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Introduction to Special Issue on the Best Papers from KDD 2016

This issue contains the best papers from the ACM KDD Conference 2016. As is customary at KDD, special issue papers are invited only from the research... (more)

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... (more)

comeNgo

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 article, we examine temporal evolution... (more)

Cross-Dependency Inference in Multi-Layered Networks

The increasingly connected world has catalyzed the fusion of networks from different domains, which facilitates the emergence of a new network... (more)

TRIÈST

“Ogni lassada xe persa.”1-- Proverb from Trieste, Italy. We present trièst, a suite of one-pass streaming algorithms to compute unbiased, low-variance, high-quality approximations of the global and local (i.e., incident to each vertex) number of triangles in a fully dynamic graph represented as an adversarial stream of edge... (more)

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... (more)

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... (more)

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... (more)

Query-Driven Learning for Predictive Analytics of Data Subspace Cardinality

Fundamental to many predictive analytics tasks is the ability to estimate the cardinality (number of data items) of multi-dimensional data subspaces,... (more)

Large-Scale Online Feature Selection for Ultra-High Dimensional Sparse Data

Feature selection (FS) is an important technique in machine learning and data mining, especially for large-scale high-dimensional data. Most existing... (more)

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About TKDD 

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
Community Detection Using Diffusion Information

Community detection in social networks has become a popular topic of research during the last decade. There exist a variety of algorithms for modularizing the network graph into different communities. However, they mostly assume that partial or complete information of the network graphs are available which is not feasible in many cases. In this paper, we focus on detecting communities by exploiting their diffusion information. We utilize the Conditional Random Field (CRF) to model the behavior of diffusion process. The proposed method (CoDi) does not require any prior knowledge of the network structure or specific properties of communities. Furthermore, in contrast to the structure based community detection methods, this method is able to identify the hidden communities. The experimental results indicate considerable improvements in detecting communities based on accuracy, scalability and real cascade information measures.

Collaborative Filtering with Topic and Social Latent Factors Incorporating Implicit Feedback

Recommender systems (RSs) provide an effective way of alleviating the information overload problem by selecting personalized items for different users. Latent factors based collaborative filtering (CF) has become the popular approaches for RSs due to its accuracy and scalability. Recently, online social networks and user-generated content provide diverse sources for recommendation beyond ratings. Although social matrix factorization (Social MF) and topic matrix factorization (Topic MF) successfully exploit social relations and item reviews, respectively; both of them ignore some useful information. In this paper, we investigate the effective data fusion by combining the aforementioned approaches. First, we propose a novel model MR3 to jointly model three sources of information (i.e., ratings, item reviews, and social relations) effectively for rating prediction by aligning the latent factors and hidden topics. Second, we incorporate the implicit feedback from ratings into the proposed model to enhance its capability and to demonstrate its flexibility. We achieve more accurate rating prediction on real-life datasets over various state-of-the-art methods. Furthermore, we measure the contribution from each of the three data sources and the impact of implicit feedback from ratings, followed by the sensitivity analysis of hyperparameters. Empirical studies demonstrate the effectiveness and efficacy of our proposed model and its extension.

Local Spectral Clustering for Overlapping Community Detection

Large graphs arise in a number of contexts and understanding their structure and extracting information from them is an important research area. Early algorithms on mining communities have focused on the global structure, and often run in time functional to the size of the entire graph. Nowadays, as we often explore networks with billions of vertices and find communities of size hundreds, it is crucial to shift our attention from macroscopic structure to microscopic structure in large networks. A growing body of work has been adopting local expansion methods in order to identify the community members from a few exemplary seed members. In this paper, we propose a novel approach for finding overlapping communities called LEMON (Local Expansion via Minimum One Norm). The algorithm finds the community by seeking a sparse vector in the span of the local spectra such that the seeds are in its support. We show that LEMON can achieve the highest detection accuracy among state-of-the-art proposals. The running time depends on the size of the community rather than that of the entire graph. The algorithm is easy to implement, and is highly parallelizable. We further provide theoretical analysis on the local spectral properties, bounding the measure of tightness of extracted community in terms of the eigenvalues of graph Laplacian. Moreover, given that networks are not all similar in nature, a comprehensive analysis on how the local expansion approach is suited for uncovering communities in different networks is still lacking. We thoroughly evaluate our approach using both synthetic and real-world datasets across different domains, and analyze the empirical variations when applying our method to inherently different networks in practice. In addition, the heuristics on how the seed set quality and quantity would affect the performance are provided.

Systematic Review of Clustering high-dimensional and Large Data Sets

Technological advancement has enabled us to store and process huge amount of data in relatively short spans of time. Nature of data is rapidly increasing its dimensionality to become multi and high dimensional. There is an immediate need to expand our focus to include analysis of high dimensional data and large data sets. Data analysis is becoming a mammoth task due to incremental increase in data volume and complexity in terms of heterogony of data. It is due to this dynamic comput- ing environment that the existing techniques either need to be modified or discarded to handle new data in multiple high dimensions. Data clustering is a tool that is used in many disciplines, including data mining, so that meaningful knowledge can be extracted from seemingly unstructured data. The major aim is to understand the problem of clustering and various approaches addressing this problem. This paper discusses the process of clustering from both micro (data treating) and macro (Overall Clustering Process) views. Various distance and similarity measures, which form the cornerstone of effective data clustering are also identified. Further, an in-depth analysis of different clustering approaches focused on data mining, dealing with large-scale data sets is given. These approaches are also comprehensively compared to bring out a clear differentiation among them. This paper also surveys the problem of high dimensional data and the existing approaches, which helps to make it more negotiable. It also explores the latest trends in cluster analysis and the real life applications of this concept. This survey is exhaustive as it tries to cover all the aspects of clustering in the field of data mining.

