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Graph Manipulations for Fast Centrality Computation

The betweenness and closeness metrics are widely used metrics in many network analysis applications. Yet, they are expensive to compute. For that... (more)

Finding Dynamic Dense Subgraphs

Online social networks are often defined by considering interactions of entities at an aggregate level. For example, a call graph is formed among individuals who have called each other at least once; or at least k times. Similarly, in social-media platforms, we consider implicit social networks among users who have interacted in some way, e.g.,... (more)

Modeling Buying Motives for Personalized Product Bundle Recommendation

Product bundling is a marketing strategy that offers several products/items for sale as one bundle. While the bundling strategy has been widely used,... (more)

Combining Structured Node Content and Topology Information for Networked Graph Clustering

Graphs are popularly used to represent objects with shared dependency relationships. To date, all existing graph clustering algorithms consider each... (more)

An Influence Propagation View of PageRank

For a long time, PageRank has been widely used for authority computation and has been adopted as a solid baseline for evaluating social influence related applications. However, when measuring the authority of network nodes, the traditional PageRank method does not take the nodes’ prior knowledge into consideration. Also, the connection... (more)

Learning Multiple Diagnosis Codes for ICU Patients with Local Disease Correlation Mining

In the era of big data, a mechanism that can automatically annotate disease codes to patients’ records in the medical information system is in... (more)

Scalable and Efficient Flow-Based Community Detection for Large-Scale Graph Analysis

Community detection is an increasingly popular approach to uncover important structures in large networks. Flow-based community detection methods rely... (more)

Robust Graph Regularized Nonnegative Matrix Factorization for Clustering

Matrix factorization is often used for data representation in many data mining and machine-learning problems. In particular, for a dataset without any... (more)

Recommendations Based on Comprehensively Exploiting the Latent Factors Hidden in Items’ Ratings and Content

To improve the performance of recommender systems in a practical manner, several hybrid approaches... (more)

Spatial Prediction for Multivariate Non-Gaussian Data

With the ever increasing volume of geo-referenced datasets, there is a real need for better statistical estimation and prediction techniques for... (more)

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About TKDD 

The ACM Transactions on Knowledge Discovery from Data (TKDD) publishes original archival papers in the area of knowledge discovery from data and closely related disciplines.  The majority of the papers that appear in TKDD is expected to address the logical and technical foundation of knowledge discovery and data mining.

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Forthcoming Articles
Cross-Dependency Inference in Multi-layered Networks: A Collaborative Filtering Perspective

The increasingly connected world has catalyzed the fusion of networks from different domains, which facilitates the emergence of a new network modelmulti-layered networks. Examples of such kind of network systems include critical infrastructure networks, biological systems, organization-level collaborations, cross-platform e-commerce, etc. One crucial structure that distances multi-layered network to other network models is its cross-layer dependency, which describes the associations between the nodes from different layers. Needless to say, the cross-layer dependency in the network plays an essential role in many data mining applications like system robustness analysis and complex network control. However, it remains a daunting task to know the exact dependency relationships due to noise, limited accessibility, etc. In this paper, we tackle the cross-layer dependency inference problem by modeling it as a collective collaborative filtering problem. Based on this idea, we propose an effective algorithm FASCINATE that can reveal unobserved dependencies with linear complexity. Moreover, we derive FASCINATE-ZERO, an online variant of FASCINATE that can respond to a newly added node timely by checking its neighborhood dependencies.We perform extensive evaluations on real datasets to substantiate the superiority of our proposed approaches.

Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy Models

Modern visual analytic tools promote human-in-the-loop analysis but are limited in their ability to direct the user toward interesting and promising directions of study. This problem is especially acute when the analysis task is exploratory in nature, e.g., the discovery of potentially coordinated relationships in massive text datasets. Such tasks are very common in domains like intelligence analysis and security forensics where the goal is to uncover surprising coalitions bridging multiple types of relations. We introduce new maximum entropy models to discover surprising chains of relationships leveraging count data about entity occurrences in documents. These models are embedded in a visual analytic system called BiSet that treats relationship bundles as first class objects and directs the user toward promising lines of inquiry. We demonstrate how user input can judiciously direct analysis toward valid conclusions whereas a purely algorithmic approach could be led astray. Experimental results on both synthetic and real datasets from the intelligence community are presented.

comeNgo: A Dynamic Model for Social Group Evolution

How do social groups, such as Facebook groups and Wechat groups, dynamically evolve over time? How do people join the social groups, uniformly or with burst? What is the pattern of people quitting from groups? Is there a simple universal model to depict the come-and-go patterns of various groups? In this paper, we examine temporal evolution patterns of more than 100 thousands social groups with more than 10 million users. We surprisingly find that the evolution patterns of real social groups goes far beyond the classic dynamic models like SI and SIR. For example, we observe both diffusion and non-diffusion mechanism in the group joining process, and power-law decay in group quitting process, rather than exponential decay as expected in SIR model. Therefore we propose a new model comeNgo, a concise yet flexible dynamic model for group evolution. Our model has the following advantages: (a) unification power: it generalizes earlier theoretical models and different joining and quitting mechanisms we find from observation. (b) succinctness and interpretability: it contains only six parameters with clear physical meanings. (c) accuracy: it can capture various kinds of group evolution patterns preciously and the goodness of fit increase by 58% over baseline. (d) usefulness: it can be used in multiple application scenarios such as forecasting and pattern discovery.

