High Correlation Of Middle East Respiratory Syndrome Spread With Google Search And Twitter Trends In Korea,
2016
Singapore Management University
High Correlation Of Middle East Respiratory Syndrome Spread With Google Search And Twitter Trends In Korea, Soo-Yong Shin, Dong-Woo Seo, Jisun An, Haewoon Kwak, Sung-Han Kim, Jin Gwack, Min-Woo Jo
Research Collection School Of Computing and Information Systems
The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26, 2015 using the Korean government MERS portal. The daily trends observed via Google search and Twitter during the same time period were also ascertained using Google Trends and Topsy. Correlations among the data were then examined using Spearman …
Autoquery: Automatic Construction Of Dependency Queries For Code Search,
2016
Singapore Management University
Autoquery: Automatic Construction Of Dependency Queries For Code Search, Shaowei Wang, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Many code search techniques have been proposed to return relevant code for a user query expressed as textual descriptions. However, source code is not mere text. It contains dependency relations among various program elements. To leverage these dependencies for more accurate code search results, techniques have been proposed to allow user queries to be expressed as control and data dependency relationships among program elements. Although such techniques have been shown to be effective for finding relevant code, it remains a question whether appropriate queries can be generated by average users. In this work, we address this concern by proposing a …
Control Flow Integrity Enforcement With Dynamic Code Optimization,
2016
Singapore Management University
Control Flow Integrity Enforcement With Dynamic Code Optimization, Yan Lin, Xiaoxiao Tang, Debin Gao, Jianming Fu
Research Collection School Of Computing and Information Systems
Control Flow Integrity (CFI) is an attractive security property with which most injected and code reuse attacks can be defeated, including advanced attacking techniques like Return-Oriented Programming (ROP). However, comprehensive enforcement of CFI is expensive due to additional supports needed (e.g., compiler support and presence of relocation or debug information) and performance overhead. Recent research has been trying to strike the balance among reasonable approximation of the CFI properties, minimal additional supports needed, and acceptable performance. We investigate existing dynamic code optimization techniques and find that they provide an architecture on which CFI can be enforced effectively and efficiently. In …
Soft Confidence-Weighted Learning,
2016
University of Chicago
Soft Confidence-Weighted Learning, Jialei Wang, Peilin Zhao, Hoi, Steven C. H.
Research Collection School Of Computing and Information Systems
Online learning plays an important role in many big datamining problems because of its high efficiency and scalability. In theliterature, many online learning algorithms using gradient information havebeen applied to solve online classification problems. Recently, more effectivesecond-order algorithms have been proposed, where the correlation between thefeatures is utilized to improve the learning efficiency. Among them,Confidence-Weighted (CW) learning algorithms are very effective, which assumethat the classification model is drawn from a Gaussian distribution, whichenables the model to be effectively updated with the second-order informationof the data stream. Despite being studied actively, these CW algorithms cannothandle nonseparable datasets and noisy datasets very …
Extracting Food Substitutes From Food Diary Via Distributional Similarity,
2016
Singapore Management University
Extracting Food Substitutes From Food Diary Via Distributional Similarity, Palakorn Achananuparp, Ingmar Weber
Research Collection School Of Computing and Information Systems
In this paper, we explore the problem of identifying substitute relationship between food pairs from real-world food consumption data as the first step towards the healthier food recommendation. Our method is inspired by the distributional hypothesis in linguistics. Specifically, we assume that foods that are consumed in similar contexts are more likely to be similar dietarily. For example, a turkey sandwich can be considered a suitable substitute for a chicken sandwich if both tend to be consumed with french fries and salad. To evaluate our method, we constructed a real-world food consumption dataset from MyFitnessPal's public food diary entries and …
Probabilistic Models For Contextual Agreement In Preferences,
2016
Singapore Management University
Probabilistic Models For Contextual Agreement In Preferences, Loc Do, Hady W. Lauw
Research Collection School Of Computing and Information Systems
The long-tail theory for consumer demand implies the need for more accurate personalization technologies to target items to the users who most desire them. A key tenet of personalization is the capacity to model user preferences. Most of the previous work on recommendation and personalization has focused primarily on individual preferences. While some focus on shared preferences between pairs of users, they assume that the same similarity value applies to all items. Here we investigate the notion of "context," hypothesizing that while two users may agree on their preferences on some items, they may also disagree on other items. To …
Detecting Community Pacemakers Of Burst Topic In Twitter,
2016
Harbin Engineering University
Detecting Community Pacemakers Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang
Research Collection School Of Computing and Information Systems