Profit Maximization with Sufficient Customer Satisfactions

In many commercial campaigns, we observe that there exists a trade-off between the number of customers satisfied by the company and the profit gained. Merely satisfying as many customers as possible or maximizing the profit is not desirable. To this end, in this paper, we propose a new problem called k-Satisfiability Assignment for Maximizing the Profit (k-SAMP) where k is a user parameter and a non-negative integer. Given a set P of products and a set O of customers, k-SAMP is to find an assignment between P and O such that at least k customers are satisfied in the assignment and the profit incurred by this assignment is maximized. Although we find that this problem is closely related to two classic computer science problems, namely maximum weight matching and maximum matching, the techniques developed for these classic problems cannot be adapted to our k-SAMP problem. In this work, we design a novel algorithm called Adjust for the k-SAMP problem. Given an assignment A, Adjust iteratively increases the profit of A by adjusting some appropriate matches in A while keeping at least k customers satisfied in A. We prove that Adjust returns a global optimum. Extensive experiments were conducted which verified the efficiency of Adjust.

De-anonymizing clustered social networks by percolation graph matching

On-line social networks offer the opportunity to collect a huge amount of valuable information about billions of users. The analysis of this data by service providers and unintended third parties are posing serious treats to user privacy. In particular, recent work has shown that users participating in more than one on-line social network can be identified based only on the structure of their links to other users. An effective tool to de-anonymize social network users is represented by graph matching algorithms. Indeed, by exploiting a sufficiently large set of seed nodes, a percolation process can correctly match almost all nodes across the different social networks. In this paper, we show the crucial role of clustering, which is a relevant feature of social network graphs (and many other systems). Clustering has both the effect of making matching algorithms more prone to errors, and the potential to greatly reduce the number of seeds needed to trigger percolation. We show these facts by considering a fairly general class of random geometric graphs with variable clustering level. We assume that seeds can be identified in particular sub-regions of the network graph, while no a-priori knowledge about the location of the other nodes is required. Under these conditions, we show how clever algorithms can achieve surprisingly good performance while limiting the number of matching errors.

Mining Overlapping Communities and Inner Role Assignments through Bayesian Mixed-Membership Models of Networks with Context-Dependent Interactions

The seamless integration of community discovery and role assignment has been recently proposed as an unsupervised approach to the exploratory analysis of networks, aimed to unveil the participation of nodes in multiple overlapping communities along with the roles played therein. One limitation of these prototypical research efforts is that the formation of ties is not truly realistic, since it does not account for a fundamental aspect of link establishment in real-world networks, i.e., the explicative reasons that cause interactions among nodes. Such reasons can be abstractedly interpreted as generic requirements of nodes that are met by other nodes and essentially pertain both to the nodes themselves and to their different interaction contexts (i.e., the respective communities and roles). In this manuscript, we present two new model-based machine-learning approaches, wherein community discovery and role assignment are tightly integrated and simultaneously performed through approximate posterior inference in Bayesian mixed-membership models of directed networks. The two proposed models account for the explicative reasons governing link establishment in terms of node-specific and contextual latent interaction factors. The former are inherently characteristic of nodes, while the latter are characterizations of nodes in the context of the individual communities and roles. The generative process of the devised models assigns nodes to communities with respective roles and connects them through directed links, which are probabilistically governed by their node-specific and contextual interaction factors. The two proposed models differ in the impact of the contextual interaction factors on link generation. We develop MCMC algorithms implementing approximate posterior inference and parameter estimation within our models. Finally, we demonstrate their superiority in community compactness and link prediction via an intensive comparative experimentation on real-world and synthetic networks.

Joint Representation Learning for Location-Based Social Networks with Multi-Grained Sequential Contexts

This paper studies the problem of learning embedding representations for Location-Based Social Networks (LBSN), which is useful in many tasks such as location recommendation and link prediction. Existing network embedding methods mainly focus on capturing topology patterns reflected in social connections, hence, the important data type, \ie check-in sequences, cannot be modeled. In this paper, we propose a representation learning method for LBSNs called as \textbf{JRLM}, which jointly model both social connections and check-in sequences. To capture sequential relatedness, JRLM characterizes two levels of sequential contexts, namely fine-grained and coarse-grained contexts. We present a learning algorithm tailored to the hierarchial architecture of the proposed model. We conduct extensive experiments on two important applications using real-world datasets. The experimental results demonstrate the superiority of our model. The proposed model can generate representations for both users and locations in the same embedding space, which can be exploited in multiple LBSN tasks.