Ranking Causal Anomalies for System Fault Diagnosis via Temporal and Dynamical Analysis on Vanishing Correlations

Detecting system anomalies is an important problem in many fields such as security, fault management, and industrial optimization. Recently, invariant network has shown to be powerful in characterizing complex system behaviours. In the invariant network, a node represents a system component and an edge indicates a stable, significant interaction between two components. Structures and evolutions of the invariance network, in particular the vanishing correlations, can shed important light on locating causal anomalies and performing diagnosis. However, existing approaches to detect causal anomalies with the invariant network often use the percentage of vanishing correlations to rank possible casual components, which have several limitations: 1) fault propagation in the network is ignored; 2) the root casual anomalies may not always be the nodes with a high-percentage of vanishing correlations; 3) temporal patterns of vanishing correlations are not exploited for robust detection; 4) prior knowledges on anomalous nodes are not exploited for (semi-)supervised detection. To address these limitations, in this paper we propose a network diffusion based framework to identify significant causal anomalies and rank them. Our approach can effectively model fault propagation over the entire invariant network, and can perform joint inference on both the structural, and the time-evolving broken invariance patterns. As a result, it can locate high-confidence anomalies that are truly responsible for the vanishing correlations, and can compensate for unstructured measurement noise in the system. Moreover, when the prior knowledges on the anomalous status of some nodes are available at certain time points, our approach is able to leverage them to further enhance the anomaly inference accuracy. When the prior knowledges are noisy, our approach also automatically learns reliable information and reduces impacts from noises. By performing extensive experiments on synthetic datasets, bank information system datasets, and coal plant cyber-physical system datasets, we demonstrate the effectiveness of our approach.

Graph-Based Fraud Detection in the Face of Camouflage

Given a bipartite graph of users and the products that they review, or followers and followees, how can we detect fake reviews or follows? Existing fraud detection methods (spectral, etc.) try to identify dense subgraphs of nodes that are sparsely connected to the remaining graph. Fraudsters can evade these methods using camouflage, by adding reviews or follows with honest targets so that they look "normal". Even worse, some fraudsters use hijacked accounts from honest users, and then the camouflage is indeed organic. Our focus is to spot fraudsters in the presence of camouflage or hijacked accounts. We propose FRAUDAR, an algorithm that (a) is camouflage-resistant, (b) provides upper bounds on the effectiveness of fraudsters, and (c) is effective in real-world data. Experimental results under various attacks show that FRAUDAR outperforms the top competitor in accuracy of detecting both camouflaged and non-camouflaged fraud. Additionally, in real-world experiments with a Twitter follower-followee graph of 1.47 billion edges, FRAUDAR successfully detected a subgraph of more than 4000 detected accounts, of which a majority had tweets showing that they used follower-buying services.

Assessing Human Error Against a Benchmark of Perfection

An increasing number of domains are providing us with detailed trace data on human decisions in settings where we can evaluate the quality of these decisions via an algorithm. Motivated by this development, an emerging line of work has begun to consider whether we can characterize and predict the kinds of decisions where people are likely to make errors. To investigate what a general framework for human error prediction might look like, we focus on a model system with a rich history in the behavioral sciences: the decisions made by chess players as they select moves in a game. We carry out our analysis at a large scale, employing datasets with several million recorded games, and using chess tablebases to acquire a form of ground truth for a subset of chess positions that have been completely solved by computers but remain challenging for even the best players in the world. We organize our analysis around three categories of features that we argue are present in most settings where the analysis of human error is applicable: the skill of the decision-maker, the time available to make the decision, and the inherent difficulty of the decision. We identify rich structure in all three of these categories of features, and find strong evidence that in our domain, features describing the inherent difficulty of an instance are significantly more powerful than features based on skill or time.

Partitioned Similarity Search with Cache-Conscious Data Traversal

All pairs similarity search (APSS) is used in many web search and data mining applications. Previous work has used comparison filtering, inverted indexing, and parallel accumulation of partial intermediate results to expedite its execution. However, shuffling intermediate results can incur significant communication overhead as data scales up. This paper studies a scalable two-step approach called Partition-based Similarity Search (PSS). The first stage is to partition the data and group potentially similar vectors. The second stage is to run a set of tasks where each task compares a partition of vectors with other candidate partitions. Because of data sparsity, accessing feature vectors in memory during runtime partition comparison incurs significant overhead due to the presence of memory hierarchy. This paper also optimizes data traversal with a cache-conscious layout to reduce the execution time through size-controlled data splitting and vector coalescing, and provides an analysis to guide the optimal choice for the parameter setting. The evaluation results show that the proposed approach leads to an early elimination of unnecessary I/O and data communication while sustaining parallel efficiency with one order of magnitude of performance improvement and it can also be integrated with LSH for approximated APSS.

Discovering Conditional Matching Rules

Matching dependencies (MDs) have recently been proposed to make data dependencies tolerant to various information representations, and found useful in data quality applications such as record matching. Instead of the strict equality function used in traditional dependency syntax (e.g., functional dependencies), MDs specify constraints based on similarity and identification. However, in practice, MDs may still be too strict and applicable only in a subset of tuples in a relation. Thereby, we study the conditional matching depen- dencies (CMDs), which bind matching dependencies only in a certain part of a table, i.e., MDs conditionally applicable in a subset of tuples. Compared to MDs, CMDs have more expressive power that enables them to satisfy wider application needs. In this paper, we study several important theoretical and practical issues of CMDs, including irreducible CMDs with respect to the implication, discovery of CMDs from data, reliable CMDs agreed most by a relation, approximate CMDs almost satisfied in a relation, and finally applications of CMDs in record matching and missing value repairing. Through an extensive experimental evaluation in real data sets, we demonstrate efficiency of proposed CMDs discovery algorithms and effectiveness of CMDs in real applications.

