ACM Transactions on

Intelligent Systems and Technology (TIST)

Latest Articles


Bridging the Air Gap between Isolated Networks and Mobile Phones in a Practical Cyber-Attack

Information is the most critical asset of modern organizations, and accordingly it is one of the resources most coveted by adversaries. When highly... (more)

Understanding the Relationship between Human Behavior and Susceptibility to Cyber Attacks

Despite growing speculation about the role of human behavior in cyber-security of machines, concrete data-driven analysis and evidence have been... (more)

Optimal Scheduling of Cybersecurity Analysts for Minimizing Risk

Cybersecurity threats are on the rise with evermore digitization of the information that many day-to-day systems depend upon. The demand for... (more)

A Risk-Scoring Feedback Model for Webpages and Web Users Based on Browsing Behavior

It has been claimed that many security breaches are often caused by vulnerable (naïve) employees within the organization [Ponemon Institute... (more)

Automatic Construction of Statechart-Based Anomaly Detection Models for Multi-Threaded Industrial Control Systems

Traffic of Industrial Control System (ICS) between the Human Machine Interface (HMI) and the... (more)

On Network Neutrality Measurements

Network level surveillance, censorship, and various man-in-the-middle attacks target only specific types of network traffic (e.g., HTTP, HTTPS, VoIP, or Email). Therefore, packets of these types will likely receive “special” treatment by a transit network or a man-in-the-middle attacker. A transit Internet Service Provider (ISP) or an... (more)

Analyzing and Optimizing Access Control Choice Architectures in Online Social Networks

The way users manage access to their information and computers has a tremendous effect on the overall security and privacy of individuals and... (more)

Tracking Illicit Drug Dealing and Abuse on Instagram Using Multimodal Analysis

Illicit drug trade via social media sites, especially photo-oriented Instagram, has become a severe problem in recent years. As a result, tracking... (more)


Recent TIST News: 

ACM Transactions on Intelligent Systems and Technology (TIST) is ranked No.1 in all ACM journals in terms of citations received per paper. Each paper published at TIST in the time span (from Jan. 2010 to Dec. 2014) has received 18 citations on average in ACM Digital Library in the past fiscal year (from July 1 2015 to June 30 2016).  

ACM Transactions on Intelligent Systems and Technology (TIST) has been a success story.  Submissions to the journal have increase 76 percent from 2013 to 2015, from 278 original papers and revisions to 488.  Despite this increase, the journal acceptance rate has remained at a steady rate of approximately 24 percent. Furthermore, the TIST Impact Factor increased from 1.251 in 2014 to 2.414 in 2015.  

Journal Metric (2016)

  • - Impact Factor: 2.4
  • - 5-year Impact Factor: 9.15
  • - Avg. Citations in ACM DL: 18 

About TIST

ACM Transactions on Intelligent Systems and Technology (ACM TIST) is a scholarly journal that publishes the highest quality papers on intelligent systems, applicable algorithms and technology with a multi-disciplinary perspective. An intelligent system is one that uses artificial intelligence (AI) techniques to offer important services (e.g., as a component of a larger system) to allow integrated systems to perceive, reason, learn, and act intelligently in the real world. READ MORE

Forthcoming Articles

TensorBeat: Tensor Decomposition for Monitoring Multi-Person Breathing Beats with Commodity WiFi

Spotting Trip Purposes from Taxi Trajectories: A General Probabilistic Model

What is the purpose of a trip? What are the unique human mobility patterns and spatial contexts in or near the pickup points and delivery points of trajectories for a specific trip purpose? Many studies have modeled human mobility patterns of urban regions; these analytics mainly focus on interpreting the semantic meanings of geographic topics at an aggregated level. However, at an individual level, given the lack of information about destination activities, it is challenging to convert these studies into effective tools for inferring trip purposes. To address this challenge, in this paper, we study large-scale taxi trajectories of individuals, and we identify some interesting observations. First, the urban forms (i.e., geographic topics and corresponding portfolios) of surrounding areas of pickup points and delivery points closely relate to trip proposes. Second, given a pickup point, spotting trip purposes can be reduced into selecting the best delivery point that should be linked to the pickup point in terms of the matching degree between trip purpose and spatiotemporal contexts. Existing human mobility modeling methods do not exhibit these types of observations, even at an individual level. Along these lines, we develop a general analytic framework for spotting trip purposes from massive taxi GPS trajectories. Specifically, we first augment the origin and destination points of trajectories by attaching POI topics and corresponding portfolios in origin and destination regions. We then propose a generative probabilistic model of taxi trajectories by capturing the intercorrelations among trajectory directions, POI topical portfolios of O-D pairs, and pickup and arrival times. This model consists four analogies: (i) POI as a word; (ii) origin and destination neighborhoods as O-D documents; (iii) trajectory as a directed link between O-D documents; (vi) trip purpose as a link type. In this way, we can group trajectories into trip clusters in terms of trip purposes, and ultimately exploit spectrum analysis to identify the semantic meanings of latent purposes. Finally, we present extensive experiments with the real-world taxi trajectory data of New York City to demonstrate the effectiveness of our proposed method for spotting trip purposes at an individual level.

Scalable Urban Mobile Crowdsourcing: Handling Uncertainty in Worker Movement

In this work, we investigate effective ways of utilizing crowdworkers in providing various urban services. The task recommendation platform that we design can match tasks to crowdworkers based on workers' historical trajectories and time budget limits, thus making recommendations personal and efficient. One major challenging we manage to address is the handling of crowdworker's trajectory uncertainties. In this work, we explicitly allow multiple routine routes to be probabilistically associated with each worker. We formulate this problem as an integer linear program whose goal is to maximize the expected total utility achieved by all workers. We further exploit the separable structures of the formulation and apply the Lagrangian relaxation technique to scale up computation. Numerical experiments have been performed over the instances generated using the realistic public transit dataset in Singapore. The results show that we can find significantly better solutions than the deterministic formulation, and in most cases we can find solutions that are very close to the theoretical performance limit. To demonstrate the practicality of our approach, we deployed our recommendation engine to a campus-scale field trial, and we demonstrate that workers receiving our recommendations incur fewer detours and complete more tasks, and are 20% more efficient against workers relying on their own planning. This is achieved despite having highly uncertain worker trajectories. We also demonstrate how to further improve the robustness of the system by using a simple multi-coverage mechanism.