Twitter has become one of largest social networks for users to broad-cast burst topics. Influential users usually have a large number of followers and play an important role in the diffusion of burst topic. There have been many studies on how to detect influential users. However, traditional influential users detection approaches have largely ignored influential users in user community. In this paper, we investigate the problem of detecting community pacemakers. Community pacemakers are defined as the influential users that promote early diffusion in the user community of burst topic. To solve this problem, we present DCPBT, a framework that can …
Cross-Cultural User Perceptions Of Website Design And Security: Introduction To A Commentary And Response On Cyr (2013),
2016
Singapore Management University
Cross-Cultural User Perceptions Of Website Design And Security: Introduction To A Commentary And Response On Cyr (2013), Robert John Kauffman
Research Collection School Of Computing and Information Systems
Just as the well-known statistician, George Box, commented in a 1978 paper, “All models are wrong, but some are useful,” so are there many ways to design research inquiry approaches to explore issues in various e-commerce contexts – all useful too. In the two brief essays that follow, the reader will see a written commentary and a response that illustrates this idea. It occurred between a technology researcher who published an article on cross-cultural issues in website design in Cyr (2013), and an economist who is able to offer useful insights on the statistical work and data analytics with methods …
Microblogging Content Propagation Modeling Using Topic-Specific Behavioral Factors,
2016
Singapore Management University
Microblogging Content Propagation Modeling Using Topic-Specific Behavioral Factors, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
When a microblogging user adopts some content propagated to her, we can attribute that to three behavioral factors, namely, topic virality, user virality, and user susceptibility. Topic virality measures the degree to which a topic attracts propagations by users. User virality and susceptibility refer to the ability of a user to propagate content to other users, and the propensity of a user adopting content propagated to her, respectively. In this paper, we study the problem of mining these behavioral factors specific to topics from microblogging content propagation data. We first construct a three dimensional tensor for representing the propagation instances. …
Is Only One Gps Position Sufficient To Locate You To The Road Network Accurately?,
2016
Singapore Management University
Is Only One Gps Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng
Research Collection School Of Computing and Information Systems
Locating only one GPS position to a road segment accurately is crucial to many location-based services such as mobile taxihailing service, geo-tagging, POI check-in, etc. This problem is challenging because of errors including the GPS errors and the digital map errors (misalignment and the same representation of bidirectional roads) and a lack of context information. To the best of our knowledge, no existing work studies this problem directly and the work to reduce GPS signal errors by considering hardware aspect is the most relevant. Consequently, this work is the first attempt to solve the problem of locating one GPS position …
Metaflow: A Scalable Metadata Lookup Service For Distributed File Systems In Data Centers,
2016
Singapore Management University
Metaflow: A Scalable Metadata Lookup Service For Distributed File Systems In Data Centers, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Haiyong Xie
Research Collection School Of Computing and Information Systems
In large-scale distributed file systems, efficient metadata operations are critical since most file operations have to interact with metadata servers first. In existing distributed hash table (DHT) based metadata management systems, the lookup service could be a performance bottleneck due to its significant CPU overhead. Our investigations showed that the lookup service could reduce system throughput by up to 70%, and increase system latency by a factor of up to 8 compared to ideal scenarios. In this paper, we present MetaFlow, a scalable metadata lookup service utilizing software-defined networking (SDN) techniques to distribute lookup workload over network components. MetaFlow tackles …
Study On The Application Of Information Technology In Inland Maritime Supervision,
2016
World Maritime University
Study On The Application Of Information Technology In Inland Maritime Supervision, Chong He
Maritime Safety & Environment Management Dissertations (Dalian)
No abstract provided.
Important Considerations For Human Activity Recognition Using Sensor Data,
2016
Rose-Hulman Institute of Technology
Important Considerations For Human Activity Recognition Using Sensor Data, Matt Buckner
Rose-Hulman Undergraduate Research Publications
Automated human activity recognition has received much attention in recent years due to increasing focus on interconnected devices in The Internet of Things (IoT) and the miniaturization and proliferation of sensor systems with the adoption of smartphones. In this work, we focus on the current status of human activity recognition across multiple studies, including methodology, accuracy of results, and current challenges to implementation. We include some preliminary work we have completed on a sensor system for classifying treadmill usage.
Real Time Activity Recognition Of Treadmill Usage Via Machine Learning,
2016
Rose-Hulman Institute of Technology
Real Time Activity Recognition Of Treadmill Usage Via Machine Learning, Nathan Blank, Matt Buckner, Christian Owen, Anna Scott
Rose-Hulman Undergraduate Research Publications
Our objective is to provide real-time classification of treadmill usage patterns based on accelerometer and magnetometer measurements. We collected data from treadmills in the Rose-Hulman Student Recreation Center (SRC) using Shimmer3 sensor units. We identified useful data features and classifiers for predicting treadmill usage patterns. We also prototyped a proof of concept wireless, real-time classification system.