Mining Redescriptions with Siren

In many areas of science, scientists need to find distinct common characterizations of the same objects and, vice versa, identify sets of objects that admit multiple shared descriptions. For example, in biology, an important task is to identify the bioclimatic constraints that allow some species to survive, that is, to describe geographical regions in terms of both the fauna that inhabits them and their bioclimatic conditions. In data analysis, the task of automatically generating such alternative characterizations is called redescription mining. If a domain expert wants to use redescription mining in his research, merely being able to find them is not enough; he must also be able to understand the redescriptions found, adjust them to better match his domain knowledge, test alternative hypotheses with them, and guide the mining process towards results he considers interesting. To facilitate these goals, we introduce Siren, an interactive tool for mining and visualizing redescriptions. Siren allows for efficient, distributed mining of the redescriptions in an anytime fashion, various linked visualizations of the results, interaction with the results either directly or via the visualizations, and guiding the mining algorithm for specific redescriptions. In this paper we explain the features of Siren and why they are useful for redescription mining. We also propose two novel redescription mining algorithms that improve the generalizability of the results compared to the existing results.

Moving Destination Prediction Using Sparse Dataset: A Mobility Gradient Descent Approach

Moving destination prediction offers an important category of location-based applications and provides essential intelligence to business and governments. In existing studies, a common approach to destination prediction is to match the given query trajectory with massive recorded trajectories by similarity calculation. Unfortunately, due to privacy concerns, budget constraints and many other factors, in most circumstances, we can only obtain a sparse trajectory dataset. In sparse dataset, the available moving trajectories are far from enough to cover all possible query trajectories, thus the predictability of the matching-based approach will decrease remarkably. Towards destination prediction with sparse dataset, instead of searching similar trajectories over the sparse records, we alternatively examine the changes of distances from sampling locations to final destination on query trajectory. The underlying idea is intuitive: it is directly motivated by travel purpose, people always gets closer to the final destination during the movement. By borrowing the conception of gradient descent in optimization theory, we propose a novel moving destination prediction approach, namely MGDPre. Building upon the mobility gradient descent, MGDPre only investigates the behavior characteristics of query trajectory itself without matching historical trajectories, thus is applicable for sparse dataset. We evaluate our approach based on extensive experiments, using GPS trajectories generated by a sample of taxis over a ten-day period in Shenzhen city, China. The results demonstrate that the effectiveness, efficiency and scalability of our approach outperforms state-of-the-art baseline methods.

Bibliometrics

Publication Years 2007-2017
Publication Count 282
Citation Count 2431
Available for Download 282
Downloads (6 weeks) 3520
Downloads (12 Months) 30422
Downloads (cumulative) 189688
Average downloads per article 673
Average citations per article 9
First Name Last Name Award
John Canny ACM Doctoral Dissertation Award (1987)
Carlos A. Castillo ACM Senior Member (2014)
Chris Clifton ACM Senior Member (2006)
Graham R. Cormode ACM Distinguished Member (2013)
Benjamin Fung ACM Senior Member (2013)
John E Hopcroft ACM Karl V. Karlstrom Outstanding Educator Award (2008)
ACM A. M. Turing Award (1986)
Piotr Indyk ACM Paris Kanellakis Theory and Practice Award (2012)
Jon Kleinberg ACM AAAI Allen Newell Award (2014)
ACM Prize in Computing (2008)
Laks Lakshmanan ACM Distinguished Member (2016)
Chih-Jen Lin ACM Distinguished Member (2011)
ACM Senior Member (2010)
Chang-Tien Lu ACM Distinguished Member (2015)
Tao Mei ACM Distinguished Member (2016)
ACM Senior Member (2012)
Filippo Menczer ACM Distinguished Member (2013)
Sethuraman Panchanathan ACM Senior Member (2009)
Jian Pei ACM Senior Member (2007)
Domenico Sacca ACM Senior Member (2007)
Jeffrey D Ullman ACM Karl V. Karlstrom Outstanding Educator Award (1997)
Hui Xiong ACM Distinguished Member (2014)
ACM Senior Member (2010)
Qiang Yang ACM Distinguished Member (2011)
Mohammed Zaki ACM Distinguished Member (2010)
Ben Yanbin Zhao ACM Distinguished Member (2015)
Yu Zheng ACM Distinguished Member (2016)
ACM Senior Member (2011)
Zhi-Hua Zhou ACM Distinguished Member (2013)
ACM Senior Member (2011)
Zhi-Hua Zhou ACM Distinguished Member (2013)
ACM Senior Member (2011)

