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Articles 4951 - 4980 of 8481
Full-Text Articles in Computer Sciences
Dynamic-Music: Accurate Device-Free Indoor Localization, Xiang Li, Shengjie Li, Daqing Zhang, Jie Xiong, Yasha Wang, Hong Mei
Dynamic-Music: Accurate Device-Free Indoor Localization, Xiang Li, Shengjie Li, Daqing Zhang, Jie Xiong, Yasha Wang, Hong Mei
Research Collection School Of Computing and Information Systems
Device-free passive indoor localization is playing a critical role in many applications such as elderly care, intrusion detection, smart home, etc. However, existing device-free localization systems either suffer from labor-intensive offline training or require dedicated special-purpose devices. To address the challenges, we present our system named MaTrack, which is implemented on commodity off-the-shelf Intel 5300 Wi-Fi cards. MaTrack proposes a novel Dynamic-MUSIC method to detect the subtle reflection signals from human body and further differentiate them from those reflected signals from static objects (furniture, walls, etc.) to identify the human target's angle for localization. MaTrack does not require any offline …
Control Flow Integrity Enforcement With Dynamic Code Optimization, Yan Lin, Xiaoxiao Tang, Debin Gao, Jianming Fu
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, Jialei Wang, Peilin Zhao, Hoi, Steven C. H.
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 …
Mining Revision Histories To Detect Cross-Language Clones Without Intermediates, Lingxiao Jiang, Zhiming Peng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao
Mining Revision Histories To Detect Cross-Language Clones Without Intermediates, Lingxiao Jiang, Zhiming Peng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao
Research Collection School Of Computing and Information Systems
To attract more users on different platforms, many projects release their versions in multiple programming languages (e.g., Java and C#). They typically have many code snippets that implement similar functionalities, i.e., cross-language clones. Programmers often need to track and modify cross-language clones consistently to maintain similar functionalities across different language implementations. In literature, researchers have proposed approaches to detect cross-language clones, mostly for languages that share a common intermediate language (such as the .NET language family) so that techniques for detecting single-language clones can be applied. As a result, those approaches cannot detect cross-language clones for many projects that are …
On The Feasibility Of Detecting Cross-Platform Code Clones Via Identifier Similarity, Xiao Cheng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao
On The Feasibility Of Detecting Cross-Platform Code Clones Via Identifier Similarity, Xiao Cheng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao
Research Collection School Of Computing and Information Systems
More and more mobile applications run on multiple mobile operating systems to attract more users of different platforms. Although versions on different platforms are implemented in different programming languages (e.g., Java and Objective-C), there must be many code snippets that implement the similar business logic on different platforms. Such code snippets are called cross-platform clones. It is challenging but essential to detect such clones for software maintenance. Due to the practice that developers usually use some common identifiers when implementing the same business logic on different platforms, in this paper, we investigate the identifier similarity of the same mobile application …
Detecting Community Pacemakers Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang
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 …
Extracting Food Substitutes From Food Diary Via Distributional Similarity, Palakorn Achananuparp, Ingmar Weber
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 …
Cross-Cultural User Perceptions Of Website Design And Security: Introduction To A Commentary And Response On Cyr (2013), Robert John Kauffman
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 …
Trustworthy Authentication On Scalable Surveillance Video With Background Model Support, Zhuo Wei, Zheng Yan, Yongdong Wu, Robert H. Deng
Trustworthy Authentication On Scalable Surveillance Video With Background Model Support, Zhuo Wei, Zheng Yan, Yongdong Wu, Robert H. Deng
Research Collection School Of Computing and Information Systems
H.264/SVC (Scalable Video Coding) codestreams, which consist of a single base layer and multiple enhancement layers, are designed for quality, spatial, and temporal scalabilities. They can be transmitted over networks of different bandwidths and seamlessly accessed by various terminal devices. With a huge amount of video surveillance and various devices becoming an integral part of the security infrastructure, the industry is currently starting to use the SVC standard to process digital video for surveillance applications such that clients with different network bandwidth connections and display capabilities can seamlessly access various SVC surveillance (sub)codestreams. In order to guarantee the trustworthiness and …
Microblogging Content Propagation Modeling Using Topic-Specific Behavioral Factors, Tuan Anh Hoang, Ee-Peng Lim
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. …
Predicting Crashing Releases Of Mobile Applications, Xin Xia, Emad Shihab, Yasutaka Kamei, David Lo, Xinyu Wang
Predicting Crashing Releases Of Mobile Applications, Xin Xia, Emad Shihab, Yasutaka Kamei, David Lo, Xinyu Wang