Risk-Sensitive Stochastic Orienteering Problems for Trip Optimization in Urban Environments

Orienteering Problems (OPs) are used to model many routing and trip planning problems. OPs are a variant of the well-known traveling salesman problem where the goal is to compute the highest reward path that includes a subset of vertices and has an overall travel time less than a specified deadline. However, the applicability of OPs is limited due to the assumption of deterministic and static travel times. To that end, \cite{campbell:11} extended OPs to Stochastic OPs (SOPs) to represent uncertain travel times. In this paper, we make the following key contributions: (1)~we extend SOPs to Dynamic SOPs (DSOPs), which allow for time dependent travel times; (2)~we introduce a new objective criterion for SOPs and DSOPs to represent a percentile measure of risk; (3)~we provide non-linear optimization formulations along with their linear equivalents for solving the risk-sensitive SOPs and DSOPs; (4)~we provide a local search mechanism for solving the risk-sensitive SOPs and DSOPs; and (5)~we provide results on existing benchmark problems and a real-world theme park trip planning problem.

Real-time Human Mobility Modeling with Multi-View Learning

Real-time human mobility modeling is essential to various urban applications. To model such human mobility, numerous data-driven techniques have been proposed. However, existing techniques are mostly driven by data from a single view, e.g., a transportation view or a cellphone view, which leads to over-fitting of these single-view models. To address this issue, we propose a human mobility modeling technique based on a generic multi-view learning framework called coMobile. In coMobile, we first improve the performance of single-view models based on tensor decomposition with correlated contexts, and then we integrate these improved single-view models together for multi-view learning to iteratively obtain mutually-reinforced knowledge for real-time human mobility at urban scale. We implement coMobile based on an extremely large dataset in the Chinese city Shenzhen, including data about taxi, bus and subway passengers along with cellphone users, capturing more than 27 thousand vehicles and 10 million urban residents. The evaluation results show that our approach outperforms a single-view model by 51\% on average. More importantly, we design a novel application where urban taxis are dispatched based on unaccounted mobility demand inferred by coMobile.

A Multiagent-based Approach for Vehicle Routing by Considering both Arriving on Time and Total Travel Time

Arriving on time and total travel time are two important properties for vehicle routing. Existing route guidance approaches always consider them independently because they may conflict with each other. In this paper, we develop a decentralized multiagent-based vehicle routing approach where vehicle agents follow the local route guidance by infrastructure agents at each intersection, and infrastructure agents perform the route guidance by solving a route assignment problem. It integrates the two properties by expressing them as two objective terms of the route assignment problem. Regarding arriving on time, it is formulated based on the probability tail model, which aims to maximize the probability of reaching destination before deadline. Regarding total travel time, it is formulated as a weighted quadratic term, which aims to minimize the expected travel time from the current location to the destination based on the potential route assignment. The weight for total travel time is designed to be comparatively large if the deadline is loose. Additionally, we improve the proposed approach in several aspects, including travel time prediction, computational efficiency and infrastructure agent communication. Experimental results on real road networks justify its ability to increase the average probability of arriving on time, reduce total travel time and enhance the overall routing performance.

illiad: InteLLigent Invariant and Anomaly Detection in Cyber Physical Systems

Cyber physical systems (CPSs) are today ubiquitous in urban environments. Such systems now serve as thebackbone to numerous critical infrastructure applications, from smart grids to IoT installations. Scalableand seamless operation of such CPSs requires sophisticated tools for monitoring the time series progres-sion of the system, dynamically tracking relationships, and issuing alerts about anomalies to operators. Wepresent an online monitoring system (illiad) that models the state of the CPS as a function of its relation-ships between constituent components, using a combination of model-based and data-driven strategies. Inaddition to accurate inference for state estimation and anomaly tracking,illiadis able to exploit the un-derlying network structure of the CPS (wired or wireless) for state estimation purposes. We demonstratethe application ofilliadto two diverse settings: a wireless sensor motes application and an IEEE 33-busmicrogrid

A Comfort-Based Approach to Smart Heating and Air Conditioning

In this paper, we address the interrelated challenges of predicting user comfort and using this to reduce energy consumption in smart heating, ventilation and air conditioning (HVAC) systems. At present, such systems use simple models of user comfort when deciding on a set point temperature. Being built using broad population statistics, these models generally fail represent individual users preferences, resulting in poor estimates of the users preferred temperatures. To address this issue, we propose the Bayesian Comfort Model (BCM). This personalised thermal comfort model using a Bayesian network learns from a users feedback, allowing it to adapt to the users individual preferences over time. We further propose an alternative to the ASHRAE 7-point scale used to assess user comfort. Using this model, we create an optimal HVAC control algorithm that minimizes energy consumption while preserving user comfort. Through an empirical evaluation based on the ASHRAE RP-884 data set and data collected in a separate deployment by us, we show that our model is consistently 13.2 to 25.8% more accurate than current models and how using our alternative comfort scale can increase our models accuracy. Through simulations we show that using this model, our HVAC control algorithm can reduce energy consumption by 7.3% to 13.5% while decreasing user discomfort by 24.8% simultaneously.