Discovering Communities and Anomalies in Attributed Graphs: Interactive Visual Exploration and Summarization

Given a neighborhood in a graph with node attributes (e.g., a community, cluster, or group of connected nodes), how can we quantify its quality? Existing measures either only consider the connectedness of the nodes inside the neighborhood and ignore the cross-edges at the boundary (e.g., density) or only quantify the structure of the neighborhood and ignore the attributes (e.g., conductance). In this work, we first introduce a new measure to quantify the normality of an attributed neighborhood. Our normality measure carefully utilizes structure and attributes together to quantify both the internal consistency and external separability. We then formulate an objective function to automatically infer a few attributes (called the neighborhood focus) and respective attribute weights, so as to maximize the normality score of a neighborhood. Most notably, unlike many other approaches, our measure allows for many cross-edges as long as they can be exonerated; i.e., either (i) are expected under a null model, and/or (ii) their boundary nodes do not exhibit the focus attributes. Finally, we propose AMEN, an algorithm that simultaneously discovers the neighborhoods and their respective focus in a given graph, with a goal to maximize the total normality. Neighborhoods for which a focus that yields high normality cannot be found are considered low quality or anomalous. As the experiments on real-world attributed graphs show, AMEN effectively finds anomalous neighborhoods and outperforms several existing measures and methods, such as conductance, density, OddBall, and SODA.

Data Stream Evolution Diagnosis using Recursive Wavelet Density Estimators

Data streams are a new class of data that is becoming pervasively important in a wide range of applications, ranging from sensor networks, environmental monitoring to finance. In this paper, we propose a novel framework for online characterisation and diagnosing the evolution of multidimensional streaming data which incorporates Recursive Wavelet Density Estimators into the context of Velocity Density Estimation. In the proposed framework changes in streaming data are characterised by the use of local and global evolution coefficients. In addition, we propose for the analysis of changes in the correlation structure of the data a recursive implementation of Pearson correlation coefficient using exponential discounting. Two visualisation tools namely, temporal and spatial velocity profiles, are extended in the context of our framework. Three are the main advantages of the proposed method over previous approaches: 1) the memory storage required is minimal and independent of any window size; 2) it has a significantly lower computational complexity; and 3) it makes possible the fast diagnosis of data evolution at all dimensions and at relevant combinations of dimensions with only one pass of the data. With the help of three examples, we show the frameworks relevance in a change detection context and its potential capability for real world applications.

GOOWE: Geometrically Optimum and Online-Weighted Ensemble Classifier for Evolving Data Streams

Designing adaptive classifiers for an evolving data stream is a challenging task due to its size and dynamically changing nature. Combining individual classifiers in an online setting, the ensemble approach, is one of the well-known solutions. It is possible that a subset of classifiers in the ensemble outperforms others in a time-varying fashion. However, optimum weight assignment for component classifiers is a problem which is not yet fully addressed in online evolving environments. We propose a novel data stream ensemble classifier, called Geometrically Optimum and Online-Weighted Ensemble (GOOWE), which assigns optimum weights to the component classifiers using a sliding window containing the most recent data instances. We map vote scores of individual classifiers and true class labels into a spatial environment. Based on the Euclidean distance between vote scores and ideal-points, and using the linear least squares (LSQ) solution, we present a novel dynamic and online weighting approach. While LSQ is used for batch mode ensemble classifiers, it is the first time that we adapt and use it for online environments by providing a spatial modeling of online ensembles. In order to show the robustness of the proposed algorithm, we use real-world datasets and synthetic data generators using the MOA libraries. We compare our results with 8 state-of-the-art ensemble classifiers in a comprehensive experimental environment. Our experiments show that GOOWE provides improved reactions to different types of concept drift compared to our baselines. The statistical tests indicate a significant improvement in accuracy, with conservative time and memory requirements.

Bibliometrics

Publication Years 2007-2017
Publication Count 299
Citation Count 2699
Available for Download 299
Downloads (6 weeks) 2710
Downloads (12 Months) 29433
Downloads (cumulative) 203026
Average downloads per article 679
Average citations per article 9
First Name Last Name Award
Foto Afrati ACM Fellows (2014)
Charu Chandra Aggarwal ACM Fellows (2013)
John Canny ACM Doctoral Dissertation Award (1987)
Carlos A. Castillo ACM Senior Member (2014)
Ming-Syan Chen ACM Fellows (2006)
Chris Clifton ACM Senior Member (2006)
Graham R. Cormode ACM Distinguished Member (2013)
Christos Faloutsos ACM Fellows (2010)
Benjamin Fung ACM Senior Member (2013)
Johannes Gehrke ACM Fellows (2014)
Lee Giles ACM Fellows (2006)
John Guttag ACM Fellows (2006)
Jiawei Han ACM Fellows (2003)
John E Hopcroft ACM Karl V. Karlstrom Outstanding Educator Award (2008)
ACM Fellows (1994)
ACM A. M. Turing Award (1986)
Piotr Indyk ACM Fellows (2015)
ACM Paris Kanellakis Theory and Practice Award (2012)
Masaru Kitsuregawa ACM Fellows (2012)
Jon Kleinberg ACM AAAI Allen Newell Award (2014)
ACM Fellows (2013)
ACM Prize in Computing (2008)
Sarit Kraus ACM Fellows (2014)
Hans-Peter Kriegel ACM Fellows (2009)
Laks Lakshmanan ACM Distinguished Member (2016)
Ming Li ACM Fellows (2006)
Chih-Jen Lin ACM Fellows (2015)
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)
S. Muthukrishnan ACM Fellows (2010)
Shamkant B Navathe ACM Fellows (2014)
Sethuraman Panchanathan ACM Senior Member (2009)
Jian Pei ACM Fellows (2015)
ACM Senior Member (2007)
Raghu Ramakrishnan ACM Fellows (2001)
Dan Roth ACM Fellows (2011)
Michael Rung-Tsong Lyu ACM Fellows (2015)
Domenico Sacca ACM Senior Member (2007)
Padhraic Smyth ACM Fellows (2013)
Divesh Srivastava ACM Fellows (2011)
Jie Tang ACM Senior Member (2017)
Donald F Towsley ACM Fellows (1997)
Jeffrey D Ullman ACM Karl V. Karlstrom Outstanding Educator Award (1997)
ACM Fellows (1995)
Eli Upfal ACM Fellows (2005)
Limsoon Wong ACM Fellows (2013)
Hui Xiong ACM Distinguished Member (2014)
ACM Senior Member (2010)
Qiang Yang ACM Distinguished Member (2011)
Philip S Yu ACM Fellows (1997)
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 Fellows (2016)
ACM Distinguished Member (2013)
ACM Senior Member (2011)
Zhi-Hua Zhou ACM Fellows (2016)
ACM Distinguished Member (2013)
ACM Senior Member (2011)

