Conference Schedule 

Please note: To prepare talks, note that all main conference regular paper presentations are of 20 minutes in length (and allow 2.5 minutes Q/A). Shorter talks are actually encouraged to allow more Q/A time. 
 
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Schedule Overview

November 3rd (Monday)
Time/Room
Emerald 1
Emerald 2 Emerald 3 Rose Jasmine+Narcissus
Lotus
8:30-10am Workshop: Web-scale Knowledge Representation, Retrieval and Reasoning (Web-KR) Workshop: Interactive Mining of Big Data (ImBig) Workshop: Ph.D. Workshop in Information and Knowledge Management (PIKM) Tutorial 1: Crowdsourcing in Information and Knowledge Management Tutorial 2: Learning Non-IID Big Data Workshop: Location and the Web (LocWeb)
10-10:30am Coffee Break
10:30-12:00 Workshop: Web-KR (Continued) Workshop: ImBig (Continued) Workshop: PIKM (Continued) Tutorial 1 (Continued) Tutorial 2 (Continued) Workshop: LocWeb (Continued)
12:00-1:30pm Lunch
1:30-3:00pm Workshop: Web-KR (Continued) Workshop: ImBig (Continued) Workshop: PIKM (Continued) Workshop: Data-driven User Behavioral Modelling and Mining from Social Media (DUBMOD) Tutorial 3: Data Analytics in Healthcare: Problems, Challenges and Future Directions Workshop: LocWeb (Continued)
3:00-3:30pm Coffee Break
3:30-5:00pm Workshop: Web-KR (Continued) Workshop: ImBig (Continued) Workshop: PIKM (Continued) Workshop: DUBMOD (Continued) Tutorial 3 (Continued) Workshop: LocWeb (Continued)
November 4th (Tuesday)
Time/Room
Emerald 1
Emerald 2 Emerald 3 Rose Jasmine+Narcissus
Lotus
8:30-9:30am Keynote 1: Qi Lu
9:30-10am 
Coffee Break
10:00-12:00 DB Session1: Query Processing IR Session 1: Evaluation IR Session 2: Models KM Session 1: Social Networks and Social Media I KM Session 2: Classification I KM Session 3: Recommenders and Collaborative Filtering I
12:00-1:30pm Lunch
1:30-3:00pm Industry Session 1 IR Session 3: Linguistics
IR Session 4: Community QA and Social Search KM Session 4: Social Networks and Social Media II KM Session 5: Classification II KM Session 6: Spatial and Temporal Data Mining
3:00-3:30pm Coffee Break
3:30-5:30pm DB Session 2: Knowledge Base and Data Semantics IR Session 5: Users IR Session 6: Query Intent KM Session 7: Social Networks and Social Media III KM Session 8: Clustering and Ranking KM Session 9: Recommenders and Collaborative Filtering II
6-8pm Conference Reception & CIKM CUP Awards
November 5th (Wednesday)
Time/Room
Emerald 1
Emerald 2 Emerald 3 Rose Jasmine+Narcissus
Lotus
8:30-9:30am Keynote 2: Gerhard Weikum
9:30-10am Coffee Break
10:00-12:00 Poster Session (Poster setup instruction)
12:00-1:30pm Lunch
1:30-3:00pm DB Session 3: Social and Graph Data Industry Session 2 IR Session 7: Exploratory Search
KM Session 10: Text Data Mining I KM Session 11: Knowledge Representation and Reasoning I Demo Group 1 (demo setup instructions)
3:00-3:30pm Coffee Break
3:30-5pm DB Session 4: Data Integration and Big Data IR Session 8: Social Media
IR Session 9: Machine Learning
KM Session 12: Text Data Mining II KM Session 13: Mining Data Streams Demo Group 1 (Continued)
6-9pm Business meeting, Awards  & Conference Banquet(Shanghai Grand Theater)
November 6th (Thursday)
Time/Room
Emerald 1
Emerald 2 Emerald 3 Rose Jasmine+Narcissus
Lotus
8:30-9:30am Keynote 3: Jeff Dean
9:30-10am 
Coffee Break
10:00-12:00 KM Session 14: Data Mining Theory and Methods KM Session 15: Knowledge Representation and Reasoning II KM Session 16: Large- Scale Machine Learning KM Session 17: Web Data Mining KM Session 18: Data Mining Applications and Bioinformatics  
12:00-1:30pm Lunch
1:30-3:00pm DB Session 5: Systems and Applications Industry Session 3 IR Session 10: Engagement, Social, Crowdsourcing IR Session 11: Semantics KM Session 19: Graph Data Mining I Demo Group 2 (demo setup instructions)
3:00-3:30pm Coffee Break
3:30-5:00pm DB Session 6: Privacy and Streams IR Session 12: Efficiency IR Session 13: Domain, Semistructured, Mobile KM Session 20: Entity and Feature Extraction KM Session 21: Graph Data Mining II Demo Group 2 (Continued)
November 7th (Friday)
Time/Room
Emerald 1
Emerald 2 Emerald 3 Rose Jasmine+Narcissus
Lotus
8:30-10am Workshop: Exploiting Semantic Annotations in Information Retrieval (ESAIR) Workshop: Data Warehousing and OLAP (DOLAP) Workshop: Data and Text Mining in Biomedical Informatics (DTMBIO) Workshop: Privacy and Security of Big Data (PSDB) Tutorial 4: E-commerce Personalization at Scale Tutorial 5: Learning to Hash with its Application to Big Data Retrieval and Mining
10-10:30am 
Coffee Break
10:30-12:00 Workshop: ESAIR (Continued) Workshop: DOLAP (Continued) Workshop: DTMBIO (Continued) Workshop: PSDB (Continued) Tutorial 4 (Continued) Tutorial 5 (Continued)
12:00-1:30pm Lunch
1:30-3:00pm Workshop: ESAIR (Continued) Workshop: DOLAP (Continued) Workshop: DTMBIO (Continued) Workshop: PSDB (Continued) Tutorial 6: Deep Learning for Natural Language Processing: Theory and Practice  
3:00-3:30pm Coffee Break
3:30-5:00pm Workshop: ESAIR (Continued) Workshop: DOLAP (Continued) Workshop: DTMBIO (Continued) Workshop: PSDB (Continued) Tutorial 6 (Continued)  