First Name Last Name Paper Counts
Christos Faloutsos 12
Jieping Ye 7
Hui Xiong 6
Jian Pei 5
Aristides Gionis 5
Tao Li 5
Philip Yu 4
Zhihua Zhou 4
Shenghuo Zhu 4
Heng Huang 4
John Lui 4
Feiping Nie 4
Huan Liu 4
Christopher Jermaine 4
John Hopcroft 3
Zhiwen Yu 3
Lise Getoor 3
Jure Leskovec 3
Malik Magdon-Ismail 3
Xiaoli Fern 3
Mingsyan Chen 3
Jilles Vreeken 3
Yun Chi 3
Yasushi Sakurai 3
Evimaria Terzi 3
Yihong Gong 3
Lei Tang 3
Bin Guo 3
Hong Cheng 3
Dingding Wang 3
Fabio Fassetti 3
Fabrizio Angiulli 3
Heikki Mannila 2
Panayiotis Tsaparas 2
Chengqi Zhang 2
Zhu Wang 2
Jianhui Chen 2
Yu Zhang 2
Fabrizio Sebastiani 2
Arthur Zimek 2
Yangqiu Song 2
Michalis Vazirgiannis 2
Junzhou Zhao 2
Xiaohong Guan 2
Geoffrey Webb 2
Indrajit Bhattacharya 2
Qiang Yang 2
Jin Huang 2
Panagis Magdalinos 2
Xiao Yu 2
Yanjie Fu 2
Charles Ling 2
Nikolaj Tatti 2
Andrea Esuli 2
JiLei Tian 2
Ping Luo 2
B Prakash 2
Yuru Lin 2
Shinjae Yoo 2
Ruoming Jin 2
Ian Davidson 2
Antonella Guzzo 2
Guofei Jiang 2
Jiawei Han 2
Jiawei Han 2
Antônio Loureiro 2
Hanghang Tong 2
Xiang Zhang 2
Daniel Kifer 2
Yan Liu 2
Laks Lakshmanan 2
Jimeng Sun 2
Don Towsley 2
Rita Chattopadhyay 2
Sucheta Soundarajan 2
Yong Ge 2
Xianchao Zhang 2
Dacheng Tao 2
Wei Ding 2
Belle Tseng 2
Enhong Chen 2
Qi Liu 2
Vivekanand Gopalkrishnan 2
Jie Tang 2
Eugene Agichtein 2
Kui Yu 2
Christopher Leckie 2
Carlotta Domeniconi 2
Sanjay Ranka 2
Jiliang Tang 2
Dantong Yu 2
Charalampos Tsourakakis 2
Jirong Wen 2
Martin Ester 2
Srinivasan Parthasarathy 2
Hari Sundaram 2
Spiros Papadimitriou 2
Joydeep Ghosh 2
Wei Fan 2
Dino Pedreschi 2
Kristina Lerman 2
Pinghui Wang 2
Hao Huang 2
Hong Qin 2
Yehuda Koren 2
Arnau Prat-Pérez 1
Josep Larriba-Pey 1
Risa Myers 1
Brian Gallagher 1
Qingtian Zeng 1
John Hutchins 1
Taneli Mielikäinen 1
Sethuraman Panchanathan 1
Abdullah Mueen 1
Yizhou Sun 1
Xiaofei He 1
Ji Liu 1
Manuel Gomez-Rodriguez 1
Muthuramakrishnan Venkitasubramaniam 1
Victor Lee 1
Zhi Yang 1
Yafei Dai 1
Robert Kleinberg 1
Pierluigi Crescenzi 1
Zijun Yao 1
Weiming Hu 1
Maoying Qiao 1
Wei Bian 1
Ying Jin 1
Hiroshi Mamitsuka 1
Xue Li 1
Guodong Long 1
Jie Cheng 1
Carlos Lorenzetti 1
Thomas Reichherzer 1
Dan Roth 1
Ephraim Korach 1
Jeffrey Ullman 1
Wenyuan Zhu 1
Kai Zheng 1
Zhongyuan Wang 1
Xunhua Guo 1
Sitaram Asur 1
Jerry Kiernan 1
Kevin Yip 1
Wei Zheng 1
Allon Percus 1
Zhenxing Wang 1
Ravi Konuru 1
Baoxing Huai 1
Hengshu Zhu 1
Nick Street 1
Anon Plangprasopchok 1
Shengrui Wang 1
Patrick Hung 1
Ganesh Ramesh 1
A Patterson 1
Manolis Kellis 1
Carlos Castillo 1
Tianbing Xu 1
Sanmay Das 1
Amit Dhurandhar 1
Beechung Chen 1
Fedja Hadzic 1
Elizabeth Chang 1
Aminul Islam 1
Feiyu Xiong 1
Fei Wang 1
Shiqiang Tao 1
Guoqiang Zhang 1
Li Wan 1
Weekeong Ng 1
Sethuraman Panchanathan 1
Michael Mampaey 1
Yu Lei 1
Haojun Zhang 1
Limsoon Wong 1
Maria Sapino 1
Shipeng Yu 1
Zhiting Hu 1
Pedro Melo 1
Yuan Jiang 1
Matteo Riondato 1
Qinbao Song 1
Michele Coscia 1
Yi Wang 1
João Gama 1
Charles Elkan 1
Jaideep Srivastava 1
Carlos Guestrin 1
Tomoharu Iwata 1
Naonori Ueda 1
Qi Lou 1
Wei Fan 1
Xifeng Yan 1
Julian McAuley 1
