matthew F. Der, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker:
Knock it off: profiling the online storefronts of counterfeit merchandise. 1759-1768 - Michael Bendersky, Lluis Garcia Pueyo, Jeremiah J. Harmsen, Vanja Josifovski, Dima Lepikhin:
Up next: retrieval methods for large scale related video suggestion. 1769-1778 - Mingqiang Xue, Huayu Wu, Wei Chen, Wee Siong Ng, Gin Howe Goh:
Identifying tourists from public transport commuters. 1779-1788 - Mohammad A. Tayebi, Martin Ester, Uwe Glässer, Patricia L. Brantingham:
Spatially embedded co-offence prediction using supervised learning. 1789-1798 - Naren Ramakrishnan
'Beating the news' with EMBERS: forecasting civil unrest using open source indicators. 1799-1808 - Nemanja Spasojevic, Jinyun Yan, Adithya Rao, Prantik Bhattacharyya:
LASTA: large scale topic assignment on multiple social networks. 1809-1818 - Onno Zoeter, Christopher R. Dance, Stéphane Clinchant, Jean-Marc Andreoli:
New algorithms for parking demand management and a city-scale deployment. 1819-1828 - Paulo Shakarian, Joseph Salmento, William R. Pulleyblank, John Bertetto:
Reducing gang violence through network influence based targeting of social programs. 1829-1836 - Pei Lee, Laks V. S. Lakshmanan, Mitul Tiwari, Sam Shah:
Modeling impression discounting in large-scale recommender systems. 1837-1846 - Richard J. Beckman, Keith R. Bisset, Jiangzhuo Chen, Bryan L. Lewis, Madhav V. Marathe, Paula Elaine Stretz:
ISIS: a networked-epidemiology based pervasive web app for infectious disease pandemic planning and response. 1847-1856 - Ron Kohavi, Alex Deng, Roger Longbotham, Ya Xu:
Seven rules of thumb for web site experimenters. 1857-1866 - Ruben Sipos, Dmitriy Fradkin, Fabian Mörchen, Zhuang Wang:
Log-based predictive maintenance. 1867-1876 - W. Scott Spangler, Angela D. Wilkins, Benjamin J. Bachman, Meena Nagarajan, Tajhal Dayaram, Peter J. Haas, Sam Regenbogen
Automated hypothesis generation based on mining scientific literature. 1877-1886 - Shashank Srikant, Varun Aggarwal:
A system to grade computer programming skills using machine learning. 1887-1896 - Shuai Yuan, Jun Wang, Bowei Chen
An empirical study of reserve price optimisation in real-time bidding. 1897-1906 - Shuang-Hong Yang, Alek Kolcz, Andy Schlaikjer, Pankaj Gupta:
Large-scale high-precision topic modeling on twitter. 1907-1916 - Vignesh Jagadeesh, Robinson Piramuthu, Anurag Bhardwaj, Wei Di, Neel Sundaresan:
Large scale visual recommendations from street fashion images. 1925-1934 - Wayne Xin Zhao, Yanwei Guo, Yulan He
We know what you want to buy: a demographic-based system for product recommendation on microblogs. 1935-1944 - Ye Xu, Zang Li, Abhishek Gupta, Ahmet Bugdayci, Anmol Bhasin:
Modeling professional similarity by mining professional career trajectories. 1945-1954 - Yukihiro Tagami, Toru Hotta, Yusuke Tanaka, Shingo Ono, Koji Tsukamoto, Akira Tajima:
Filling context-ad vocabulary gaps with click logs. 1955-1964
Panel
- Raghu Ramakrishnan, Geoffrey I. Webb:
Does social good justify risking personal privacy? 1965
Tutorials
- Yoshua Bengio:
Scaling up deep learning. 1966 - Antoine Bordes, Evgeniy Gabrilovich:
Constructing and mining web-scale knowledge graphs: KDD 2014 tutorial. 1967 - Jiawei Han, Chi Wang, Ahmed El-Kishky:
Bringing structure to text: mining phrases, entities, topics, and hierarchies. 1968 - Madhav V. Marathe, Anil Kumar S. Vullikanti:
Computational epidemiology. 1969 - Mengling Feng, Mohammad M. Ghassemi, Thomas Brennan, John Ellenberger, Ishrar Hussain, Roger G. Mark:
Management and analytic of biomedical big data with cloud-based in-memory database and dynamic querying: a hands-on experience with real-world data. 1970 - Xavier Amatriain, Bamshad Mobasher
The recommender problem revisited: morning tutorial. 1971 - Francesco Bonchi, David García-Soriano
Correlation clustering: from theory to practice. 1972 - Ruslan Salakhutdinov:
Deep learning. 1973 - Feida Zhu
Network mining and analysis for social applications. 1974 - Graham Cormode
Sampling for big data: a tutorial. 1975 - Wilhelmiina Hämäläinen, Geoffrey I. Webb:
Statistically sound pattern discovery. 1976 - Jiliang Tang, Jie Tang, Huan Liu:
Recommendation in social media: recent advances and new frontiers. 1977
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