November 4, Tuesday, Morning

DB Session 1 - Query Processing
Time:
10:00am - 12:00noon

  • 843, Rubato DB: A Highly Scalable Staged Grid Database System for OLTP and Big Data Applications, Li-Yan Yuan (University of Alberta); Lengdong Wu (University of Alberta); Jia-Huai You (University of Alberta)
  • 943, MaC: A Probabilistic Framework For Query Answering With Machine-Crowd Collaboration, Chen Zhang (HKUST); Lei Chen (HKUST); Yongxin  Tong (HKUST)
  • 1085, Templated Search over Relational Databases, Anastasios Zouzias (IBM Research); Vagelis Hristidis (UC Riverside); Michail Vlachos (IBM Research)
  • 281, ExpressQ: Enhancing the Expressive Power of Relational Keyword Queries, Zhong Zeng (NUS); Zhifeng Bao (University of Tasmania); Thuy Ngoc Le (National University of Singapore); Mong Li Lee (National University of Singapore); Tok Wang Ling (National University of Singapore)
  • 971, Pulling Conjunctive Query Equivalence out of the Bag, Stefan Boettcher (University of Paderborn); Sebastian Link (The University of Auckland); Lin Zhang (The University of Auckland)

IR Session 1 - IR Evaluation
Time:
10:00am - 12:00noon

  • 391, Machine-Assisted Evaluation for Search Preference Judgments, Ahmed Hassan Awadallah (Microsoft); Imed Zitouni (Microsoft)
  • 30, Designing Test Collections for Comparing Many Systems, Tetsuya Sakai (Waseda University)
  • 1190, Multileaved Comparisons for Fast Online Evaluation, Anne Schuth (University of Amsterdam); Floor Sietsma (University of Amsterda); Shimon Whiteson (University of Amsterdam); Damien Lefortier (Yandex); Maarten de Rijke (University of Amsterdam)
  • 1116, A Retrievability Analysis: Exploring the Relationship Between Retrieval Bias and Retrieval Performance, Colin Wilkie (University of Glasgow); Leif Azzopardi (University of Glasgow)
  • 1204, Relevance and Effort: An Analysis of Document Utility, Emine Yilmaz (University College London); Manisha Verma (UCL); Filip Radlinski (Microsoft); Nick Craswell (Microsoft); Peter Bailey (Microsoft)

IR Session 2 - Models
Time:
10:00am - 12:00noon

  • 895, A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval, Yelong Shen (Microsoft Research); Xiaodong He (Microsoft Research); Jianfeng Gao (Microsoft Research); Li Deng (Microsoft Research); Grégoire Mesnil (University of Montréal)
  • 37, A Comparison of Retrieval Models using Term Dependencies, Samuel Huston (Google); W. Bruce Croft (University of Massachusetts)
  • 1485, Meta-Path-Based Ranking with Pseudo Relevance Feedback on Heterogeneous Graph for Citation Recommendation, Xiaozhong Liu (Department of Information and Library Science, Indiana University); Chun Guo (Indiana University Bloomington); Yingying Yu (Dalian Maritime University); Yizhou Sun (Northeastern University)
  • 1342, A Fixed-Point Method for Weighting Terms   in Verbose Informational Queries, Jiaul Paik (University of Maryland, College Park); Doug Oard (University of Maryland)
  • 937, Term Selection and Result Reranking for Question Retrieval by Exploiting Hierarchical Classification, Wen Chan (Fudan University); Jintao Du (Fudan University); XIangdong Zhou (Fudan University)

KM Session 1: Social Networks and Social Media I
Time: 10:00am - 12:00noon

  • 277, Analysis on Community Variational Trend in Dynamic Networks, Xiaowei Jia, University at Buffalo, SUNY; Nan Du, University at Buffalo, SUNY; Jing Gao, University at Buffalo, SUNY; Aidong Zhang, University at Buffalo, SUNY
  • 1029, Learning Interactions for Social Prediction in Large-scale Networks, Xiaofeng Yu, HP Labs China; Junqing Xie,
  • 355, Influence Maximization over Large-Scale Social Networks: A Bounded Linear Approach, Qi Liu, USTC; Biao Xiang, ; Enhong Chen, University of Science and Technology of China; Hui Xiong, "Rutgers,the State University of New Jersey"; Fangshuang Tang, ; Jeffrey Xu Yu, CUHK
  • 131, Predictability of Distrust with Interaction Data, Jiliang Tang, ; Huan Liu, Arizona State University
  • 1014, Optimizing Multi-Relational Factorization Models for Multiple Target Relations, Lucas Drumond, University of Hildesheim; Ernesto Diaz-Aviles, IBM Research; Lars Schmidt-Thieme, University of Hildesheim; Wolfgang Nejdl, L3S Research Center

KM Session 2 - Classification I
Time:
10:00am - 12:00noon

  • 67, Learning to Propagate Rare Labels, Rakesh Pimplikar, ; Dinesh Garg, IBM India Research Lab; Deepesh Bharani, ; Gyana Parija,
  • 138, A Mixtures-of-Experts Framework for Multi-Label Classification, Charmgil Hong, University of Pittsburgh; Iyad Batal, GE Global Research; Milos Hauskrecht, University of Pittsburgh
  • 175, Solving Linear SVMs with Multiple 1D Projections, Johannes Schneider, ; Michail Vlachos, IBM Research; Jasmina Bogojeska,
  • 977, Adding Robustness to Support Vector Machines Against Adversarial Reverse Engineering, Ibrahim Alabdulmohsin, KAUST; Xin Gao, KAUST; Xiangliang Zhang, KAUST
  • 1129, Regularized Survival Regression with Active Learning for Censored Data, Bhanukiran Vinzamuri, Wayne State University; Yan Li, Wayne State University; Chandan K. Reddy, Wayne State University

KM Session 3 - Recommenders and Collaborative Filtering I
Time: 10:00am - 12:00noon