A Traffic Flow Approach to Early Detection of Gathering Events: Comprehensive Results

Given a spatial field and the traffic flow between neighboring locations, the early detection of gathering events (EDGE) problem aims to discover and localize a set of most likely gathering events. It is important for city planners to identify emerging gathering events which might cause public safety or sustainability concerns. However, it is challenging to solve the EDGE problem due to numerous candidate gathering footprints in a spatial field and the non-trivial task to balance pattern quality and computational efficiency. Prior solutions to model the EDGE problem lack the ability to describe the dynamic flow of traffic and the potential gathering destinations because they rely on static or undirected footprints. In our recent work, we modeled the footprint of a gathering event as a Gathering Graph (G-Graph), where the root of the directed acyclic G-Graph is the potential destination and the directed edges represent the most likely paths traffic takes to move towards the destination. We also proposed an efficient algorithm called {SmartEdge} to discover the most likely non-overlapping G-Graphs in the given spatial field.However, it is challenging to perform a systematic performance study of the proposed algorithm, due to unavailability of the ground truth of gathering events. In this paper, we introduce an event simulation mechanism, which makes it possible to conduct a comprehensive performance study of the SmartEdge algorithm. We measure the quality of the detected patterns, in a systematic way, in terms of timeliness and location accuracy. The results show that, on average, the SmartEdge algorithm is able to detect patterns within a grid cell away (less than 500 meters) of the simulated events and detect patterns of the simulated events as early as 10 minutes prior to the first arrival to the gathering event.

RCMC: Recognizing Crowd Mobility Patterns in Cities based on Location Based Social Networks Data

During the past few years, the analysis of data generated from Location-Based Social Networks (LBSNs) have aided in the identification of urban patterns, understanding activity behaviours in urban areas, as well as producing novel recommender systems that facilitate users choices. Recognizing crowd mobility patterns in cities is very important for public safety, traffic managment, disaster management, and urban planning. In this paper we propose a framework for Recognizing the Crowd Mobility Patterns in Cities (RCMC) using Location Based Social Networks (LBSN) data. Our proposed framework comprises of four main components: data gathering, recurrent crowd mobility patterns extraction, temporal functional regions detection and visualization component. More specifically, we employ a novel approach based on Non-negative Matrix Factorization (NMF) and gaussian Kernel Density Estimation (KDE) for extracting the recurrent crowd mobility patterns in cities illustrating how crowd shifts from one area to another during each day across various time-slots. Moreover, the framework employs a hierarchical clustering based algorithm for identifying what we refer to as temporal functional regions by modeling functional areas taking into account temporal variation by means of check-ins categories. We build the framework using spatial-temporal dataset crawled from Twitter for two entire years 2013 and 2014 for the area of Manhattan in New York City (NYC). We perform a detailed analysis of the extracted crowd patterns with an exploratory visualization showing that our proposed approach can identify clearly obvious mobility patterns that recur over time and location in the urban scenario. Using same time interval, we show that correlating the temporal functional regions with the recognized recurrent crowd mobility patterns can yield to a deeper understanding of city dynamics and the motivation behind the crowd mobility. We are confident that our proposed framework can not only help in managing complex city environments and better allocation of resources based on the expected crowd mobility and temporal functional regions but can have a direct implication on a variety of applications such as personalized recommender systems, anomalous event detection, disaster resilience management systems, and others.

Refined-Graph Regularization Based Nonnegative Matrix Factorization

Nonnegative matrix factorization (NMF) is one of the most popular data representation methods in the field of computer vision and pattern recognition. High dimension data are usually assumed to be sampled from the submanifold embedded in the original high dimension space. So it is very important to recover the geometric structure information of the data in the procedure of data representation and feature extraction. To preserve the locality geometric structure of the data, k-nearest neighbor (k-NN) graph is often constructed to encode the near neighbor layout structure. However, k-NN graph is based on the Euclidean distance which is sensitive to noise and outliers. We in this paper propose a refined-graph regularized nonnegative matrix factorization (RGRNMF) by employing a manifold regularized least squares regression (MRLSR) method to compute the refined graph. In particular, each sample is represented by the whole dataset regularized with `2-norm and Laplacian regularizer. Then a MRLSR graph is constructed based on the representative coefficients of each sample. The Laplacian regularizer helps to enforce the coefficients of the samples within the same class locating compactly. To avoid the effects of errors, we utilize hard thresholding to generate a truncated graph, which can improve the robustness of the proposed method. Two optimization schemes are proposed in solving our problem and two corresponding methods are proposed, i.e. RGRNMF1 and RGRNMF2. Finally, the proposed methods are used for performing image clustering. Experimental results on several image datasets reveal that they outperform eleven representative methods.

A Real-Time Framework for Task Assignment in Hyperlocal Spatial Crowdsourcing

Spatial Crowdsourcing (SC) is a novel platform that engages individuals in the act of collecting various types of spatial data. This method of data collection can significantly reduce cost and turnover time, and is particularly useful in environmental sensing, where traditional means fail to provide fine-grained field data. In this study, we introduce hyperlocal spatial crowdsourcing, where all workers who are located within the spatiotemporal vicinity of a task are eligible to perform the task, e.g., reporting the precipitation level at their area and time. In this setting, there is often a $budget$ constraint, either for every time period or for the entire campaign, on the number of workers to activate to perform tasks. The challenge is thus to maximize the number of assigned tasks under the budget constraint, despite the dynamic arrivals of workers and tasks. We introduce a taxonomy of several problem variants, such as budget-per-time-period vs. budget-per-campaign and binary-utility vs. distance-based-utility. We study the hardness of the task assignment problem in the offline setting and propose online heuristics which exploits the spatial and temporal knowledge acquired over time. Our experiments are conducted systematically with datasets generated by spatial crowdsourcing workbench and extensive results show the effectiveness and efficiency of our proposed solutions.