Topic Extraction From Microblog Posts Using Conversation Structures,
2016
Singapore Management University
Topic Extraction From Microblog Posts Using Conversation Structures, Jing Li, Ming Liao, Wei Gao, Yulan He, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Conventional topic models are ineffective for topic extraction from microblog messages since the lack of structure and context among the posts renders poor message-level word co-occurrence patterns. In this work, we organize microblog posts as conversation trees based on reposting and replying relations, which enrich context information to alleviate data sparseness. Our model generates words according to topic dependencies derived from the conversation structures. In specific, we differentiate messages as leader messages, which initiate key aspects of previously focused topics or shift the focus to different topics, and follower messages that do not introduce any new information but simply echo …
A Novel Digital Image Classification Algorithm Via Low-Rank Sparse Bag-Of-Features Model,
2016
Singapore Management University
A Novel Digital Image Classification Algorithm Via Low-Rank Sparse Bag-Of-Features Model, Xiu-Ming Zou, Huai-Jiang Sun, Sai Yang, Yan Zhu
Research Collection School of Computing and Information Systems
Bag-of-features (BoF) is one of the most well-known methods used to represent digital image features because of its simplicity and efficiency. A variety of improved algorithms have been employed to enhance the performance of BoF in characterization. However, challenges in the application of BoF in the field still exist. This study focused on BoF by decomposing local features and presented a novel framework for BoF on the basis of low-rank and sparse matrix decomposition to obtain a more robust and discriminative digital image classification. First, the local feature matrix of a digital image is decomposed into a low-rank matrix and …
Profiling Social Media Users With Selective Self-Disclosure Behavior,
2016
Singapore Management University
Profiling Social Media Users With Selective Self-Disclosure Behavior, Wei Gong
Dissertations and Theses Collection
Social media has become a popular platform for millions of users to share activities and thoughts. Many applications are now tapping on social media to disseminate information (e.g., news), to promote products (e.g., advertisements), to manage customer relationship (e.g., customer feedback), and to source for investment (e.g., crowdfunding). Many of these applications require user profile knowledge to select the target social media users or to personalize messages to users. Social media user profiling is a task of constructing user profiles such as demographical labels, interests, and opinions, etc., using social media data. Among the social media user profiling research works, …
Analyzing Clinical Depressive Symptoms In Twitter,
2016
Wright State University - Main Campus
Analyzing Clinical Depressive Symptoms In Twitter, Amir Hossein Yazdavar, Hussein S. Al-Olimat, Tanvi Banerjee, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
350 million people are suffering from clinical depression worldwide.
Unsupervised Multi-Graph Cross-Modal Hashing For Large-Scale Multimedia Retrieval,
2016
Wuhan University of Technology
Unsupervised Multi-Graph Cross-Modal Hashing For Large-Scale Multimedia Retrieval, Liang Xie, Lei Zhu, Guoqi Chen
Research Collection School Of Computing and Information Systems
With the advance of internet and multimedia technologies, large-scale multi-modal representation techniques such as cross-modal hashing, are increasingly demanded for multimedia retrieval. In cross-modal hashing, three essential problems should be seriously considered. The first is that effective cross-modal relationship should be learned from training data with scarce label information. The second is that appropriate weights should be assigned for different modalities to reflect their importance. The last is the scalability of training process which is usually ignored by previous methods. In this paper, we propose Multi-graph Cross-modal Hashing (MGCMH) by comprehensively considering these three points. MGCMH is unsupervised method which …
User Identity Linkage By Latent User Space Modelling,
2016
Nanjing University
User Identity Linkage By Latent User Space Modelling, Xin Mu, Feida Zhu, Ee-Peng Lim, Jing Xiao, Jianzong Wang, Zhi-Hua Zhou
Research Collection School Of Computing and Information Systems
User identity linkage across social platforms is an important problem of great research challenge and practical value. In real applications, the task often assumes an extra degree of difficulty by requiring linkage across multiple platforms. While pair-wise user linkage between two platforms, which has been the focus of most existing solutions, provides reasonably convincing linkage, the result depends by nature on the order of platform pairs in execution with no theoretical guarantee on its stability. In this paper, we explore a new concept of “Latent User Space” to more naturally model the relationship between the underlying real users and their …