Bertil Schmidt 1
Yi Yang 1
Siyuan Liu 1
Quanzeng You 1
Polina Rozenshtein 1
Rezwan Ahmed 1
Wei Wei 1
Ana Maguitman 1
Filippo Menczer 1
Foto Afrati 1
Rómer Rosales 1
Xiaofang Zhou 1
Xindong Wu 1
Fangtao Li 1
Junjie Wu 1
Duygu Ucar 1
Ben Kao 1
David Cheung 1
Cheng Zeng 1
Mustafa Bilgic 1
Atreya Srivathsan 1
Tong Sun 1
Songhua Xu 1
Yanchi Liu 1
Kun Liu 1
Duo Zhang 1
Dmitry Pavlov 1
Raymond Ng 1
Piotr Indyk 1
Christopher Carothers 1
Anne Laurent 1
Satyanarayana Valluri 1
Ashish Verma 1
Raghu Ramakrishnan 1
Rong Ge 1
Byronju Gao 1
Yubao Wu 1
Maryam Tahani 1
Hamid Rabiee 1
Ying Wei 1
Li Tu 1
Saharon Rosset 1
Claudia Perlich 1
Seekiong Ng 1
Hong Xie 1
Jérémy Besson 1
Tuannhon Dang 1
Chengkai Li 1
Vasileios Kandylas 1
Salvatore Ruggieri 1
Ramana Kompella 1
Jing Zhang 1
Guangtao Wang 1
Xueying Zhang 1
Yiping Ke 1
Evrim Acar 1
Yang Zhou 1
Ben London 1
Joseph Ruiz Md 1
Charu Aggarwal 1
Neil Shah 1
Masahiro Kimura 1
Alexander Ihler 1
Kaiwei Chang 1
Forrest Briggs 1
Gustavo Batista 1
Qiang Zhu 1
Philip Yu 1
Jon Kleinberg 1
Jure Leskovec 1
Maya Bercovitch 1
Stefan Kramer 1
Huaimin Wang 1
Qiang You 1
Luke McDowell 1
Miao Tian 1
Naren Ramakrishnan 1
Qi Tian 1
Jennifer Neary 1
Minoru Kanehisa 1
Irwin King 1
Shanshan Feng 1
Guannan Liu 1
Ling Liu 1
Huilei He 1
Hua Wang 1
Shantanu Sharma 1
Yuanli Pei 1
Teresa Tjahja 1
Wenchih Peng 1
Zekai Gao 1
Sutharshan Rajasegarar 1
Jeffrey Chan 1
Laura Smith 1
Jin Zhang 1
Fei Zou 1
Christos Faloutsos 1
Nitin Agarwal 1
S Muthukrishnan 1
Kunta Chuang 1
Yao Wu 1
Siqi Shen 1
Xinran He 1
Lei Li 1
Ying Wang 1
Ke Wang 1
Jing Zhang 1
Benoît Dumoulin 1
Chris Ding 1
Xiuyao Song 1
John Gums 1
Yin Zhang 1
Zhongfei Zhang 1
Yunxin Zhao 1
Jude Shavlik 1
Beilun Wang 1
Chihya Shen 1
Zhitao Wang 1
Jingrui He 1
Ali Hemmatyar 1
Wei Cheng 1
Meng Jiang 1
Peng Cui 1
Yi Zhen 1
Qian Sun 1
Sibel Adalı 1
Xiaohui Lu 1
Domenico Saccà 1
Francesco Lupia 1
Nima Mirbakhsh 1
Antti Ukkonen 1
Xindong Wu 1
Zheng Wang 1
Johannes Schneider 1
Bin Cui 1
Juanzi Li 1
Patrick Haffner 1
Zhili Zhang 1
Qingyan Yang 1
Scott Burton 1
Christos Boutsidis 1
Bingsheng Wang 1
Hui Ke 1
Tamara Kolda 1
Jie Wang 1
Karthik Subbian 1
Galileo Namata 1
João Duarte 1
Yulan He 1
Gianlorenzo D'Angelo 1
Yu Zheng 1
Saurav Sahay 1
Xiaowen Ding 1
Bill Howe 1
Ahmet Sarıyüce 1
Sen Wang 1
Chong Peng 1
Jörg Sander 1
Siyuan Liu 1
Tanmoy Chakraborty 1
David Leake 1
Chenguang Wang 1
Zhoujun Li 1
Neilzhenqiang Gong 1
Yi Chang 1
Qiang Wei 1
Maria Halkidi 1
Lei Zou 1
Luming Zhang 1
Jian Wang 1
Manos Papagelis 1
Pritam Gundecha 1
Lei Chen 1
Edward Wild 1
Murat Kantarcıoğlu 1
John Guttag 1
Marc Plantevit 1
Jinlin Chen 1
Fan Guo 1
Shantanu Godbole 1
Alin Dobra 1
Binay Bhattacharya 1
Zoran Obradović 1
Wangchien Lee 1
Sri Ravana 1
Alex Beutel 1
Shiqiang Yang 1
Bin Zhou 1
Anushka Anand 1
Yicheng Tu 1
Hao Wang 1
Dan Simovici 1
Siddharth Gopal 1
Madhav Jha 1
Alice Leung 1
Renato Assunção 1
Subhabrata Sen 1
Dino Ienco 1
Rosa Meo 1
Pauli Miettinen 1
Eduardo Hruschka 1
Hongliang Fei 1
Jun Huan 1
Carlos Garcia-Alvarado 1
Ana Appel 1
Jeffreyxu Yu 1
Zhen Guo 1
Yashu Liu 1