  • 1071, Collaborative Filtering Incorporating Review Text and Co-clusters of Hidden User Communities and Item Groups, Yinqing Xu, CUHK; Wai Lam, The Chinese University of HK; Tianyi Lin,
  • 241, Leveraging Social Connections to Improve Personalized Ranking for Collaborative Filtering, Tong Zhao, CUHK; Julian McAuley, Stanford; Irwin King, Chinese University of Hong Kong, Hong Kong, China
  • 125, Deviation-Based Contextual SLIM Recommenders, YONG ZHENG, DePaul University; Bamshad Mobasher, DePaul University; Robin Burke, DePaul University
  • 891, User Interests Imbalance Exploration in Social Recommendation: A Fitness Adaptation, Tianchun Wang, Tsinghua University; Xiaoming Jin, Tsinghua University; Xuetao Ding, Yahoo! Labs, Beijing; Xiaojun Ye, Tsinghua University
  • 1212, CARS2: Learning Context-aware Representations for Context-Aware Recommendations, Yue Shi, Yahoo! Labs; Alexandros Karatzoglou, Telefonica Research; Linas Baltrunas, Telefonica Research; Martha Larson, TU Delft; Alan Hanjalic, TU Delft

November 4, Tuesday, Afternoon

 

IR Session 3 - Linguistics
Time: 1:30pm - 3:00pm

  • 1179, Incremental Update Summarization: Adaptive Sentence Selection based on  Prevalence and Novelty, Richard McCreadie (University of Glasgow); Craig Macdonald (University of Glasgow); Iadh Ounis (University of Glasgow)
  • 900, A Reconstruction Approach to Structural and Textual Summarization of Dynamic Multi-Source User-Generated-Content, Zhao Yan Ming (National University of Singapo); Jintao Ye (Mozat PTE LTD); Tat-Seng Chua (NUS)
  • 506, Using Crowdsourcing to Investigate Perception of Narrative Similarity, Dong Nguyen (University of Twente); Dolf  Trieschnigg (University of Twente); Mariet Theune ()
  • 991, Correct Me If I'm Wrong: Fixing Grammatical Errors by Preposition Ranking, Roman Prokofyev (University of Fribourg); Ruslan Mavlyutov (); Martin Grund (EXascale Infolab); Gianluca Demartini (University of Fribourg); Philippe Cudre-Mauroux (eXascale Infolab)

IR Session 4 - Community QA and Social Search
Time: 1:30pm - 3:00pm

  • 1565, Mining Semi-Structured Online Knowledge Bases to Answer Natural Language Questions on Community QA Websites, Parikshit Sondhi (Walmartlabs, uiuc); Chengxiang Zhai (UIUC)
  • 149, Improving Term Weighting for Community Question Answering Search Using Syntactic Analysis, Idan Szpektor (Yahoo! Research); David Carmel (Yahoo! Research); Yuval Pinter (Yahoo! Research); Avihai Mejer (Yahoo! Research)
  • 969, Social Book Search Reranking with Generalized Content-Based Filtering, Bo-Wen Zhang (University of Science and Technology Beijing); Xu-Cheng Yin (University of Science and Technology Beijing); Xiao-Ping Cui (University of Science and Technology Beijing); Bin Geng (University of Science and Technology Beijing); Jiao Qu (University of Science and Technology Beijing); Fang Zhou (University of Science and Technology Beijing); Li Song (Institute of Automation,Chinese Academy of Science); Hongwei Hao (Institute of Automation, Chinese Academy of Sciences)
  • 295,  Question Retrieval with High Quality Answers in Community Question Answering, Kai Zhang (Beihang University); Wei Wu (); zhoujun Li (Beihang University)
KM Session 4 - Social Networks and Social Media II
Time: 1:30pm - 3:00pm
  • 102, Controllable Information Sharing for User Accounts Linkage across Multiple Online Social Networks, Yilin Shen, Samsung Research America; Hongxia Jin, Samsung Research America
  • 1031, Identifying Your Customers in Social Networks, Chun-Ta Lu, UIC; Hong-Han Shuai, NTU; Philip Yu, University of Illinois at Chicago
  • 1092, Learning a linear model of influence  from transient opinion dynamics, Abir De, IIT  Kharagpur; sourangshu Bhattacharya, IIT Kharagpur; Parantapa Bhattacharya, IIT Kharagpur; niloy Ganguly, IIT Kharagpur; Soumen Chakrabarti, IIT Bombay
  • 645, Modeling Paying Behavior in Game Social Networks, Zhanpeng Fang, Tsinghua University; Xinyu Zhou, ; Jie Tang,

KM Session 5 - Classification II
Time:
1:30pm - 3:00pm

  • 35, Enabling Precision/Recall Preferences for Semi-supervised SVM Training, ZEYI WEN, University of Melbourne; Rui Zhang, The University of Melbourne; Kotagiri Rao, The University of Melbourne, Australia
  • 604, A Cross-modal Multi-task Learning Framework for Image Annotation, Liang Xie, HUST; Peng Pan, Huazhong University of Science and Technology; Yansheng Lu, Huazhong University of Science and Technology; Shixun Wang,
  • 1025, Multi-task Multi-view Learning for Heterogeneous Tasks, Xin Jin, Chinese Academy of Sciences; Fuzhen Zhuang, Chinese Academy of Sciences; Hui Xiong, "Rutgers,the State University of New Jersey"; Changying Du, Chinese Academy of Sciences; Ping Luo, CAS, China; Qing He, Chinese Academy of Sciences
  • 1770, Multi-task Sparse Structure Learning, Andre Goncalves, University of Minnesota; Puja Das, ; Soumyadeep Chatterjee, ; Vidyashankar Sivakumar, ; Fernando Von Zuben, ; Arindam Banerjee,

KM Session 6 - Recommenders and Collaborative Filtering II
Time: 1:30pm - 3:00pm

  • 274, Truth Discovery in Crowdsourced Detection of Spatial Events, Robin Wentao Ouyang, UCLA; Mani Srivastava, UCLA; Alice Toniolo, University of Aberdeen; Timothy Norman, University of Aberdeen
  • 327, Maximizing Multi-scale Spatial Statistical Discrepancy, Weishan Dong, IBM Research - China; Renjie Yao, ; Chunyang Ma, ; Changsheng Li, IBM Research-China; Lei Shi, ; Lu Wang, ; Yu Wang, ; Peng Gao, ; Junchi Yan
  • 1636, Mining and Planning Time-aware Routes  Using Location Check-in Data, Hsun-Ping Hsieh, National Taiwan University; Cheng-Te Li, Academia Sinica
  • 1135, High Impact Academic Paper Prediction Using Temporal and Topological Features, Feruz Davletov, Istanbul Sehir University; Ali Selman Aydin, Istanbul Sehir University; Ali Cakmak, Istanbul Sehir University