First Name Last Name Paper Counts
Christos Faloutsos 15
Hui Xiong 7
Jieping Ye 7
Jian Pei 5
Aristides Gionis 5
Tao Li 5
Philip YU 4
Zhiwen Yu 4
Zhihua Zhou 4
Shenghuo Zhu 4
Heng Huang 4
John Lui 4
Feiping Nie 4
Bin Guo 4
Huan Liu 4
Hong Cheng 4
Christopher Jermaine 4
Dingding Wang 3
Lei Tang 3
Chengqi Zhang 3
Guofei Jiang 3
John Hopcroft 3
Fabrizio Angiulli 3
Lise Getoor 3
Hanghang Tong 3
Jure Leskovec 3
Malik Magdon-Ismail 3
Mingsyan Chen 3
Qi Liu 3
Enhong Chen 3
Xiaoli Fern 3
Jilles Vreeken 3
Yun Chi 3
Yasushi Sakurai 3
Evimaria Terzi 3
Yihong Gong 3
Fabio Fassetti 3
Charu Aggarwal 2
Jon Kleinberg 2
Neil Shah 2
Wei Wang 2
Eli Upfal 2
Mohamed Bouguessa 2
Spiros Papadimitriou 2
Joydeep Ghosh 2
Martin Ester 2
Wei Fan 2
Dino Pedreschi 2
Jirong Wen 2
Pinghui Wang 2
Hao Huang 2
Hong Qin 2
Chen Chen 2
Kristina Lerman 2
Yehuda Koren 2
Heikki Mannila 2
Panayiotis Tsaparas 2
Zhu Wang 2
Jianhui Chen 2
Yu Zhang 2
Arthur Zimek 2
Michalis Vazirgiannis 2
Junzhou Zhao 2
Xiaohong Guan 2
Wei Cheng 2
Peng Cui 2
Geoffrey Webb 2
Jin Huang 2
Xiao Yu 2
Panagis Magdalinos 2
Qiang Yang 2
Yangqiu Song 2
Yanjie Fu 2
Charles Ling 2
Nikolaj Tatti 2
Andrea Esuli 2
Petros Drineas 2
JiLei Tian 2
Ping Luo 2
B Prakash 2
Yuru Lin 2
Shinjae Yoo 2
Steven Hoi 2
Ian Davidson 2
Antonella Guzzo 2
Jiawei Han 2
Ruoming Jin 2
Antônio Loureiro 2
Lei Chen 2
Alex Beutel 2
Daniel Kifer 2
Jiawei Han 2
Xiang Zhang 2
Fabrizio Sebastiani 2
Laks Lakshmanan 2
Yan Liu 2
Jimeng Sun 2
Indrajit Bhattacharya 2
Don Towsley 2
Matteo Riondato 2
Rita Chattopadhyay 2
Sucheta Soundarajan 2
Yong Ge 2
Xianchao Zhang 2
Dacheng Tao 2
Belle Tseng 2
Vivekanand Gopalkrishnan 2
Jie Tang 2
Wei Ding 2
Eugene Agichtein 2
Christopher Leckie 2
Carlotta Domeniconi 2
Sanjay Ranka 2
Jiliang Tang 2
Dantong Yu 2
Charalampos Tsourakakis 2
Kui Yu 2
Srinivasan Parthasarathy 2
Hari Sundaram 2
Jie Wang 1
Shiyou Qian 1
Dengyong Zhou 1
Ming Zhang 1
Biru Dai 1
Xinjiang Lu 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
Siyuan Liu 1
Jingchao Ni 1
Alceu Costa 1
Yihan Wang 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
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
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
Kedar Bellare 1
Brandon Norick 1
Ming Ji 1
Yuval Elovici 1
Ming Lin 1
Changshui Zhang 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
Allon Percus 1
Xunhua Guo 1
Sri Ravana 1
Shiqiang Yang 1
Zoran Obradović 1
Wangchien Lee 1
Qinli Yang 1
Josif Grabocka 1
Nicolas Schilling 1
David Aha 1
Richard Xu 1
Sougata Mukherjea 1
Ashwin Ram 1
Zhanpeng Fang 1
Jing Peng 1
Yang Zhou 1
Kamer Kaya 1
Quan Sheng 1
Qiang Cheng 1
Maha Alabduljalil 1
Daniel Halperin 1
Xiang Li 1
Jian Cao 1
Qinbao Song 1
Michele Coscia 1
Yi Wang 1
Charles Elkan 1
Jaideep Srivastava 1
João Gama 1
Carlos Guestrin 1
Tomoharu Iwata 1
Naonori Ueda 1
Qi Lou 1
Wei Fan 1
Xifeng Yan 1
Julian McAuley 1
Sanjukta Bhowmick 1
Sriram Srinivasan 1
Niloy Ganguly 1
Animesh Mukherjee 1
Lingjyh Chen 1
Linhong Zhu 1
Makoto Yamada 1
Guoqing Chen 1
Feiyu Xiong 1
Fei Wang 1
Shiqiang Tao 1
Guoqiang Zhang 1
Bertil Schmidt 1
Yi Yang 1
Quanzeng You 1
Tao Mei 1
Kosuke Hashimoto 1
Nobuhisa Ueda 1
Jie Tang 1
Haiqin Yang 1
Aparna Varde 1
Ricardo Campello 1
Can Chen 1
Erik Saule 1
Tao Ku 1
Yunhong Hu 1
Seunghee Bae 1
Qiang Qu 1
Shuhui Wang 1
Abhisek Kundu 1
Pedro Vaz De Melo 1
Jeffrey Chan 1
Michael Houle 1
Dimitrios Gunopulos 1
Gianlorenzo D'Angelo 1
Yu Zheng 1
Saurav Sahay 1
Xiaowen Ding 1
Jörg Sander 1
Ahmet Sarıyüce 1
Changtien Lu 1
Sen Wang 1
Chong Peng 1
Bill Howe 1
Siyuan Liu 1
Nicholasjing Yuan 1
Yu Yang 1
Maria Halkidi 1
David Gleich 1
Steven Hoi 1
Lei Zou 1
Luming Zhang 1
Jian Wang 1
Manos Papagelis 1
Ruud Van De Bovenkamp 1
Clyde Giles 1
Wei Peng 1
David Jensen 1
Tengfei Bao 1
Brook Wu 1
Tao Mei 1
Essam Algizawy 1
Deb Roy 1
Glenn Fung 1
Zeeshan Syed 1