Personalized Air Travel Prediction: A Multi-factor Perspective

Human mobility analysis is one of the most important research problems in the field of urban computing. Existing research mainly focuses on the intra-city ground travel behavior modeling, while the inter-city air travel behavior modeling has been largely ignored. Actually, the inter-city travel analysis can be of equivalent importance and complementary to the intra-city travel analysis. Understanding the massive passengers' air travel behaviors delivers intelligence for airlines' precision marketing and related socioeconomic activities, such as airport planning, emergency management, local transportation planning, and tourism-related businesses. Moreover, it provides opportunities to study the characteristics of cities and the mutual relationships between cities. However, modeling and predicting air travelers' behavior is challenging due to the complex factors of the market situation and individual characteristics of customers (e.g. airlines' market share, customer membership, and travelers' intrinsic interests on destinations). To this end, in this paper, we present a systematic study on the personalized air travel prediction problem, namely where a customer will fly to and which airline carrier to fly with, by leveraging real-world anonymized Passenger Name Record (PNR) data. Specifically, we first propose a Relational Travel Topic Model (RTTM), which combines the merits of latent factor model and neighborhood-based method, to uncover the personal travel preferences of aviation customers and the latent travel topics of air routes simultaneously. Then we present a Multi-Factor Travel Prediction (MFTP) framework, which fuses complex factors of the market situation and individual characteristics of customers, to predict airline customers' personalized travel demands. Experimental results on two real-world PNR datasets demonstrate the effectiveness of our approach on both latent travel topics discovery and customer travel prediction.


Publication Years 2010-2017
Publication Count 461
Citation Count 5363
Available for Download 461
Downloads (6 weeks) 5398
Downloads (12 Months) 48120
Downloads (cumulative) 212002
Average downloads per article 460
Average citations per article 12
First Name Last Name Award
Benjamin B Bederson ACM Distinguished Member (2011)
Andrei Broder ACM Paris Kanellakis Theory and Practice Award (2012)
Carlos A. Castillo ACM Senior Member (2014)
Charles L A Clarke ACM Distinguished Member (2015)
Ingemar J. Cox ACM Distinguished Member (2011)
Alberto Del Bimbo ACM Distinguished Member (2016)
Deborah Estrin ACM Athena Lecturer Award (2006)
Maria L Gini ACM Distinguished Member (2006)
Xian-Sheng Hua ACM Distinguished Member (2015)
ACM Senior Member (2009)
Chih-Jen Lin ACM Distinguished Member (2011)
ACM Senior Member (2010)
C.L. Liu ACM Karl V. Karlstrom Outstanding Educator Award (1989)
Tao Mei ACM Distinguished Member (2016)
ACM Senior Member (2012)
Jeffrey Nichols ACM Senior Member (2013)
Judea Pearl ACM A. M. Turing Award (2011)
ACM AAAI Allen Newell Award (2003)
Jian Pei ACM Senior Member (2007)
Yong Rui ACM Distinguished Member (2009)
ACM Senior Member (2006)
Stefan Savage ACM Prize in Computing (2015)
Yoav Shoham ACM AAAI Allen Newell Award (2012)
Gita Reese Sukthankar ACM Senior Member (2013)
Jaime Teevan ACM Senior Member (2012)
Moshe Tennenholtz ACM AAAI Allen Newell Award (2012)
Feiyue Wang ACM Distinguished Member (2007)
Xing Xie ACM Senior Member (2010)
Hui Xiong ACM Distinguished Member (2014)
ACM Senior Member (2010)
Shuicheng Yan ACM Distinguished Member (2016)
Qiang Yang ACM Distinguished Member (2011)
Franco Zambonelli ACM Distinguished Member (2012)
ACM Senior Member (2009)
Yu Zheng ACM Distinguished Member (2016)
ACM Senior Member (2011)
Michelle Zhou ACM Distinguished Member (2009)
ACM Senior Member (2007)
Michelle Zhou ACM Distinguished Member (2009)
ACM Senior Member (2007)