DB Session 2 - Knowledge Base and Data Semantics
Time: 3:30pm - 5:00pm

  • 1403, Robust Entity Linking via Random Walks, Zhaochen Guo (University of Alberta); Denilson Barbosa (University of Alberta, Canada)
  • 533, X: A Scalable Distributed SPARQL Query Processing System, Buwen Wu (HUST); Yongluan Zhou (University of Southern Denmark); Pingpeng Yuan (HUST); Hai Jin (Huazhong Uni. of Sci. & Tech.); Ling Liu (Georgia Tech)
  • 262, Pattern Match Query in a Large Uncertain Graph, Ye Yuan (Neu)
  • 258, Semantic Approximate Keyword Query Based on Keyword and Query Coupling Relationship Analysis, Xiangfu Meng (UTS); longbing  Cao (UTS); Jingyu Shao (UTS)

IR Session 5 - Users
Time: 3:30pm - 5:30pm

  • 766, The Effects of Vertical Rank and Border on Aggregated Search Coherence and Search Behavior, Jaime Arguello (University of North Carolina, USA); Robert Capra (University of North Carolina, USA)
  • 584, An Eye-tracking Study of User Interactions with Query Auto Completion, Katja Hofmann (Microsoft); Bhaskar Mitra (); Milad Shokouhi (); Filip Radlinski ()
  • 1009, Improving Tail Query Performance by Fusion Model, Shuai Huo (Tsinghua); Min Zhang (Tsinghua university); Liu Yiqun (Tsinghua University); Ma ShaoPing (Tainghua University)
  • 954, Predicting Search Task Difficulty at Different Search Stages, CHANG LIU (Peking University); Jingjing Liu (University of South Carolina); Nicholas Belkin (Rutgers University)
  • 564, Re-call and Re-cognition in Episode Re-retrieval: A User Study on News Re-finding a Fortnight Later, Shuya Ochiai (Kyoto University); Makoto Kato (Kyoto University); Katsumi Tanaka (Kyoto University)

IR Session 6 - Query Intent
Time: 3:30pm - 5:00pm

  • 1115, Online Exploration for Detecting Shifts in Fresh Intent, Damien Lefortier (Yandex); Pavel Serdyukov (Yandex); Maarten de Rijke (University of Amsterdam)
  • 1157, Effect of Intent Descriptions on Retrieval Evaluation, Emine Yilmaz (University College London); Evangelos Kanoulas (Google); Nick Craswell (Microsoft)
  • 875, Search Result Diversification via Filling Up Multiple Knapsacks, Hai-Tao Yu (The University of Tokushima); Fuji Ren (The University of Tokushima)
  • 95, Query Augmentation based Intent Matching in Retail Vertical Ads, Huasha Zhao (UC Berkeley); Ye Chen (Microsoft); John Canny (UC Berkeley); Tak Yan (Microsoft)

KM Session 7 - Social Networks and Social Media III
Time: 3:30pm - 5:30pm

  • 1407, Sketch-based Influence Maximization and Computation: Scaling up with Guarantees, Edith Cohen, Microsoft Research; Daniel Delling, Microsoft Research; Thomas Pajor, Microsoft Research; Renato Werneck, Microsoft Research
  • 1296, Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference, Joseph Pfeiffer, Purdue University; Jennifer Neville, Purdue; Paul Bennett, Microsoft
  • 247, Modeling Topic Diffusion in Multi-Relational Bibliographic Information Networks, Huan Gui, University of Illinois at Urba; Yizhou Sun, Northeastern University; Jiawei Han, University of Illinois at Urbana-Champaign; George Brova, University of Illinois at Urbana-Champaign
  • 70, Graph-based Point-of-interest Recommendation with Geographical and Temporal Influences, Quan Yuan, Nanyang Technological Univ.; Gao Cong, "Nanyang Technological University, Singapore"; Aixin Sun, NTU
  • 913, On Building Decision Trees from Large-scale Data in Applications of On-line Advertising, Shivaram Kalyanakrishnan, Yahoo Labs Bangalore; Deepthi Singh, Yahoo Labs Bangalore; Ravi Kant, Yahoo Labs Bangalore

KM Session 8 - Clustering and Ranking
Time: 3:30pm - 5:30pm

  • 49, On Improving Co-Cluster Quality with Application to Recommender Systems, Michail Vlachos, IBM Research; Francesco Fusco, ; Harry Mavroforakis, ; Anastasios Kyrillidis, ; Vasileios Vasiliadis,
  • 1010, Focusing Decomposition Accuracy by Personalizing Tensor Decomposition (PTD), Xinsheng Li, ASU; Shengyu Huang, ASU; K. Selcuk Candan, ASU; Maria Luisa Sapino, U. Torino
  • 839, Ranking-based Clustering on General Heterogeneous Information Networks by Network Projection, Chuan Shi, BUPT; Wang Ran, ; Yitong Li, BUPT
  • 40, NCR: A Scalable Network-Based Approach to Co-Ranking in Question-and-Answer Sites, Jingyuan Zhang, UIC; Xiangnan Kong, UIC; Roger Jie Luo, Yahoo! Labs; Yi Chang, Yahoo Lab; Philip Yu, University of Illinois at Chicago
  • 180, Similarity Search using Concept Graphs, Rakesh Agrawal, Microsoft Research; Sreenivas Gollapudi, Microsoft Research; Anitha Kannan, Microsoft Research; Krishnaram Kenthapadi, Microsoft Research