Waynexin Zhao 1
Faming Lu 1
Andrew Mehler 1
Stephen North 1
Seungil Huh 1
Chojui Hsieh 1
Chihjen Lin 1
Zheng Wang 1
Thanawin Rakthanmanon 1
Jesin Zakaria 1
Tao Mei 1
Kosuke Hashimoto 1
Nobuhisa Ueda 1
Jie Tang 1
Haiqin Yang 1
Aparna Varde 1
Seunghee Bae 1
Can Chen 1
Erik Saule 1
Yunhong Hu 1
Ricardo Campello 1
Qiang Qu 1
Shuhui Wang 1
Antonio Ortega 1
Jeffrey Chan 1
Michael Houle 1
Dimitrios Gunopulos 1
Daxin Jiang 1
Muna Al-Razgan 1
Bin Liu 1
Pedro Vaz De Melo 1
Lei Zhang 1
Mohsen Bayati 1
Peilin Zhao 1
Raymond Wong 1
Ada Fu 1
Li Zheng 1
Noman Mohammed 1
Jaideep Vaidya 1
Collin Stultz 1
Boleslaw Szymanski 1
Maguelonne Teisseire 1
Paolo Boldi 1
Lini Thomas 1
Chao Liu 1
Sachindra Joshi 1
Tharam Dillon 1
Leonid Hrebien 1
Pei Yang 1
Li Li 1
Denian Yang 1
Zhishan Guo 1
Yunsing Koh 1
Silei Xu 1
Bo Liu 1
Yixin Chen 1
Xuanhong Dang 1
Shumo Chu 1
Rodrigo Alves 1
Juhua Hu 1
Yu Jin 1
Veerabhadran Baladandayuthapani 1
Timothy De Vries 1
Eric Xing 1
Albert Bifet 1
Xiaoming Li 1
Josep Brunat 1
Giulio Rossetti 1
Jiang Bian 1
Padhraic Smyth 1
Claudia Plant 1
Jiayu Pan 1
Brandon Westover 1
Eamonn Keogh 1
Ron Eyal 1
Avi Rosenfeld 1
Asaf Shabtai 1
Shifeng Weng 1
Junming Shao 1
Yllka Velaj 1
Xiaojun Chang 1
Lars Schmidt-Thieme 1
Michael Lyu 1
Dityan Yeung 1
Jevin West 1
Evangelos Papalexakis 1
Nicholas Sidiropoulos 1
George Karypis 1
Jilei Tian 1
Davoud Moulavi 1
Jun Yan 1
James Bezdek 1
Marimuthu Palaniswami 1
Jayavardhana Gubbi 1
Koji Hino 1
Masaru Kitsuregawa 1
Xiang Zhang 1
Jenwei Huang 1
James Bailey 1
Jianping Zhang 1
Manas Somaiya 1
Graham Cormode 1
Fernando Kuipers 1
Dick Epema 1
Linpeng Tang 1
Anthony Tung 1
Virgílio Almeida 1
Laiwan Chan 1
Adelelu Jia 1
Alexandru Iosup 1
Aniket Chakrabarti 1
Reza Zafarani 1
Saurabh Kataria 1
Amin Saberi 1
Matthew Rattigan 1
Geoffrey Barbier 1
Limin Yao 1
Cheukkwong Lee 1
Olvi Mangasarian 1
Chris Clifton 1
Mohammed Zaki 1
Jennifer Dy 1
Shaojun Wang 1
Henry Tan 1
Yanjun Qi 1
Theodoros Lappas 1
Munmun De Choudhury 1
Wenjie Li 1
Yada Zhu 1
Chen Chen 1
Tina Eliassi-Rad 1
Gianluigi Greco 1
Francesco Gullo 1
Guimei Liu 1
Loïc Cerf 1
Leman Akoglu 1
Min Ding 1
Gensheng Zhang 1
Jennifer Neville 1
Yiming Yang 1
Vassilios Vassiliadis 1
Kaiming Ting 1
Christophe Giraud-Carrier 1
Ayan Acharya 1
Sreangsu Acharyya 1
Arnold Boedihardjo 1
Changtien Lu 1
Zhiqiang Xu 1
Zhongfei Zhang 1
Matthew Rowe 1
Edward Chang 1
Aditya Menon 1
John Frenzel MD 1
Joshua Vogelstein 1
Hua Duan 1
Yandong Liu 1
Qiaozhu Mei 1
Takeshi Yamada 1
Suresh Iyengar 1
Jiawei Han 1
Ashwin Machanavajjhala 1
Erheng Zhong 1
Wei Fan 1
Ruud Van De Bovenkamp 1
Clyde Giles 1
Wei Peng 1
David Gleich 1
Steven Hoi 1
David Jensen 1
Tengfei Bao 1
Brook Wu 1
Glenn Fung 1
Zeeshan Syed 1
Kamalakar Karlapalem 1
Dale Schuurmans 1
Peer Kröger 1
Jean Boulicaut 1
Pradeep Tamma 1
Zengjian Hu 1
Boaz Ben-Moshe 1
Moshe Kam 1
Jieping Ye 1
Licong Cui 1
Xiaofeng Zhu 1
Neil Smalheiser 1
James Cheng 1
Shachar Kaufman 1
Ori Stitelman 1
Leland Wilkinson 1
José Balcázar 1
Hockhee Ang 1
Steven Hoi 1
Weekeong Ng 1
Mengling Feng 1
Dimitrios Mavroeidis 1