First Name Last Name Paper Counts
Dacheng Tao 8
Tatseng Chua 7
Xing Xie 7
Enhong Chen 6
Nicholasjing Yuan 5
Yu Zheng 5
Xiansheng HUA 5
Jinhui Tang 5
Shuicheng Yan 5
Steven Hoi 4
Xuan Song 4
Ryosuke Shibasaki 4
Yuval Elovici 4
Changsheng Xu 4
Qiang Yang 4
Michelle Zhou 4
Ya'akov Gal 3
Quanshi Zhang 3
Martha Larson 3
Philip YU 3
Christopherchuen Yang 3
Wen Gao 3
Xue Li 3
Alex Rogers 3
Hui Xiong 3
Rongrong Ji 3
Xiaowei Shao 3
Huanhuan Cao 3
Francesco Bonchi 3
Irwin King 3
Meng Wang 3
Rebecca Castaño 3
VS Subrahmanian 3
Qi Tian 3
Wenchih Peng 3
Tao Li 3
Daxin Jiang 2
Katia Sycara 2
Rino Falcone 2
Jinshi Cui 2
Jia Zeng 2
Dana Nau 2
Xuning Tang 2
Shoude Lin 2
Charles Ling 2
Daqing Zhang 2
Anlei Dong 2
Zhengjun Zha 2
Yue Gao 2
Jure Leskovec 2
Shazia Sadiq 2
Mohan Kankanhalli 2
Yoshinobu Kawahara 2
Oded Maimon 2
Chihjen Lin 2
Diane Cook 2
Defu Lian 2
Jie Cheng 2
Quan Fang 2
Elena Baralis 2
Tania Cerquitelli 2
Robin Cohen 2
Vincent Tseng 2
Hongxun Yao 2
Zhiwen Yu 2
Paulo Shakarian 2
Hongyuan Zha 2
Sihong Xie 2
Haggai Roitman 2
SungWook Yoon 2
Mahmud Hossain 2
Liyan Zhang 2
Eran Toch 2
Xueqi Cheng 2
Huijing Zhao 2
Alberto Del Bimbo 2
Liqiang Nie 2
Richang Hong 2
Yongdong Zhang 2
Amin Javari 2
Jian Pei 2
Amit Chopra 2
Alexander Artikis 2
Venkatramanan Subrahmanian 2
Maria Sapino 2
Guirong Xue 2
Iván Cantador 2
Ido Guy 2
Bohao Chen 2
Hongzhi Yin 2
Yixin Chen 2
Matteo Venanzi 2
Nicholas Jennings 2
Fuzheng Zhang 2
Nathan Eagle 2
Shulamit Reches 2
Jamal Bentahar 2
Kyumin Lee 2
James Caverlee 2
Wangchien Lee 2
Thomas Dietterich 2
Subbarao Kambhampati 2
Jalal Mahmud 2
Manish Marwah 2
Tao Mei 2
Pablo Castells 2
Hanqing Lu 2
Meir Kalech 2
Sushil Jajodia 2
Ling Guan 2
Xiaofang Zhou 2
Michael Fire 2
Neil Yorke-Smith 2
Laiwan Chan 2
Jaegil Lee 2
Ratnesh Sharma 2
Fabio Gasparetti 2
Alessandro Micarelli 2
Munindar Singh 2
Gita Sukthankar 2
Zhiyuan Cheng 2
John Dickerson 2
Alvin Chin 2
David Carmel 2
Michael Lyu 2
Rajesh Ganesan 2
Vito Ostuni 2
Jun Ma 2
Jiuyong Li 2
Yuichi Motai 2
Masaki Aono 2
David Thompson 2
Yihsuan Yang 2
Benno Stein 2
Alejandro Bellogín 2
Bingbing Ni 2
Jeffrey Nichols 2
John Doucette 2
Daqing Zhang 2
Tommaso Noia 2
Zhi Geng 2
Kun Zhang 2
Bernhard Schölkopf 2
Jitao Sang 2
Ramesh Jain 2
Naren Ramakrishnan 2
Sarit Kraus 2
Lior Rokach 2
Rui Zhang 2
Kiri Wagstaff 2
Martin Potthast 2
Alan Said 2
Li Chen 2
Shihchia Huang 2
Eugenio Sciascio 2
Xavier Serra 2
Ron Hirschprung 2
Xindong Wu 2
Robin Cohen 2
Hasan Cam 2
Shuaiqiang Wang 2
Chong Peng 2
Jiawei Han 2
Qingzhong Liu 2
Luan Tang 2
JiLei Tian 2
Mahdi Jalili 2
Claudio Biancalana 2
Giuseppe Sansonetti 2
Luca Cagliero 2
Yue Shi 2
Alan Hanjalic 2
Richard Comont 1
Elaine O'mahony 1
Krzysztof Grudzień 1
Yunchao Wei 1
Robert Morris 1
Mohammad Hossain 1
Ghulam Muhammad 1
Guangchan Liu 1
Sarah Schulz 1
Xiaoming Zhang 1
Christopher Yang 1
Simon Pool 1
Juanzi Li 1
Emil Stefanov 1
Elaine Shi 1
Dan Ventura 1
W Towne 1
Changshing Perng 1
Jing Lv 1
William Groves 1
Fabrizio Silvestri 1
Chongyu Chen 1
Meng Wang 1
Haiyan Li 1
Nan Dong 1
Fanchieh Cheng 1
Tao Guan 1
Liya Duan 1
Yinting Wang 1
Jiadong Zhang 1
Guodong Guo 1
Haiwei Dong 1
Hong Liu 1
Frederic Font 1
Kartik Talamadupula 1
Alessandro Saffiotti 1
Daniel Neill 1
Haipeng Chen 1
Mordechai Guri 1
Steven Reece 1
Hoda Sepehri Rad 1
Beryl Plimmer 1
Vincentwenchen Zheng 1
Zhao Kang 1
Jingfei Li 1
Jinghe Zhang 1
Eepeng Lim 1
Xibin Zhao 1
Jiebo Luo 1
Andrew Sung 1
Mengyu Qiao 1
Roland Kays 1
Karen Haigh 1
Joshua Plotkin 1
Shyam Boriah 1
Christopher Potter 1
Zhenyu Lu 1
Itamar Hata 1
Si Liu 1
Qiang Chen 1
Jinfeng Zhuang 1
Rómer Rosales 1
Qiusha Zhu 1
Xi Li 1
Zhongfei Zhang 1
Anton Hengel 1
Brandon Gozick 1
Chewlim Tan 1
Nitesh Chawla 1
Elisabeth Weiss 1
Hannes Wolf 1
Klaus Herrmann 1
Yugyung Lee 1
Deendayal Dinakarpandian 1
Nicoletta Fornara 1
Michael Wooldridge 1
Cristiano Castelfranchi 1
Viviana Patti 1
Yiqun Hu 1
Liu Wenyin 1
Jiqing Han 1
Tieran Zheng 1
Ofrit Lesser 1
Luigi Caro 1
Jiawei Han 1
John Debenham 1
Liubin Wang 1
Dingkun Ma 1
Alen Docef 1
Md Seddiqui 1
Christos Faloutsos 1
Zhao Lu 1
Shanyuan Ho 1
Alice Chan 1
Benjamin Bornstein 1
Michele Judd 1
Fabrizio Marozzo 1
Domenico Talia 1
James Herbsleb 1
Yexi Jiang 1
Javid Ebrahimi 1
Graham Pinhey 1
Hongbo Ni 1
Houqiang Li 1
Rok Sosič 1
Tieke He 1
Ingemar Cox 1
Ping Tan 1
Chiyin Chow 1
Yu Zhu 1
Meiyu Huang 1
Jonathan Doherty 1
Zhou Jin 1
B Prakash 1
Takashi Washio 1
Yuval Shavitt 1
Amit Kleinmann 1
Sahar Changuel 1
Nicolas Labroche 1
Peter Rodgers 1
Long Xia 1
Yuexian Hou 1
Haoyi Xiong 1
Yizhou Sun 1
Tuananh Hoang 1
Xiaofeng Zhu 1
Lars Kulik 1
Shanika Karunasekera 1
Eman Khunayn 1
Homer Chen 1
Ying Xu 1
Randy Goebel 1
Mark Beattie 1
Ana Martínez-García 1
Xilin Chen 1
Yohan Jin 1
Aijun Bai 1
Xin Sun 1
Pietro Pala 1
Junming Xu 1
Christine Parent 1
Pavel Serdyukov 1
Kouzou Ohara 1
Yuval Marton 1
Trevor Cohn 1
Chang Hu 1
Katrin Erk 1
Steven Burrows 1
David Newman 1
Padhraic Smyth 1
Kostas Kolomvatsos 1
Stathes Hadjiefthymiades 1
Albert Bifet 1
Weinan Zhang 1
Fabiano Belém 1
Jintao Ye 1
Dihong Gong 1
Hweepink Tan 1
Domonkos Tikk 1
Benno Stein 1
Steffen Becker 1
Denis Helic 1
Roman Kern 1
Marco Baroni 1
Charles Parker 1
Ugur Kuter 1
Daniel Corkill 1
Daniel Tran 1
Robert Pappalardo 1
Yuzhou Zhang 1
Vasant Dhar 1
Edward Chang 1
Bo Liu 1
Gilles Gasso 1
Xuelong Li 1
Aleksandr Farseev 1
Yuan Zhou 1
Lei Wu 1
Jia Liu 1
Massimiliano Cattafi 1
Paolo Cagnoli 1
Bart Peintner 1
Tomasz Stepinski 1
Onur Küçüktunç 1
Zhiguo Gong 1
Chunhua Shen 1
Ram Dantu 1
Gregory Cooper 1
Vincenzo D'Elia 1
Kurt Rothermel 1
Jeremiah Folsom-Kovarik 1
Matteo Baldoni 1
Zhengxiang Wang 1
Shunxuan Wang 1
Qi Guo 1
Fabian Abel 1
Wil Van Der Aalst 1
Argimiro Arratia 1
Tao Li 1
Haiyin Shen 1
Yi Wang 1
Zhenlong Sun 1
Damian Martínez-Muñoz 1
Zhonggang Wu 1
Steve Chien 1
Bernd Freisleben 1
John Champaign 1
Alexander Schindler 1
Jiming Liu 1
Tara Estlin 1
Ning Zhang 1
Lingyu Duan 1
Pramod Anantharam 1
Osmar Zaïane, 1
Eunju Kim 1
Chris Nugent 1
Patricia Serrano-Alvarado 1
Haikun Wei 1
Steffen Rendle 1
Xiaoping Chen 1
Zhixian Yan 1
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Dimitrios Michalopoulos 1
Michael Borish 1
Advaith Siddharthan 1