Kamalakar Karlapalem 1
Dale Schuurmans 1
Peer Kröger 1
Céline Robardet 1
Jean Boulicaut 1
Pradeep Tamma 1
Zengjian Hu 1
Boaz Ben-Moshe 1
Shachar Kaufman 1
Ori Stitelman 1
Leland Wilkinson 1
José Balcázar 1
Hockhee Ang 1
Mengling Feng 1
Xiao Jiang 1
Lyle Ungar 1
Franco Turini 1
Comandur Seshadhri 1
Luan Tang 1
Quanquan Gu 1
Dimitrios Mavroeidis 1
Neil Smalheiser 1
James Cheng 1
Weekeong Ng 1
Xintao Wu 1
Jie Cheng 1
Sitaram Asur 1
Jerry Kiernan 1
Kevin Yip 1
Wei Zheng 1
Ravi Konuru 1
Zhenxing Wang 1
Baoxing Huai 1
Hengshu Zhu 1
Nick Street 1
Pritam Gundecha 1
Lei Ying 1
Yu Shi 1
Tianyang Zhang 1
Shiqiang Yang 1
Agma Traina 1
Mostafa Mohsenvand 1
Fan Guo 1
Edward Wild 1
Murat Kantarcıoğlu 1
John Guttag 1
Marc Plantevit 1
Jinlin Chen 1
Shantanu Godbole 1
Alin Dobra 1
Binay Bhattacharya 1
Bin Zhou 1
Yicheng Tu 1
Dan Simovici 1
Hao Wang 1
Siddharth Gopal 1
Madhav Jha 1
Alice Leung 1
Renato Assunção 1
Dino Ienco 1
Rosa Meo 1
Subhabrata Sen 1
Pauli Miettinen 1
Eduardo Hruschka 1
Hongliang Fei 1
Jun Huan 1
Ana Appel 1
Jeffreyxu Yu 1
Zhen Guo 1
Carlos Garcia-Alvarado 1
Anushka Anand 1
Yashu Liu 1
Feitony Liu 1
Chun Li 1
Jianyong Wang 1
Nick Duffield 1
Sanjay Chawla 1
Jinpeng Wang 1
Arnau Prat-Pérez 1
Josep Larriba-Pey 1
Risa Myers 1
Brian Gallagher 1
Qingtian Zeng 1
John Hutchins 1
Taneli Mielikäinen 1
Ji Liu 1
Manuel Gomez-Rodriguez 1
Sethuraman Panchanathan 1
Abdullah Mueen 1
Yizhou Sun 1
Xiaofei He 1
Muthuramakrishnan Venkitasubramaniam 1
Victor Lee 1
Robert Kleinberg 1
Zhi Yang 1
Yafei Dai 1
Tanmoy Chakraborty 1
David Leake 1
Chenguang Wang 1
Zhoujun Li 1
Neilzhenqiang Gong 1
Yi Chang 1
Qiang Wei 1
Moshe Kam 1
Jieping Ye 1
Licong Cui 1
Xiaofeng Zhu 1
Pierluigi Crescenzi 1
Zijun Yao 1
Weiming Hu 1
Maoying Qiao 1
Wei Bian 1
Ying Jin 1
Hiroshi Mamitsuka 1
Ümit Çatalyürek 1
Xutong Liu 1
Yencheng Lu 1
Xue Li 1
Guodong Long 1
Daxin Jiang 1
Muna Al-Razgan 1
Mohsen Bayati 1
Peilin Zhao 1
Lei Zhang 1
Raymond Wong 1
Ada Fu 1
Li Zheng 1
Ashton Anderson 1
Sendhil Mullainathan 1
Qing He 1
Kai Zhang 1
Yue Wu 1
Christos Anagnostopoulos 1
Noman Mohammed 1
Chao Liu 1
Jaideep Vaidya 1
Collin Stultz 1
Boleslaw Szymanski 1
Maguelonne Teisseire 1
Paolo Boldi 1
Lini Thomas 1
Sachindra Joshi 1
Tharam Dillon 1
Yixin Chen 1
Xuanhong Dang 1
Luigi Pontieri 1
Francesco Bonchi 1
Kasim Candan 1
Sunil Vadera 1
Thomas Porta 1
Hongzhi Yin 1
Shumo Chu 1
Bingrong Lin 1
S Upham 1
Ming Li 1
Jeffrey Erman 1
Dora Erdős 1
Joydeep Ghosh 1
Kaiyuan Zhang 1
Fosca Giannotti 1
James Cheng 1
Peter Christen 1
Daniel Dunlavy 1
Christos Doulkeridis 1
Carlos Ordonez 1
U Kang 1
David Dominguez-Sal 1
Danai Koutra 1
Steven Skiena 1
Hiroshi Motoda 1
Chris Volinsky 1
Andreas Krause 1
Hsiangfu Yu 1
Aditya Parameswaran 1
Binbin Lin 1
Johannes Gehrke 1
Christo Wilson 1
Ben Zhao 1
Bin Liu 1
Antonio Ortega 1
Zhishan Guo 1
Yunsing Koh 1
Silei Xu 1
Leonid Hrebien 1
Pei Yang 1
Li Li 1
Denian Yang 1
Bo Liu 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
Rezwan Ahmed 1
Wei Wei 1
Guoqing Chen 1
Xiaojun Chang* 1
Lina Yao 1
Zhao Kang 1
Xin Jin 1
Tao Yang 1
Polina Rozenshtein 1
Martin Rosvall 1
Duygu Ucar 1
Mustafa Bilgic 1
Ben Kao 1
David Cheung 1
Cheng Zeng 1
Atreya Srivathsan 1
Tong Sun 1
Yanchi Liu 1
Songhua Xu 1
Yunfei Lu 1
Wenwu Zhu 1
Jeffreyxu Yu 1
Soroush Vosoughi 1
Duo Zhang 1
Dmitry Pavlov 1
Raymond Ng 1
Piotr Indyk 1
Christopher Carothers 1
Anne Laurent 1
Satyanarayana Valluri 1
Kun Liu 1
Ashish Verma 1
Jérémy Besson 1
Raghu Ramakrishnan 1
Rong Ge 1
Byronju Gao 1
Li Tu 1
Saharon Rosset 1
Claudia Perlich 1
Tuannhon Dang 1
Seekiong Ng 1
Hong Xie 1
Ramana Kompella 1
Chengkai Li 1
Salvatore Ruggieri 1
Jing Zhang 1
Vasileios Kandylas 1
Rodrigo Alves 1
Juhua Hu 1
Yu Jin 1
Giulio Rossetti 1
Timothy De Vries 1
Eric Xing 1
Veerabhadran Baladandayuthapani 1
Albert Bifet 1
Xiaoming Li 1
Josep Brunat 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