KM Session 9 - Recommenders and Collaborative Filtering II
Time: 3:30pm - 5:30pm

  • 687, Strength Lies in Differences - Diversifying Friends for Recommendations through Subspace Clustering, Eirini Ntoutsi, LMU; Kostas Stefanidis, ICS-FORTH; Katharina Rausch, LMU; Hans-Peter Kriegel, LMU
  • 265, Exploiting Geographical Neighborhood Characteristics for Location Recommendation, Yong Liu, NTU; Wei Wei, Nanyang Technological University; Aixin Sun, NTU; Chunyan Miao, Nanyang Technological University
  • 750, Increasing the Responsiveness of Recommended Expert Collaborators for Online Open Projects, Mohammad Allaho, The Pennsylvania State Univers; Wang-Chien Lee, Penn State
  • 857, Dual-Regularized One-Class Collaborative Filtering, Yuan Yao, Nanjing University; Hanghang Tong, City College, CUNY; Guo Yan, ; Feng Xu, ; Xiang Zhang, ; Boleslaw Szymanski, ; Jian Lv, Nanjing University
  • 554, HGMF: Hierarchical Group Matrix Factorization for Collaborative Recommendation, Xin Wang, ZheJiang University; Weike Pan, Shenzhen University; Congfu Xu,

November 5, Wednesday, Afternoon

DB Session 3 - Social and Graph Data
Time: 1:30pm - 3:00pm

  • 286, SocialTransfer: Transferring Social Knowledge for Cold-Start Crowdsourcing, Zhou Zhao (Hkust); James Cheng (CUHK); Wilfred Ng (HKUST); furu Wei (); ming Zhou (); Yingjun Wu ()
  • 57, CAST: A Context-Aware Story-Teller for Streaming Social Content, Pei Lee (UBC); Laks V.S. Lakshmanan (UBC); Evangelos Milios (Dal)
  • 189, Distributed Graph Summarization, Xingjie Liu (Penn State); Yuanyuan Tian (IBM); Qi He (Linkedin); Wang-Chien Lee (Penn State)
  • 428, Efficient Probabilistic Supergraph Search over Large Uncertain Graphs, Yongxin Tong (HKUST); Caleb Chen CAO (HKUST); Lei Chen (HKUST)

IR Session 7: Exploratory Search
Time: 1:30pm - 3:00pm

  • 177, Narrow or Broad? Estimating Subjective Specificity in Exploratory Search, Kumaripaba Athukorala (University of Helsinki); Antti Oulasvirta (Max Planck Institute for Informatics); Dorota Glowacka (University of Helsinki); Jilles Vreeken (MPI); giulio Jacucci (Helsinki Institute for Information Technology HIIT)
  • 390, Exploration Suggestions for Complex Search Tasks, Ahmed Hassan Awadallah (Microsoft); Ryen White (Microsoft Research); Patrick Pantel (Microsoft Research); Susan Dumais (Microsoft Research)
  • 1463, Extending Faceted Search to the General Web, Weize Kong (Univ of Massachusetts Amherst); James Allan (University of Massachussetts Amherset)
  • 233, From Skimming to Reading:  A Two-stage Examination Model for Web Search, Liu Yiqun (Tsinghua University); Chao WANG (Tsinghua University); Ke ZHOU (University of Edinburgh); Jian-Yun Nie (University of Montreal); Min Zhang (Tsinghua university); Ma ShaoPing (Tainghua University)

KM Session 10: Text Data Mining I
Time: 1:30pm - 3:00pm

  • 458, Generative Modeling of Entity Comparisons in Text, Maksim Tkatchenko, ; Hady Lauw, Singapore Management University
  • 481, How many folders do you really need? Classifying email into a handful of categories, Mihajlo Grbovic, Yahoo; Guy Halawi, Yahoo; Zohar Karnin, Yahoo Labs; Yoelle Maarek, Yahoo
  • 1080, Latent Aspect Mining via Exploring Sparsity and Intrinsic Information, Yinqing Xu, CUHK; Tianyi Lin, ; Wai Lam, The Chinese University of HK; Zirui Zhou, ; Hong Cheng, CUHK; Anthony Man-Cho So,
  • 193, Recognizing Humor on Twitter, Renxian Zhang, Tongji University; Naishi Liu, Shanghai Jiaotong University

KM Session 11: Knowledge Representation and Reasoning I
Time: 1:30pm - 3:00pm

  • 1073, Towards Consistency Checking over Evolving Ontologies, Jiewen Wu, IBM Research; Freddy Lecue, IBM Research
  • 931, A Practical Fine-grained Approach to Resolving Incoherent OWL 2 DL Terminologies, Jianfeng Du, Guangdong University Foreign S; Guilin Qi, Southeast University; Xuefeng Fu, Southeast University
  • 1700, Domain Cartridge : Unsupervised Framework for Shallow Domain Ontology Construction from Corpus, Subhabrata Mukherjee, MPI; Jitendra Ajmera, ; Sachindra Joshi,
  • 694, Faceted Search over Ontology-Enhanced RDF Data, Marcelo Arenas, Pontificia Universidad Catolica de Chile; Bernardo Cuenca-Grau, University of Oxford; Evgeny Kharlamov, University of Oxford; Sarunas Marciuska, ; Dmitriy Zheleznyakov, University of Oxford

DB Session 4 - Data Integration and Big Data
Time: 3:30pm - 5:00pm

  • 1105, DFD: Efficient Functional Dependency Discovery, Ziawasch Abedjan (Hasso Plattner Institute); Felix Naumann (Hasso Plattner Institute); Patrick Schulze ()
  • 1173, Estimating the Number and Sizes of Fuzzy-Duplicate Clusters, Arvid Heise (Hasso-Plattner Institute); Kasneci Gjergji (Hasso-Plattner-Institut fur Softwaresystemtechnik); Felix Naumann (Hasso Plattner Institute)
  • 211, Efficient Static and Dynamic In-Database Tensor Decompositions on Chunk-Based Array Stores, Mijung Kim (ASU); K. Selcuk Candan (ASU)
  • 587, Efficient Filter Approximation Using the Earth Mover's Distance in Very Large Multimedia Databases with Feature Signatures, Merih Seran Uysal (RWTH Aachen); Christian Beecks (RWTH Aachen); Jochen Schmuecking (RWTH Aachen); Thomas Seidl (RWTH Aachen)