Affiliation Paper Counts
Ryukoku University 1
University of Connecticut Health Center 1
University of Lausanne 1
Federal University of Amazonas 1
University of Macedonia 1
Demokritos National Centre for Scientific Research 1
University of Michigan 1
Anhui University 1
National Taitung University Taiwan 1
University of Sheffield 1
Ehime University 1
University of Haifa 1
University of Perugia 1
Joint Institute for Nuclear Research, Dubna 1
Instituto Superior Tecnico 1
University of Auckland 1
Bogazici University 1
University of Houston 1
University of Pennsylvania 1
University of Koblenz-Landau 1
Guangdong University of Technology 1
Northwestern University 1
Smithsonian National Museum of Natural History 1
Hebrew University of Jerusalem 1
Osaka Prefecture University 1
Duke University 1
Vrije Universiteit Amsterdam 1
Birkbeck University of London 1
Educational Testing Service 1
IBM Almaden Research Center 1
Wayne State University 1
Northeast Normal University China 1
Central European University 1
University of Arizona 1
Rissho University 1
Istituto Di Calcolo E Reti Ad Alte Prestazioni, Rende 1
The University of British Columbia 1
Dartmouth College 1
Hohai University 1
The University of Western Ontario 1
Citigroup 1
Lingnan University 1
King's College London 1
Center for Mathematics and Computer Science - Amsterdam 1
University of Messina 1
University of Shizuoka 1
Aoyama Gakuin University 1
United States National Science Foundation 1
Ionian University 1
University of Passau 1
Eastman Kodak Company 1
University of Saskatchewan 1
General Electric Company 1
New York State Museum 1
Beijing Institute of Technology 1
Charles Stark Draper Lab Inc 1
University of Sussex 1
Defence Research and Development Canada 1
Nankai University 1
Vienna University of Technology 1
Washington State University Pullman 1
Office of Naval Research 1
Polytechnic School of Montreal 1
Netherlands Organisation for Applied Scientific Research - TNO 1
Binghamton University State University of New York 1
American University 1
Massachusetts General Hospital and Harvard Medical School 1
University of Surrey 1
Nanjing University of Aeronautics and Astronautics 1
Aalborg University 1
Naresuan University 1
Politecnico di Milano 1
Shanghai University 1
Soka University 1
Ecole Centrale Paris 1
National University of Defense Technology China 1
University of Fribourg 1
National Central University Taiwan 1
Dublin City University 1
Catholic University of Leuven, Leuven 1
The University of North Carolina at Chapel Hill 1
University of Cincinnati 1
University of Sydney 1
INSA Rouen 1
University of Udine 1
Institute of Intelligent Machines Chinese Academy of Sciences 1
Capital Medical University China 1
United States Military Academy 1
University of Quebec in Montreal 1
Yunnan University 1
Lanzhou University 1
Berlin University of Applied Sciences 1
Northeastern University 1
Fairleigh Dickinson University 1
Research Organization of Information and Systems National Institute of Informatics 1
University of Hawaii System 1
University of Chicago 1
University of Southern California 1
European Space Agency - ESA 1
University of California, Riverside 1
Institute of Applied Physics and Computational Mathematics 1
Columbia University 1
Texas State University-San Marcos 1
Ecole des Mines de Paris 1
Hosei University 1
Rutgers, The State University of New Jersey 1
Boeing Corporation 1
Santa Fe Institute 1
Michigan State University 1
University of Western Australia 1
Indian Institute of Technology Roorkee 1
North Dakota State University 1
University of Electro-Communications 1
Pontifical Catholic University of Rio de Janeiro 1
University of Jyvaskyla 1
University of Chittagong 1
University of Seville 1
Mehran University of Engineering & Technology 1
University of Sousse 1
Nanjing University of Information Science and Technology 1
Know-Center, Graz 1
Institute for Cancer Research and Treatment, Candiolo 1
Reykjavik University 1
Macau University of Science and Technology 1
SONY Computer Science Laboratory, Paris 1
Google Switzerland GmbH 1
Intel Research Laboratories 1, Inc. 1
Nanyang Technological University School of Computer Engineering 1
Florida Institute for Human & Machine Cognition 1
Fujitsu America, Inc. 1
Shandong University of Finance 1
Shandong Academy of Sciences 1
Austrian Institute of Technology 1
Laboratoire d'Informatique de Nantes-Atlantique 1
Yuncheng University 1
Liverpool Hope University 1
Qatar Foundation 1
CSIRO Data61 1
Shenzhen University 2
University of Texas at Arlington 2
University of Manchester 2
King Abdulaziz University 2
Southeast University China, Nanjing 2
University of Lugano 2
University of Missouri-Kansas City 2
University of Wolverhampton 2
University of Texas at El Paso 2
University of Brighton 2
Utrecht University 2
National University of Ireland, Galway 2
University of Massachusetts Dartmouth 2
Universite des Sciences et Technologies de Lille 2
Harvard University 2
University of Kent 2
RMIT University 2
Technical University of Berlin 2
Open University 2
University of Zurich 2
University of Antwerp 2
King Saud University 2
Telecom Bretagne 2
Aston University 2
University of Hawaii at Hilo 2
Aristotle University of Thessaloniki 2
University of Southern California, Information Sciences Institute 2
Dalhousie University 2
Academia Sinica Taiwan 2
National Tsing Hua University 2
Xiamen University 2
Technical University of Dresden 2
Tamkang University 2
University of Nebraska at Omaha 2
University of Bristol 2
East China Normal University 2
Communication University of China 2
Ecole d' Ingenieurs Telecom Lille 1 2
Johannes Kepler University Linz 2
Queen Mary, University of London 2
University of Central Florida 2
Waseda University 2
Lancaster University 2
University of Massachusetts Boston 2
University of Ferrara 2
Sam Houston State University 2
University of Oxford 2
University of Rochester 2
University of Edinburgh 2
Jerusalem College of Technology 2
Hungarian Academy of Sciences 2
New Mexico Institute of Mining and Technology 2
University of Athens 2
Universite de Rennes 1 2
University of California System 2