Ana Maguitman 1
Filippo Menczer 1
Foto Afrati 1
Rómer Rosales 1
Xiaofang Zhou 1
Xindong Wu 1
Fangtao Li 1
Junjie Wu 1
Maryam Tahani 1
Hamid Rabiee 1
Ying Wei 1
Yubao Wu 1
Junming Shao 1
Yllka Velaj 1
Xiaojun Chang 1
Lars Schmidt-Thieme 1
Michael Lyu 1
Dityan Yeung 1
Evangelos Papalexakis 1
Nicholas Sidiropoulos 1
George Karypis 1
Davoud Moulavi 1
Fei Yi 1
Ting Guo 1
Jia Wu 1
Xingquan Zhu 1
Xun Tang 1
Jevin West 1
Koji Hino 1
Masaru Kitsuregawa 1
Xiang Zhang 1
Jenwei Huang 1
Jilei Tian 1
Biao Xiang 1
Yi Zheng 1
James Bailey 1
Jianping Zhang 1
Manas Somaiya 1
Graham Cormode 1
Bin Li 1
Fernando Kuipers 1
Dick Epema 1
Linpeng Tang 1
Min Wang 1
Marc Maier 1
Lionel Ni 1
Bryan Hooi 1
Tetsuji Ogawa 1
Ahmed El-Mahdy 1
Yuto Yamaguchi 1
Shaoxu Song 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
Kuan Zhang 1
Luigi Moccia 1
Edoardo Serra 1
Claudio Schifanella 1
Nesreen Ahmed 1
Min Wang 1
Shuiwang Ji 1
Ali Pınar 1
Michail Vlachos 1
Ling Chen 1
Yang Liu 1
Chunxiao Xing 1
Vetle Torvik 1
Dechuan Zhan 1
Ruggero Pensa 1
Saurabh Paul 1
Jose Hern´ndez-Orallo 1
Rainer Gemulla 1
Guangtao Wang 1
Xueying Zhang 1
Yiping Ke 1
Evrim Acar 1
Yang Zhou 1
Ben London 1
Joseph Ruiz Md 1
Masahiro Kimura 1
Alexander Ihler 1
Kaiwei Chang 1
Forrest Briggs 1
Gustavo Batista 1
Qiang Zhu 1
Philip Yu 1
Jure Leskovec 1
Maya Bercovitch 1
Jun Yan 1
James Bezdek 1
Marimuthu Palaniswami 1
Jayavardhana Gubbi 1
Maryam Ramezani 1
Shebuti Rayana 1
Michalis Faloutsos 1
Hongxia Yang 1
Haoda Fu 1
Dawei Zhou 1
Jingrui He 1
Liming Chen 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
Ling Liu 1
Hua Wang 1
Guannan Liu 1
Liang Wang 1
Shanshan Feng 1
Fei Zou 1
Huilei He 1
Kimon Fountoulakis 1
Virgílio Almeida 1
Christos Faloutsos 1
Nitin Agarwal 1
S Muthukrishnan 1
Kunta Chuang 1
Anthony Tung 1
Amin Saberi 1
Adelelu Jia 1
Alexandru Iosup 1
Aniket Chakrabarti 1
Reza Zafarani 1
Saurabh Kataria 1
Matthew Rattigan 1
Laiwan Chan 1
Geoffrey Barbier 1
Kijung Shin 1
Lorenzo De Stefani 1
Alessandro Epasto 1
Caetanotraina Jr 1
Oualid Boutemine 1
Limin Yao 1
Cheukkwong Lee 1
Olvi Mangasarian 1
Chris Clifton 1
Mohammed Zaki 1
Jennifer Dy 1
Shaojun Wang 1
Loïc Cerf 1
Henry Tan 1
Gianluigi Greco 1
Francesco Gullo 1
Guimei Liu 1
Min Ding 1
Jennifer Neville 1
Gensheng Zhang 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
Aditya Menon 1
Zhongfei Zhang 1
Matthew Rowe 1
Edward Chang 1
Kazumi Saito 1
Chengxiang Zhai 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
Sigal Sina 1
Sarit Kraus 1
Lior Rokach 1
Dityan Yeung 1
Bruno Abrahão 1
Xiaolin Wang 1
Tingting Gao 1
Longjie Li 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
Leman Akoglu 1
Tina Eliassi-Rad 1
Yanjun Qi 1
Theodoros Lappas 1
Munmun De Choudhury 1
Wenjie Li 1
Yada Zhu 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
Xiaotong Zhang 1
Han Liu 1
Kathleen Carley 1
Feng Chen 1
Xiaodan Song 1
Yasuhiro Fujiwara 1
Wei Wang 1
ChienWei Chen 1
Weiyin Loh 1
Giacomo Berardi 1
Eugenia Kontopoulou 1
John Salerno 1
Nitin Kumar 1
Flip Korn 1
Ying Wang 1
Chris Ding 1
Siqi Shen 1
Xinran He 1
Lei Li 1
Ke Wang 1
Chris Ding 1
Lei Xie 1
Hyunah Song 1
Haifeng Chen 1
Xiang Zhang 1
Hao Ye 1
Nenghai Yu 1
Peter Triantafillou 1
Jing Zhang 1
Benoît Dumoulin 1
Xiuyao Song 1
John Gums 1
Yin Zhang 1
Zhongfei Zhang 1
Yunxin Zhao 1
Jude Shavlik 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
Qingyan Yang 1
Patrick Haffner 1
Zhili Zhang 1
Scott Burton 1
Christos Boutsidis 1
Bingsheng Wang 1
Hui Ke 1
Tamara Kolda 1
Karthik Subbian 1
Jie Wang 1
Galileo Namata 1
João Duarte 1
Yulan He 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
Shlomi Dolev 1
Fang Wang 1
Haixun Wang 1
Zhirui Hu 1
Dheeraj Kumar 1
Yao Wu 1
Dandan Qiao 1
Ali Hemmatyar 1
Meng Jiang 1
Beilun Wang 1
Chihya Shen 1
Zhitao Wang 1
Jingrui He 1
Ming Zhang 1
Yi Zhen 1