IR Session 8: Social Media
Time: 3:30pm - 5:00pm

  • 186, Time-Aware Rank Aggregation for Microblog Search, Shangsong Liang (University of Amsterdam); Zhaochun Ren (University of Amsterdam); Wouter Weerkamp (904Labs); Edgar Meij (Yahoo! Labs); Maarten de Rijke (University of Amsterdam)
  • 152, Tagging Your Tweets: A Probabilistic Modeling of Hashtag Annotation in Twitter, Zongyang Ma (NTU); Aixin Sun (NTU); Quan Yuan (Nanyang Technological Univ.); Gao Cong ("Nanyang Technological University, Singapore")
  • 1540, Large Scale Analysis of People Search within an Online Social Network, Nikita Spirin (UIUC); Karrie Karahalios (UIUC); Junfeng He (Facebook); Mike Develin (Facebook); Maxime Boucher (Facebook)
  • 1690, Automatic Social Circle Detection Using Multi-View Clustering, Yuhao Yang (University of Kansas); Chao Lan (University of Kansas); Xiaoli Li (University of Kansas); Bo Luo (University of Kansas); Luke Huan (University of Kansas)

IR Session 9: Machine Learning
Time: 3:30pm - 5:00pm 

  • 1304, Semantic Compositionality in Tree Kernels, Roberto Basili (University of Roma Tor Vergata); Paolo Annesi (University of Roma Tor Vergata); Danilo Croce (University of Roma, Tor Vergat)
  • 151, Focused Crawling for Structured Data, Robert Meusel (University of Mannheim); Peter Mika (Yahoo Barcelona); Roi Blanco (Yahoo! Labs); Christian Bizer (University of Mannheim)
  • 48, Ranking Optimization with Constraints, Fangzhao Wu (Tsinghua University); Jun Xu (ICT, CAS); Li Hang (Huawei); Xin Jiang (Huawei)
  • 1569, Supervised Nested PageRank, Maksim Zhukovskii (Yandex); Gleb Gusev (yandex); Pavel Serdyukov (Yandex)

KM Session 12: Text Data Mining II
Time: 3:30pm - 5:00pm

  • 1166, Concept-based Short Text Classification and Ranking, Zhongyuan Wang, Renmin University of China; Fang Wang, Beihang University; Wen Ji-Rong, Renmin University of China; zhoujun Li, Beihang University
  • 143, EgoCentric: Ego Networks for Knowledge-based Short Text Classification, William Lucia, University of Insubria; Elena Ferrari, University of Insubria
  • 494, A Cross-Lingual Joint Aspect/Sentiment Model for Sentiment Analysis, Zheng Lin, Institute of Information Engineering, Chinese Academy of Sciences; Xiaolong Jin, ; Weiping Wang, Institute of Information Engineering, Chinese Academy of Sciences; Xueqi Cheng, ICT, CAS; Xueke Xu, Institute of Computing Technology, Chinese Academy of Sciences
  • 433, Microblog Topic Contagiousness Measurement and Emerging Outbreak Monitoring, Victor W. Chu, University of New South Wales; Raymond K. Wong, University of New South Wales; Chi-Hung Chi, CSIRO

KM Session 13: Mining Data Streams
Time: 3:30pm - 5:00pm

  • 324, Fast, Accurate, and Space-efficient Tracking of Time-weighted Frequent Items from Data Streams, Yongsub Lim, KAIST; Jihoon Choi, ; U Kang, KAIST
  • 343, GI-NMF: Group Incremental Non-Negative Matrix Factorization on Data Streams, Xilun Chen, Arizona State University; K. Selcuk Candan, ASU
  • 54, Active Learning for Streaming Networked Data, Zhilin Yang, Tsinghua University; Jie Tang, ; Yutao Zhang,
  • 824, Online User Location Inference Exploiting Spatiotemporal Correlations in Social Streams, Yuto Yamaguchi, University of Tsukuba; Toshiyuki Amagasa, University of Tsukuba; Hiroyuki Kitagawa, University of Tsukuba; Yohei Ikawa, IBM Research Tokyo
November 6th, Morning

KM Session 14: Data Mining Theory and Methods
Time: 10:00am - 12:00noon

  • 1633, Robust Principal Component Analysis with Missing Data, Fanhua Shang, CUHK; Yuanyuan Liu, The Chinese University of Hong Kong; James Cheng, CUHK; Hong Cheng, CUHK
  • 778, Model Selection with the Covering Number of the Ball of RKHS, Lizhong Ding, ; Shizhong Liao, Tianjin Unversity
  • 727, A Flexible Framework for Projecting Heterogeneous Data, Aubrey Gress, UC Davis; Ian Davidson, UC Davis
  • 396, Fair Allocation in Online Markets, Sreenivas Gollapudi, Microsoft Research; Debmalya Panigrahi, Duke University
  • 33, Understanding the Sparsity: Augmented Matrix Factorization with Sampled Constraints on Unobservables, Yongfeng Zhang, Tsinghua University; Min Zhang, Tsinghua university; Yi Zhang, UC Santa Cruz; Liu Yiqun, Tsinghua University; Ma ShaoPing, Tainghua University

KM Session 15: Knowledge Representation and Reasoning II
Time: 10:00am - 12:00noon

  • 566, Structure Learning via Parameter Learning, William Yang Wang, CMU; Kathryn Mazaitis, Carnegie Mellon University; William Cohen, Carnegie Mellon University
  • 1521, Scalable Distributed Belief Propagation with Prioritized Block Updates, Jiangtao Yin, UMASS Amherst; Lixin Gao, University of Massachusetts Amherst
  • 814,  Improving Word Representations with Relation Knowledge and Grouping Knowledge, Chang Xu, Nankai University; Yalong Bai,
  • 1034, On Independence Atoms and Keys, Miika Hannula, University of Helsinki; Juha Kontinen, University of Helsinki; Sebastian Link, The University of Auckland
  • 1681, Rebuilding the Tower of Babel: Towards Cross-System Malware Information Sharing, Ting Wang, IBM Research; Shicong Meng, IBM Research; Wei Gao, The University of Tennessee, Knoxville