Céline Robardet 1
Xiao Jiang 1
Lyle Ungar 1
Franco Turini 1
Comandur Seshadhri 1
Luan Tang 1
Quanquan Gu 1
Xintao Wu 1
Nick Duffield 1
Chun Li 1
Jianyong Wang 1
Feitony Liu 1
Petros Drineas 1
Sanjay Chawla 1
Jinpeng Wang 1
Kedar Bellare 1
Brandon Norick 1
Ming Ji 1
Yuval Elovici 1
Ming Lin 1
Changshui Zhang 1
Qinli Yang 1
Josif Grabocka 1
Nicolas Schilling 1
Xiang Li 1
David Aha 1
Richard Xu 1
Sougata Mukherjea 1
Ashwin Ram 1
Zhanpeng Fang 1
Jing Peng 1
Daniel Halperin 1
Jian Cao 1
Jie Wang 1
Shiyou Qian 1
Kamer Kaya 1
Quan Sheng 1
Qiang Cheng 1
Yang Zhou 1
Xinjiang Lu 1
Animesh Mukherjee 1
Sriram Srinivasan 1
Niloy Ganguly 1
Sanjukta Bhowmick 1
Lingjyh Chen 1
Linhong Zhu 1
Makoto Yamada 1
Guoqing Chen 1
Dengyong Zhou 1
Ming Zhang 1
Biru Dai 1
Divesh Srivastava 1
Hungleng Chen 1
Zhenjie Zhang 1
Liang Hong 1
Hunghsuan Chen 1
Venu Satuluri 1
Rose Yu 1
Yao Zhang 1
Aisling Kelliher 1
Paul Castro 1
Lian Duan 1
Bruno Ribeiro 1
Luigi Pontieri 1
Bingrong Lin 1
Francesco Bonchi 1
Kasim Candan 1
Sunil Vadera 1
S Upham 1
Thomas Porta 1
Hongzhi Yin 1
Jeffrey Erman 1
Ming Li 1
Dora Erdős 1
Joydeep Ghosh 1
Kaiyuan Zhang 1
Carlos Ordonez 1
James Cheng 1
U Kang 1
Peter Christen 1
Daniel Dunlavy 1
David Dominguez-Sal 1
Fosca Giannotti 1
Christos Doulkeridis 1
Danai Koutra 1
Steven Skiena 1
Hiroshi Motoda 1
Chris Volinsky 1
Hsiangfu Yu 1
Aditya Parameswaran 1
Binbin Lin 1
Andreas Krause 1
Johannes Gehrke 1
Christo Wilson 1
Ben Zhao 1
Hoangvu Dang 1
Fen Xia 1
Linlin Zong 1
Yijuan Lu 1
Feng Liu 1
Yufeng Wang 1
Ernest Garcia 1
Shamkant Navathe 1
Wei Fan 1
Martin Rosvall 1
Guoqing Chen 1
Um&idot;t Catalyurek 1
Xiaojun Chang* 1
Lina Yao 1
Zhao Kang 1
Min Wang 1
Bin Li 1
Marc Maier 1
Lionel Ni 1
Mohamed Bouguessa 1
Mingxi Wu 1
Benjamin Fung 1
Ye Chen 1
John Canny 1
Dominique Laurent 1
Yeowwei Choong 1
Luca Becchetti 1
Ying Cui 1
Meghana Deodhar 1
Keli Xiao 1
Bo Long 1
Hans Kriegel 1
Gunjan Gupta 1
Ling Feng 1
Diana Inkpen 1
Hongxia Yang 1
Haoda Fu 1
Dawei Zhou 1
Jingrui He 1
Liming Chen 1
Maryam Ramezani 1
Wei Wang 1
Michalis Faloutsos 1
Kuan Zhang 1
Vetle Torvik 1
Luigi Moccia 1
Edoardo Serra 1
Shebuti Rayana 1
Claudio Schifanella 1
Min Wang 1
Nesreen Ahmed 1
Shuiwang Ji 1
Ali Pınar 1
Michail Vlachos 1
Ling Chen 1
Yang Liu 1
Chunxiao Xing 1
Dechuan Zhan 1
Ruggero Pensa 1
Saurabh Paul 1
Jose Hern´ndez-Orallo 1
Rainer Gemulla 1
Eli Upfal 1
Kazumi Saito 1
Dong Xin 1
Christian Böhm 1
Dafna Shahaf 1
Stephen Fienberg 1
Raviv Raich 1
Bilson Campana 1
Vibhor Rastogi 1
Deng Cai 1
Chengxiang Zhai 1
Sigal Sina 1
Sarit Kraus 1
Chris Ding 1
Lior Rokach 1
Dityan Yeung 1
Longjie Li 1
Xiaolin Wang 1
Tingting Gao 1
Bruno Abrahão 1
Lorenzo Severini 1
Ou Wu 1
Lei Ma 1
Xing Yong 1
T Murali 1
Kiyoko Aoki-Kinoshita 1
Ravi Janardan 1
Sudhir Kumar 1
Tiancheng Lou 1
Guna Seetharaman 1
Giacomo Berardi 1
Xiaotong Zhang 1
Han Liu 1
Kathleen Carley 1
Ming Zhang 1
Shlomi Dolev 1
Fang Wang 1
Haixun Wang 1
Zhirui Hu 1
Dheeraj Kumar 1
Dandan Qiao 1
Xiaodan Song 1
Yasuhiro Fujiwara 1
Wei Wang 1
ChienWei Chen 1
Weiyin Loh 1
John Salerno 1
Nitin Kumar 1
Flip Korn 1