Affiliation Paper Counts
Ryukoku University 1
California State University Fullerton 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
City University of New York 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
University of Arizona 1
Nanjing University of Science and Technology 1
Washington University in St. Louis 1
Soochow University 1
HP Labs 1
Universidad Politecnica de Valencia 1
State University of New York at Albany 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
University of Tsukuba 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
Florida Atlantic University 1
Wright State University 1
Air Force Research Laboratory 1
Macquarie University 1
University of West Florida 1
Shenyang Institute of Automation Chinese Academy of Sciences 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
Waseda University 1
Universite Claude Bernard Lyon 1 1
Lancaster University 1
Osaka University 1
University of Iowa 1
National University of Defense Technology China 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
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
University at Buffalo, State University of New York 1
US Naval Academy 1
University of Roma La Sapienza 1
Griffith University 1
University of New Mexico 1
Alexandria University 1
Saarland University 1
University of Kuwait 1
Vilnius University 1
Amazon.com, Inc. 1
Harvard School of Engineering and Applied Sciences 1
Ariel University Center of Samaria 1
Siemens USA 1
eBay, Inc. 1
Yuncheng University 1
Innopolis University 1
IBM, India 1
University of Montpellier 1
Max Planck Institute for Informatics 2
University of Glasgow 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
Harvard 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
Singapore Management University 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 California, Berkeley 2
University of Tokyo 2
University Michigan Ann Arbor 2
Nokia Corporation 2
University of California, Los Angeles 2
University of Quebec in Montreal 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
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
Shandong University of Science and Technology 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 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
Wuhan University 3
Southern Illinois University at Carbondale 3
University of Alberta 3
University of Queensland 3
Johannes Gutenberg University Mainz 3
Emory University 4
Institute for Infocomm Research, A-Star, Singapore 4
Brookhaven National Laboratory 4
Universitat Politecnica de Catalunya 4
The University of Western Ontario 4
IBM Research 4
Brown University 4
University of Antwerp 4
Beihang University 4
AT&T Inc. 4
University of Washington, Seattle 4
National University of Singapore 4
Athens University of Economics and Business 4
Monash University 4
Boston University 4
Shanghai Jiaotong University 4
Microsoft Corporation 4
Sharif University of Technology 4
University of Pisa 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
Google Inc. 5
Sandia National Laboratories, New Mexico 5
University of Turin 5
Renmin University of China 5
New Jersey Institute of Technology 5
The University of North Carolina at Chapel Hill 5
University of Southern California 5
Rutgers, The State University of New Jersey 5
Delft University of Technology 6
University of Sao Paulo 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 California, Santa Barbara 6
University of Minnesota Twin Cities 6
Yahoo Inc. 6
Purdue University 7
University of Florida 7
University of Maryland 7
Massachusetts Institute of Technology 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
Pennsylvania State University 8
Nanyang Technological University 8
University of Texas at Austin 8
Oregon State University 8
Xi'an Jiaotong University 8
Microsoft Research 8
Stony Brook University 8
Nanjing University 8
Peking University 9
Florida International University 9
Georgia Institute of Technology 9
Yahoo Research Labs 9
National Taiwan University 10
Stanford University 10
IBM Thomas J. Watson Research Center 10
University of Melbourne 10
Virginia Tech 10
University of Illinois at Chicago 10
Rensselaer Polytechnic Institute 11
Hong Kong University of Science and Technology 12
University of Calabria 12
Cornell University 13
University of Science and Technology of China 13
University of Texas at Arlington 15
Northwestern Polytechnical University China 16
University of Technology Sydney 16
Simon Fraser University 17
University of Illinois at Urbana-Champaign 19
NEC Laboratories America, Inc. 19
Chinese University of Hong Kong 21
Tsinghua University 33
Carnegie Mellon University 41
Arizona State University 48