NEC Corporation 2
University of Verona 2
TU Dortmund University 2
Intel Corporation 2
U.S. Army Research Laboratory 2
American University of Beirut 2
Universite Paris-Est 2
Telecom & Management SudParis 2
SRI International 3
David R. Cheriton School of Computer Science 3
Universiti Sains Malaysia 3
Chalmers University of Technology 3
Universite Pierre et Marie Curie 3
University of Glasgow 3
University of Texas at San Antonio 3
University College Dublin 3
Brigham Young University 3
Jiangnan University 3
Universitat Politecnica de Catalunya 3
Orebro University 3
University of Wyoming 3
University of Texas at Dallas 3
Washington State University 3
Free University of Bozen-Bolzano 3
Universidad Politecnica de Valencia 3
Changchun University of Technology 3
BBN Technologies 3
University of Oregon 3
Philipps-Universitat Marburg 3
Beihang University 3
Universidad de Jaen 3
Georgia Tech Research Institute 3
University of Stuttgart 3
Kassel University 3
Wright State University 3
Simon Fraser University 3
Singapore Management University 3
Xerox Corporation 3
Graz University of Technology 3
New York University 3
University of Macau 3
University of Connecticut 3
University of North Texas 3
Universite Paris-Sud XI 3
University of Utah 3
University of Konstanz 3
Xidian University 3
University of Teesside 3
Huazhong University of Science and Technology 3
Center For Research And Technology - Hellas 3
Stony Brook University 3
University of Szeged 3
University of Bologna 3
University of Pisa 3
EURECOM Ecole d'Ingenieurs & Centre de Recherche en Systemes de Communication 3
University of California, San Diego 3
Utah State University 3
University of Wisconsin Madison 3
University of Roma La Sapienza 3
Intel Corporation, China 3
Rutgers University-Newark Campus 4
New Mexico State University Las Cruces 4
Bar-Ilan University 4
Toyohashi University of Technology 4
Ohio State University 4
University of Waikato 4
The University of North Carolina at Charlotte 4
University of Vermont 4
University of Adelaide 4
University of Florida 4
University of Pavia 4
University of Washington, Seattle 4
University of Trento 4
Technical University of Lodz 4
Tianjin University 4
University of Calabria 4
Guangxi Normal University 4
University of Liverpool 4
Indiana University 4
West Virginia University 4
University of Notre Dame 4
University of Florence 4
University of Virginia 4
Massachusetts Institute of Technology 4
University of Tehran 4
Swiss Federal Institute of Technology, Zurich 4
National University of Ireland, Maynooth 4
Microsoft Corporation 4
Complutense University of Madrid 4
Sharif University of Technology 4
University of Ottawa, Canada 4
University of California, Santa Barbara 4
University of Miami 4
Korea Advanced Institute of Science & Technology 4
Eindhoven University of Technology 4
Nanjing University 4
Cornell Tech 4
Institute for Infocomm Research, A-Star, Singapore 5
North Carolina State University 5
Google Inc. 5
University of California, Irvine 5
Soochow University 5
Istituto Di Scienze E Tecnologie Della Cognizione, Rome 5
City University of Hong Kong 5
University of Massachusetts Amherst 5
National Cheng Kung University 5
University of Pittsburgh 5
CSIC - Instituto de Investigacion en Inteligencia Artificial 5
University College London 5
Beijing Jiaotong University 5
Osaka University 5
Rensselaer Polytechnic Institute 5
Southern Illinois University at Carbondale 5
Max Planck Institute for Intelligent Systems 5
TECH Lab 5
Yahoo Research Barcelona 5
Istituto di Scienza e Tecnologie dell'Informazione A. Faedo 5
Pennsylvania State University 6
Virginia Commonwealth University 6
Hong Kong Polytechnic University 6
Washington University in St. Louis 6
National Taipei University of Technology 6
Hong Kong Baptist University 6
IBM Thomas J. Watson Research Center 6
NEC Laboratories America, Inc. 6
Texas A and M University 6
Missouri University of Science and Technology 6
Biblioteca CICESE 6
TELECOM ParisTech 6
University of Alberta 6
Ryerson University 6
Shandong University 6
University of South Australia 6
Universitat Pompeu Fabra 6
Hefei University of Technology 7
Stanford University 7
Oregon State University 7
George Mason University 7
Institute of Automation Chinese Academy of Sciences 7
University of Ulster 7
University of Bari 7
University of Southampton 7
Universidad Autonoma de Madrid 7
University of Queensland 7
Tel Aviv University 8
HP Labs 8
National Chiao Tung University Taiwan 8
Roma Tre University 8
Drexel University 8
University of Aberdeen 8
University of California, Berkeley 8
Ghent University 8
Northwestern Polytechnical University China 9
NASA Ames Research Center 9
Hong Kong University of Science and Technology 9
University of Texas at Austin 9
University of Waterloo 9
University of Illinois at Chicago 9
Bauhaus University Weimar 9
University of Turin 10
Beijing University of Posts and Telecommunications 10
Virginia Tech 10
Swiss Federal Institute of Technology, Lausanne 10
University of Minnesota Twin Cities 10
Federal University of Minas Gerais 10
Nanjing University of Science and Technology 11
Georgia Institute of Technology 11
University of Melbourne 11
Nokia Corporation 11
Zhejiang University 12
Shanghai Jiaotong University 12
Delft University of Technology 13
Polytechnic Institute of Turin 13
University of Technology Sydney 13
Chinese University of Hong Kong 14
University of California, Los Angeles 14
Florida International University 15
Yahoo Research Labs 15
Arizona State University 16
Tsinghua University 16
Carnegie Mellon University 16
Harbin Institute of Technology 17
University of Tokyo 18
Nanyang Technological University 19
University of Illinois at Urbana-Champaign 20
Microsoft Research 20
National Taiwan University 21
Institute of Computing Technology Chinese Academy of Sciences 21
Microsoft Research Asia 21
Peking University 22
Ben-Gurion University of the Negev 22
Jet Propulsion Laboratory 24
IBM Research 24
University of Maryland 29
University of Science and Technology of China 32
National University of Singapore 34
Chinese Academy of Sciences 35