KM Session 16: Large- Scale Machine Learning
Time: 10:00am - 12:00noon

  • 395, Computing Multi-Relational Sufficient Statistics for  Large Databases, Zhensong Qian, Simon Fraser University; Oliver Schulte, Simon Fraser University; Yan Sun, Simon Fraser University
  • 181, Distributed Stochastic ADMM for Matrix Factorization, Zhi-Qin Yu, Shanghai Jiaotong Univservity; Xing-Jian Shi, Shanghai Jiao Tong University; Ling Yan, Shanghai Jiao Tong University; Wu-Jun Li, Nanjing University
  • 1536, Data/Feature Distributed Stochastic Coordinate Descent for Fast, Scalable, and High-Dim. Logistic Regression, Dongyeop Kang, ; Woosang Lim, ; Kijung Shin, Seoul National University; Sael Lee, ; U Kang, KAIST
  • 1245, Exploring Ensemble of Models in Taxonomy-based Cross-Domain Sentiment Classification, Cong-Kai Lin, National Taiwan University; Yang-Yin Lee, National Taiwan University; Chi-Hsin Yu, National Taiwan University; Hsin-Hsi Chen, National Taiwan University
  • 1003, Verifiable UML Artifact-Centric Business Process Models, Diego Calvanese, Univ. of Bozen-Bolzano.; Montserrat Estanol, Universitat Politecnica de Catalunya; Marco Montali, Free Universtiy of Bozen-Bolzano; Ernest Teniente, Universitat Politecnica de Catalunya 

KM Session 17: Web Data Mining
Time: 10:00am - 12:00noon

  • 1421, Transfer Understanding from Head Queries to Tail Queries, Yangqiu Song, UIUC; Haixun Wang, Google Research; Weizhu Chen, ; Shusen Wang,
  • 291, Twitter Opinion Topic Model: Extracting Product Opinions from Tweets by leveraging Hashtags and Sentiment Lexicon, Kar Wai Lim, ANU; Wray Buntine, Monash University
  • 649, Analysis of Physical Activity Propagation in a Health Social Network, Hai Phan, University of Oregon; Dejing Dou, University of Oregon; Xiao Xiao, University of Oregon; Brigitte Piniewski, PeaceHealth Laboratories; David Kil, HealthMantic, Inc
  • 1028, Predicting the Popularity of Online Serials with Autoregressive Models, Biao Chang, University of Science and Tech; hengshu Zhu, ; Yong Ge, ; Enhong Chen, University of Science and Technology of China; Hui Xiong, "Rutgers,the State University of New Jersey"; Chang Tan,
  • 1759, What a Nasty day: Exploring Mood-Weather Relationship from Twitter, Xun Wang, NTT

KM Session 18: Data Mining Applications and Bioinformatics
Time: 10:00am - 12:00noon

  • 981, Sequential Action Patterns in Collaborative Ontology-Engineering Projects: A Case-Study in the Biomedical Domain, Simon Walk, Graz University of Technology; Philipp Singer, Gesis - Leibniz Institute for the Social Sciences; Markus Strohmaier, Gesis - Leibniz Institute for the Social Sciences
  • 409, Towards Pathway Variation Identification: Aligning Patient Records with
  • 744, PatentDom: Analyzing Technology Relationship on Multi-View Patent Graphs, Longhui Zhang, FIU; Lei Li, Florida International University; Tao Li, Florida International University
  • 716, Exploring Legal Patent Citations for Patent Valuation, Shuting Wang, Penn State University; Zhen Lei, ; Wang-Chien Lee, Penn State
  • 397, Tracking Temporal Dynamics of Purchase Decisions via Hierarchical Time-rescaling Model, Hideaki Kim, NTT Laboratory; Noriko Takaya, NTT; Hiroshi Sawada, NTT

November 6th, Afternoon

DB Session 5 - Systems and Applications
Time: 1:30pm - 3:00pm

  • 1419, Robust Skew-resistant Joins in Shared-Nothing Systems, Long Cheng (National University of Ireland); Spyros Kotoulas (IBM Research); Tomas Ward (National University of Ireland Maynooth); Georgios Theodoropoulos (Durham University)
  • 630, SharkDB - An In-memory Column-oriented Trajectory Storage, Haozhou Wang (The University of Queensland); Kevin Zheng (Queensland U); Xiaofang Zhou (Soochow University); Shazia Sadiq (The University of Queensland)
  • 491, Deal or Deceit: Detecting Cheating in Distribution Channels, Kai Shu (CQU); Ping Luo (CAS, China)
  • 58, An Appliance-driven Approach to Detection of Corrupted Load Curve Data, Guoming Tang (University of Victoria); Kui Wu (University of Victoria); Jian Pei ("Simon Fraser University, Canada"); Jiuyang Tang (National University of Defence Technology); Jingsheng Lei (Shanghai University of Electric Power)

IR Session 10: Engagement, Social, Crowdsourcing
Time: 1:30pm - 3:00pm 

  • 315, Understanding Within-Content Engagement through Pattern Analysis of Mouse Gestures, Ioannis Arapakis (Yahoo Labs); Mounia Lalmas (Yahoo Labs); George Valkanas (University of Athens)
  • 1382, Modelling and Detecting Changes in User Satisfaction, Julia Kiseleva (TU/e); Eric Crestan (Microsoft Bing); Riccardo Brigo (Microsoft Bing); Roland  Dittel (Microsoft Bing)
  • 627, "Picture the scene..."; Visually Summarising Social Media Events, Philip McParlane (University of Glasgow); Andrew McMinn (University of Glasgow); Joemon Jose (University of Glasgow)
  • 1096, Competitive Game Designs for Improving the Cost Effectiveness of Crowdsourcing, Markus Rokicki (L3S Research Center); Sergiu Chelaru (L3S Research Center); Sergej Zerr (L3S Research Center); Stefan Siersdorfer ()