ACM Transactions on Knowledge Discovery from Data (TKDD) - Special Issue on KDD 2016 and Regular Papers
Archive


2017
Volume 11 Issue 4, August 2017 Special Issue on KDD 2016 and Regular Papers
Volume 11 Issue 3, April 2017

2016
Volume 11 Issue 2, December 2016
Volume 11 Issue 1, August 2016
Volume 10 Issue 4, July 2016 Special Issue on SIGKDD 2014, Special Issue on BIGCHAT and Regular Papers
Volume 10 Issue 3, February 2016

2015
Volume 10 Issue 2, October 2015
Volume 10 Issue 1, July 2015
Volume 9 Issue 4, June 2015
Volume 9 Issue 3, April 2015 TKDD Special Issue (SIGKDD'13)

2014
Volume 9 Issue 2, November 2014
Volume 9 Issue 1, October 2014
Volume 8 Issue 4, October 2014
Volume 8 Issue 3, June 2014
Volume 8 Issue 2, June 2014
Volume 8 Issue 1, February 2014 Casin special issue

2013
Volume 7 Issue 4, November 2013
Volume 7 Issue 3, September 2013 Special Issue on ACM SIGKDD 2012
Volume 7 Issue 2, July 2013
Volume 7 Issue 1, March 2013

2012
Volume 6 Issue 4, December 2012 Special Issue on the Best of SIGKDD 2011
Volume 6 Issue 3, October 2012
Volume 6 Issue 2, July 2012
Volume 6 Issue 1, March 2012
Volume 5 Issue 4, February 2012

2011
Volume 5 Issue 3, August 2011
Volume 5 Issue 2, February 2011

2010
Volume 5 Issue 1, December 2010
Volume 4 Issue 3, October 2010
Volume 4 Issue 4, October 2010
Volume 4 Issue 2, May 2010
Volume 4 Issue 1, January 2010

2009
Volume 3 Issue 4, November 2009
Volume 3 Issue 3, July 2009
Volume 3 Issue 2, April 2009
Volume 3 Issue 1, March 2009
Volume 2 Issue 4, January 2009

2008
Volume 2 Issue 3, October 2008
Volume 2 Issue 2, July 2008
Volume 2 Issue 1, March 2008
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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