ACM Transactions on Intelligent Systems and Technology (TIST)

Volume 8 Issue 4, May 2017  Issue-in-Progress
Volume 8 Issue 3, April 2017 Special Issue: Mobile Social Multimedia Analytics in the Big Data Era and Regular Papers
Volume 8 Issue 2, January 2017 Survey Paper, Special Issue: Intelligent Music Systems and Applications and Regular Papers

Volume 8 Issue 1, October 2016
Volume 7 Issue 4, July 2016 Special Issue on Crowd in Intelligent Systems, Research Note/Short Paper and Regular Papers
Volume 7 Issue 3, April 2016 Regular Papers, Survey Papers and Special Issue on Recommender System Benchmarks
Volume 7 Issue 2, January 2016 Special Issue on Causal Discovery and Inference

Volume 7 Issue 1, October 2015
Volume 6 Issue 4, August 2015 Regular Papers and Special Section on Intelligent Healthcare Informatics
Volume 6 Issue 3, May 2015 Survey Paper, Regular Papers and Special Section on Participatory Sensing and Crowd Intelligence
Volume 6 Issue 2, May 2015 Special Section on Visual Understanding with RGB-D Sensors
Volume 6 Issue 1, April 2015
Volume 5 Issue 4, January 2015 Special Sections on Diversity and Discovery in Recommender Systems, Online Advertising and Regular Papers

Volume 5 Issue 3, September 2014 Special Section on Urban Computing
Volume 5 Issue 2, April 2014 Special Issue on Linking Social Granularity and Functions

Volume 5 Issue 1, December 2013 Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
Volume 4 Issue 4, September 2013 Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Volume 4 Issue 3, June 2013 Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
Volume 4 Issue 2, March 2013 Special section on agent communication, trust in multiagent systems, intelligent tutoring and coaching systems
Volume 4 Issue 1, January 2013 Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context

Volume 3 Issue 4, September 2012
Volume 3 Issue 3, May 2012
Volume 3 Issue 2, February 2012

Volume 3 Issue 1, October 2011
Volume 2 Issue 4, July 2011
Volume 2 Issue 3, April 2011
Volume 2 Issue 2, February 2011
Volume 2 Issue 1, January 2011

Volume 1 Issue 2, November 2010
Volume 1 Issue 1, October 2010
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