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Extracting City Traffic Events from Social Streams
Pramod Anantharam, Payam Barnaghi, Krishnaprasad Thirunarayan, Amit Sheth
Article No.: 43
Cities are composed of complex systems with physical, cyber, and social components. Current works on extracting and understanding city events mainly rely on technology-enabled infrastructure to observe and record events. In this work, we propose...
Automated Generation of Counterterrorism Policies Using Multiexpert Input
Anshul Sawant, John P. Dickerson, Mohammad T. Hajiaghayi, V. S. Subrahmanian
Article No.: 44
The use of game theory to model conflict has been studied by several researchers, spearheaded by Schelling. Most of these efforts assume a single payoff matrix that captures players’ utilities under different assumptions about what the...
Online Planning for Large Markov Decision Processes with Hierarchical Decomposition
Aijun Bai, Feng Wu, Xiaoping Chen
Article No.: 45
Markov decision processes (MDPs) provide a rich framework for planning under uncertainty. However, exactly solving a large MDP is usually intractable due to the “curse of dimensionality”— the state space grows exponentially with...
In recent years, crimes against children and cases of missing children have increased at a high rate. Therefore, there is an urgent need for safety support systems to prevent crimes against children or for antiloss, especially when parents are not...
Peacock: Learning Long-Tail Topic Features for Industrial Applications
Yi Wang, Xuemin Zhao, Zhenlong Sun, Hao Yan, Lifeng Wang, Zhihui Jin, Liubin Wang, Yang Gao, Ching Law, Jia Zeng
Article No.: 47
Latent Dirichlet allocation (LDA) is a popular topic modeling technique in academia but less so in industry, especially in large-scale applications involving search engine and online advertising systems. A main underlying reason is that the topic...
Automated Pricing in a Multiagent Prediction Market Using a Partially Observable Stochastic Game
Janyl Jumadinova, Prithviraj Dasgupta
Article No.: 48
Prediction markets offer an efficient market-based mechanism to aggregate large amounts of dispersed or distributed information from different people to predict the possible outcome of future events. Recently, automated prediction markets where...
Effective Social Graph Deanonymization Based on Graph Structure and Descriptive Information
Hao Fu, Aston Zhang, Xing Xie
Article No.: 49
The study of online social networks has attracted increasing interest. However, concerns are raised for the privacy risks of user data since they have been frequently shared among researchers, advertisers, and application developers. To solve this...
Hazy Image Restoration by Bi-Histogram Modification
Bo-Hao Chen, Shih-Chia Huang, Jian Hui Ye
Article No.: 50
Visibility restoration techniques are widely used for information recovery of hazy images in many computer vision applications. Estimation of haze density is an essential task of visibility restoration techniques. However, conventional visibility...
Introduction to the ACM TIST Special Issue on Intelligent Healthcare Informatics
Carlo Combi, Jiming Liu
Article No.: 51
Analyzing Activity Recognition Uncertainties in Smart Home Environments
Eunju Kim, Sumi Helal, Chris Nugent, Mark Beattie
Article No.: 52
In spite of the importance of activity recognition (AR) for intelligent human-computer interaction in emerging smart space applications, state-of-the-art AR technology is not ready or adequate for real-world deployments due to its insufficient...
Design of a Predictive Scheduling System to Improve Assisted Living Services for Elders
Valeria Soto-Mendoza, J. Antonio García-Macías, Edgar Chávez, Ana I. Martínez-García, Jesús Favela, Patricia Serrano-Alvarado, Maythé R. Zúñiga Rojas
Article No.: 53
As the number of older adults increases, and with it the demand for dedicated care, geriatric residences face a shortage of caregivers, who themselves experience work overload, stress, and burden. We conducted a long-term field study in three...
Empowering Patients and Caregivers to Manage Healthcare Via Streamlined Presentation of Web Objects Selected by Modeling Learning Benefits Obtained by Similar Peers
John Champaign, Robin Cohen, Disney Yan Lam
Article No.: 54
In this article, we introduce a framework for selecting web objects (texts, videos, simulations) from a large online repository to present to patients and caregivers, in order to assist in their healthcare. Motivated by the paradigm of peer-based...
Using Health-Consumer-Contributed Data to Detect Adverse Drug Reactions by Association Mining with Temporal Analysis
Haodong Yang, Christopher C. Yang
Article No.: 55
Since adverse drug reactions (ADRs) represent a significant health problem all over the world, ADR detection has become an important research topic in drug safety surveillance. As many potential ADRs cannot be detected though premarketing review,...
Estimating a Ranked List of Human Genetic Diseases by Associating Phenotype-Gene with Gene-Disease Bipartite Graphs
Md Zia Ullah, Masaki Aono, Md Hanif Seddiqui
Article No.: 56
With vast amounts of medical knowledge available on the Internet, it is becoming increasingly practical to help doctors in clinical diagnostics by suggesting plausible diseases predicted by applying data and text mining technologies. Recently,...
MeTA: Characterization of Medical Treatments at Different Abstraction Levels
Dario Antonelli, Elena Baralis, Giulia Bruno, Luca Cagliero, Tania Cerquitelli, Silvia Chiusano, Paolo Garza, Naeem A. Mahoto
Article No.: 57
Physicians and health care organizations always collect large amounts of data during patient care. These large and high-dimensional datasets are usually characterized by an inherent sparseness. Hence, analyzing these datasets to figure out...
Smart Colonography for Distributed Medical Databases with Group Kernel Feature Analysis
Yuichi Motai, Dingkun Ma, Alen Docef, Hiroyuki Yoshida
Article No.: 58
Computer-Aided Detection (CAD) of polyps in Computed Tomographic (CT) colonography is currently very limited since a single database at each hospital/institution doesn't provide sufficient data for training the CAD system's classification...
Recognition of Patient-Related Named Entities in Noisy Tele-Health Texts
Mi-Young Kim, Ying Xu, Osmar R. Zaiane, Randy Goebel
Article No.: 59
We explore methods for effectively extracting information from clinical narratives that are captured in a public health consulting phone service called HealthLink. Our research investigates the application of state-of-the-art natural language...