Affiliation Paper Counts
National University of Defense Technology China 1
University of California, Berkeley 1
Wright-Patterson AFB 1
Eli Lilly and Company 1
Swiss Federal Institute of Technology, Zurich 1
Lawrence Livermore National Laboratory 1
University of Rochester 1
Naval Research Laboratory 1
Stevens Institute of Technology 1
Jerusalem College of Technology 1
University of California, Los Angeles 1
National Taiwan University of Science and Technology 1
Oracle Corporation 1
Lanzhou University 1
University of New South Wales 1
Northeastern University 1
Research Organization of Information and Systems National Institute of Informatics 1
University of Malaya 1
University of Milan 1
Temple University 1
Syracuse University 1
Umea University 1
Curtin University of Technology, Perth 1
US Naval Academy 1
University of Roma La Sapienza 1
Griffith University 1
University of New Mexico 1
Institute of Mathematics and Informatics Lithuanian 1
Tongji University 1
Amazon.com, Inc. 1
Harvard School of Engineering and Applied Sciences 1
Ariel University Center of Samaria 1
Siemens USA 1
Yuncheng University 1
Innopolis University 1
Ryukoku University 1
California State University Fullerton 1
Western Michigan University 1
University of Michigan 1
Anhui University 1
University of Ontario Institute of Technology 1
Universite de Cergy-Pontoise 1
National Technical University of Athens 1
Princeton University 1
Claremont Graduate University 1
Queens College, City University of New York 1
Iowa State University 1
University of Arkansas - Fayetteville 1
Yale University 1
University of Auckland 1
University of Missouri-Columbia 1
John F. Kennedy School of Government 1
University of South Florida Tampa 1
Valley Laboratory 1
University of Salford 1
Hong Kong Polytechnic University 1
Australian National University 1
Sabanci University 1
University of Texas at Dallas 1
University of Vermont 1
Harvard University 1
University of Arizona 1
Nanjing University of Science and Technology 1
Washington University in St. Louis 1
HP Labs 1
Universidad Politecnica de Valencia 1
BBN Technologies 1
Air Force Research Laboratory Information Directorate 1
University of Shizuoka 1
National Chiao Tung University Taiwan 1
MITRE Corporation 1
Norwegian University of Science and Technology 1
Indian Institute of Science 1
Zhejiang Wanli University 1
Aston University 1
University of Hawaii at Hilo 1
Colorado School of Mines 1
University of Louisiana at Lafayette 1
Sandia National Laboratories, California 1
John Carroll University 1
Radboud University Nijmegen 1
Brigham and Women's Hospital 1
University of Toronto 1
De Montfort University 1
Wright State University 1
Singapore Management University 1
Air Force Research Laboratory 1
Macquarie University 1
University of West Florida 1
Universite Montpellier 2 Sciences et Techniques 1
Nanjing University of Aeronautics and Astronautics 1
University of Florence 1
University of Connecticut 1
Hong Kong Red Cross Blood Transfusion Service 1
Nokia USA 1
Universite Claude Bernard Lyon 1 1
Lancaster University 1
Osaka University 1
University of Iowa 1
Max Planck Institute for Informatics 2
Shandong University of Science and Technology 2
Hefei University of Technology 2
Zhejiang University 2
Institute of High Performance Computing, Singapore 2
Johns Hopkins University 2
University of Electronic Science and Technology of China 2
Tel Aviv University 2
University of Minnesota System 2
University of Houston 2
The University of Hong Kong 2
Brigham Young University 2
The University of North Carolina at Charlotte 2
Soochow University 2
Brown University 2
Montclair State University 2
South National University 2
Hong Kong Baptist University 2
University of California, Davis 2
Drexel University 2
University of Kansas Lawrence 2
University of Nebraska at Omaha 2
University of Quebec in Outaouais 2
Institute for Systems and Computer Engineering of Porto 2
Indiana University 2
University of Virginia 2
Industrial Technology Research Institute of Taiwan 2
Missouri University of Science and Technology 2
University of Tokyo 2
University Michigan Ann Arbor 2
Nokia Corporation 2
University of Ottawa, Canada 2
University of Athens 2
IBM Zurich Research Laboratory 2
Kent State University 2
University of California, San Diego 2
University of Queensland 2
Istituto di Scienza e Tecnologie dell'Informazione A. Faedo 2
Microsoft Research Asia 2
Qatar Computing Research institute 2
International Institute of Information Technology Hyderabad 3
Bar-Ilan University 3
University of Hildesheim 3
Indian Institute of Technology, Kharagpur 3
University of Pennsylvania 3
University of California, Irvine 3
The University of British Columbia 3
University of Texas M. D. Anderson Cancer Center 3
University of Southern California, Information Sciences Institute 3
University of Washington, Seattle 3
University of Kentucky 3
INSA Lyon 3
Academia Sinica Taiwan 3
George Mason University 3
Institute of Automation Chinese Academy of Sciences 3
Xerox Corporation 3
Chinese Academy of Sciences 3
Binghamton University State University of New York 3
Italian National Research Council 3
University of Massachusetts Boston 3
University of Sydney 3
Microsoft Corporation 3
University of California, Santa Barbara 3
Wuhan University 3
Southern Illinois University at Carbondale 3
University of Alberta 3
Johannes Gutenberg University Mainz 3
Emory University 4
Institute for Infocomm Research, A-Star, Singapore 4
Google Inc. 4
Brookhaven National Laboratory 4
Universitat Politecnica de Catalunya 4
University of Sao Paulo 4
The University of Western Ontario 4
IBM Research 4
Beihang University 4
National University of Singapore 4
Athens University of Economics and Business 4
Monash University 4
Boston University 4
Massachusetts Institute of Technology 4
Shanghai Jiaotong University 4
Sharif University of Technology 4
University of Pisa 4
Rutgers, The State University of New Jersey 4
Yahoo Research Barcelona 4
Case Western Reserve University 5
University of Texas at San Antonio 5
Ohio State University 5
Dalian University of Technology 5
Rice University 5
Purdue University 5
University of Turin 5
University of Antwerp 5
Renmin University of China 5
Sandia National Laboratories 5
New Jersey Institute of Technology 5
The University of North Carolina at Chapel Hill 5
University of Southern California 5
University of Texas System 5
Pennsylvania State University 6
Delft University of Technology 6
AT&T Laboratories Florham Park 6
Kyoto University 6
University of Massachusetts Amherst 6
Nippon Telegraph and Telephone Corporation 6
Ludwig Maximilian University of Munich 6
University of Minnesota Twin Cities 6
Yahoo Inc. 6
University of Texas at Austin 7
University of Florida 7
University of Science and Technology of China 7
University of Maryland 7
Microsoft Research 7
Ben-Gurion University of the Negev 7
University of California, Riverside 7
Federal University of Minas Gerais 7
University of Wisconsin Madison 7
Aalto University 7
Rutgers University-Newark Campus 8
Nanyang Technological University 8
Oregon State University 8
Xi'an Jiaotong University 8
Stony Brook University 8
Virginia Tech 8
Nanjing University 8
Yahoo Research Labs 9
Georgia Institute of Technology 9
IBM Thomas J. Watson Research Center 9
Florida International University 9
Peking University 9
National Taiwan University 10
University of Melbourne 10
University of Illinois at Chicago 10
University of Texas at Arlington 10
Stanford University 10
Rensselaer Polytechnic Institute 11
Hong Kong University of Science and Technology 11
University of Calabria 12
Northwestern Polytechnical University China 12
Cornell University 12
University of Technology Sydney 13
NEC Laboratories America, Inc. 15
Simon Fraser University 16
University of Illinois at Urbana-Champaign 18
Chinese University of Hong Kong 19
Tsinghua University 26
Carnegie Mellon University 33
Arizona State University 45

ACM Transactions on Knowledge Discovery from Data (TKDD)
Archive


2017
Volume 11 Issue 3, March 2017  Issue-in-Progress

2016
Volume 11 Issue 2, December 2016
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Volume 10 Issue 4, July 2016 Special Issue on SIGKDD 2014, Special Issue on BIGCHAT and Regular Papers
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2015
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2014
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Volume 8 Issue 4, October 2014
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2013
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2012
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Volume 5 Issue 4, February 2012

2011
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2010
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Volume 4 Issue 3, October 2010
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2009
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2008
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Volume 1 Issue 4, January 2008

2007
Volume 1 Issue 3, December 2007
Volume 1 Issue 2, August 2007
Volume 1 Issue 1, March 2007
 
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