IR Session 11: Semantics
Time: 1:30pm - 3:00pm 

  • 679, Cross-Modality Submodular Dictionary Learning for Information Retrieval, Fan Zhu (The University of Sheffield); Ling Shao (The University of Sheffield); Mengyang Yu (The University of Sheffield)
  • 1514, A Word-Scale Probabilistic Latent Variable Model for Detecting Human Values, Yasuhiro Takayama (Tokuyama College of Technology); Yoichi Tomiura (Kyushu University); Emi Ishita (Kyushu University); Doug Oard (University of Maryland); Kenneth Fleischmann (University of Texas at Austin); An-Shou Cheng (National Sun Yat-sen University)
  • 1280, Searching Locally-Defined Entities, Zhaohui Wu (Penn State University); Yuanhua Lv (Microsoft); Ariel Fuxman (Microsoft Research)
  • 79, Customized Organization of Social Media Contents using Focused Topic Hierarchy, Xingwei Zhu (CS Dept., Tsinghua University); Zhao-Yan Ming (Dept. of CS, School of Computing, National University of Singapore, Singapore); Yu Hao (Dept. of Computer Sci. and Tech., Tsinghua University, Beijing, China); Xiaoyan Zhu (Dept. of Computer Sci. and Tech., Tsinghua University, Beijing, China); Tat-Seng Chua (Dept. of CS, School of Computing, National University of Singapore, Singapore)

KM Session 19: Graph Data Mining I
Time: 1:30pm - 3:00pm

  • 1387, Sampling triples from restricted networks using MCMC strategy, Mahmudur Rahman, IUPUI; Mohammad AlHassan, IUPUI
  • 796, Efficient Subgraph Skyline Search Over Large Graphs, Weiguo Zheng, Peking university; Lei Zou, Beijing University; Xiang Lian, UTPA; Liang Hong, ; Dongyan Zhao,
  • 43, Within-Network Classification Using Radius-Constrained Neighborhood Patterns, Jialong Han, Renmin Univerisity of China; Wen Ji-Rong, Renmin University of China; Jian Pei, Simon Fraser University, Canada
  • 1019, Pushing the envelope in graph compression, Panagiotis Liakos, University of Athens; Katia Papakonstantinopoulou, University of Athens; Michael Sioutis, Université Lille-Nord de France

DB Session 6 - Privacy and Streams
Time: 3:30pm - 5:00pm

  • 209, PraDa: Privacy-preserving Data-Deduplication-as-a-Service, Boxiang Dong (); Ruilin Liu (Stevens Institute of Technolog); Wendy Hui Wang ()
  • 1343, Aroma: A New Data Protection Method with Differential Privacy and Accurate Query Answering, Chunyao Song (); Tingjian Ge (Univ. of Massachusetts, Lowell)
  • 1026, Fast heuristics for near-optimal task allocation in data stream processing over clusters, Andreas Chatzistergiou (University of Edinburgh); Stratis Viglas (University of Edinburgh)
  • 1659, Truth Discovery in Data Streams: A Single-Pass Probabilistic Approach, Zhou Zhao (Hkust); James Cheng (CUHK); Wilfred Ng (HKUST)

IR Session 12: Efficiency
Time: 3:30pm - 5:00pm 

  • 583, Time-sensitive Personalized Query Auto-Completion, Fei Cai (University of Amsterdam); Shangsong Liang (University of Amsterdam); Maarten de Rijke (University of Amsterdam)
  • 394, Document Prioritization for Scalable Query Processing, Hao Wu (); Hui Fang (University of Delaware)
  • 779, Analytical Performance Modeling for Top-K Query Processing, Hao Wu (); Hui Fang (University of Delaware)
  • 1391, Compact auxiliary dictionaries for incremental compression of large repositories, Jiancong Tong (Nankai University); Anthony Wirth (The University of Melbourne); Justin Zobel (University of Melbourne)

IR Session 13: Domain, Semistructured, Mobile
Time: 3:30pm - 5:00pm 

  • 1349, Modelling Relevance towards Multiple Inclusion Criteria when Ranking Patients, Nut Limsopatham (University of Glasgow); Craig Macdonald (University of Glasgow); Iadh Ounis (University of Glasgow)
  • 478, Predicting Relationship Occurrence Time In Heterogeneous Networks Through Dynamic Frequent Prototype Network Mining, Yang Liu (NJIT); Songhua Xu (New Jersey Institute of Technology)
  • 98, Query-Driven Mining of Citation Networks for Patent Citation Retrieval and Recommendation, Parvaz Mahdabi (University of Lugano); Fabio Crestani (University of Lugano)
  • 375, Cross-Device Search, George Montanez (Carnegie Mellon University); Ryen White (Microsoft Research); Xiao Huang (Microsoft Bing)
KM Session 20: Entity and Feature Extraction
Time: 3:30pm - 5:00pm
  • 1298, Canonicalizing Open Knowledge Bases, Luis Galárraga, Télécom ParisTech; Geremy Heitz, Google Inc.; Kevin Murphy, Google Inc.; Fabian Suchanek, Telecom ParisTech
  • 73, A Fresh Look on Knowledge Bases: Distilling Named Events from News, Erdal Kuzey, Max Planck Institute, Germany; Jilles Vreeken, MPI; Gerhard Weikum, Max Planck Institute for Informatics
  • 851, Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning, Jia Wu, University of Technology, Sydney; Zhibin Hong, University of Technology Sydney; shirui Pan, ; Xingquan Zhu, Florida Atlantic University, USA; Chengqi Zhang, QCIS, University of Technology, Sydney
  • 1072, On Efficient Meta-Level Features for Effective Text Classification, Sérgio Canuto, UFMG; Thiago Salles, UFMG; Luiz Gonçalves, UFMG; Marcos Gonçalves, ; Gabriel Ramos, UFSJ; Leonardo Rocha, UFSJ; Thierson Rosa,
KM Session 21: Graph Data Mining II
Time: 3:30pm - 5:00pm
  • 1742, Scalable Vaccine Distribution in Large Graphs given Uncertain Data, Yao Zhang, Virginia Tech; Aditya Prakash, Virginia Tech
  • 1324, Component Detection in Directed Networks, Yu-Keng Shih, ; Sungmin Kim, ; Yiye Ruan, The Ohio State University; Jinxing Cheng, ; Abhishek Gattani, ; Tao Shi, ; Srinivasan Parthasarathy,
  • 474, MapReduce Triangle Enumeration With Guarantees, Ha-Myung Park, KAIST; Francesco Silvestri, University of Padova, Italy; U Kang, KAIST; Rasmus Pagh, IT University of Copenhagen, Denmark
  • 145, Hotspot Detection in a Service-Oriented Architecture, Pranay Anchuri, RPI; Roshan Sumbaly, LinkedIn; Sam Shah, LinkedIn