Research Collection School Of Computing and Information Systems
Context: The quality of mobile applications has a vital impact on their user's experience, ratings and ultimately overall success. Given the high competition in the mobile application market, i.e., many mobile applications perform the same or similar functionality, users of mobile apps tend to be less tolerant to quality issues. Goal: Therefore, identifying these crashing releases early on so that they can be avoided will help mobile app developers keep their user base and ensure the overall success of their apps. Method: To help mobile developers, we use machine learning techniques to effectively predict mobile app releases that are more …
Is Only One Gps Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng
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 …
Automated Bug Report Field Reassignment And Refinement Prediction, Xin Xia, David Lo, Emad Shihab, Xinyu Wang
Automated Bug Report Field Reassignment And Refinement Prediction, Xin Xia, David Lo, Emad Shihab, Xinyu Wang
Research Collection School Of Computing and Information Systems
Bug fixing is one of the most important activities in software development and maintenance. Bugs are reported, recorded, and managed in bug tracking systems such as Bugzilla. In general, a bug report contains many fields, such as product, component, severity, priority, fixer, operating system (OS), and platform, which provide important information for the bug triaging and fixing process. Our previous study finds that approximately 80% of bug reports have their fields reassigned and refined at least once, and bugs with reassigned and refined fields take more time to fix than bugs with no reassigned and refined fields. Thus, automatically predicting …
Tasker: Behavioral Insights Via Campus-Based Experimental Mobile Crowd-Sourcing, Thivya Kandappu, Jaiman, Tandriansyah, Archan Misra, Shih-Fen Cheng, Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta
Tasker: Behavioral Insights Via Campus-Based Experimental Mobile Crowd-Sourcing, Thivya Kandappu, Jaiman, Tandriansyah, Archan Misra, Shih-Fen Cheng, Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta
Research Collection School Of Computing and Information Systems
While mobile crowd-sourcing has become a game-changer for many urban operations, such as last mile logistics and municipal monitoring, we believe that the design of such crowdsourcing strategies must better accommodate the real-world behavioral preferences and characteristics of users. To provide a real-world testbed to study the impact of novel mobile crowd-sourcing strategies, we have designed, developed and experimented with a real-world mobile crowd-tasking platform on the SMU campus, called TA$Ker. We enhanced the TA$Ker platform to support several new features (e.g., task bundling, differential pricing and cheating analytics) and experimentally investigated these features via a two-month deployment of TA$Ker, …
A Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Archan Misra, Randy Tandriansyah Daratan, Thivya Kandappu
A Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Archan Misra, Randy Tandriansyah Daratan, Thivya Kandappu
Research Collection School Of Computing and Information Systems
By effectively utilizing smartphones to reach out and engage a large population of mobile users, mobile crowdsourcing can become a game-changer for many urban operations, such as last mile logistics and municipal monitoring. To overcome the uncertainties and risks associated with a purely best-effort, opportunistic model of such crowdsourcing, we advocate a more centrally-coordinated approach, that (a) takes into account the predicted movement paths of workers and (b) factors in typical human behavioral responses to various incentives and deadlines. To experimentally tackle these challenges, we design, develop and experiment with a real-world mobile crowd-Tasking platform on an urban campus in …
Indoor Localization Via Multi-Modal Sensing On Smartphones, Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Ke Yi, Yunhao Liu
Indoor Localization Via Multi-Modal Sensing On Smartphones, Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Ke Yi, Yunhao Liu
Research Collection School Of Computing and Information Systems
Indoor localization is of great importance to a wide range ofapplications in shopping malls, office buildings and publicplaces. The maturity of computer vision (CV) techniques andthe ubiquity of smartphone cameras hold promise for offering sub-meter accuracy localization services. However, pureCV-based solutions usually involve hundreds of photos andpre-calibration to construct image database, a labor-intensiveoverhead for practical deployment. We present ClickLoc, anaccurate, easy-to-deploy, sensor-enriched, image-based indoor localization system. With core techniques rooted insemantic information extraction and optimization-based sensor data fusion, ClickLoc is able to bootstrap with few images. Leveraging sensor-enriched photos, ClickLoc also enables user localization with a single photo of the …
Developers’ Perceptions On Object-Oriented Design And Architectural Roles, Maurício Aniche, Marco Aurélio Gerosa, Christoph Treude
Developers’ Perceptions On Object-Oriented Design And Architectural Roles, Maurício Aniche, Marco Aurélio Gerosa, Christoph Treude
Research Collection School Of Computing and Information Systems
Software developers commonly rely on well-known software architecture patterns, such as MVC, to build their applications. In many of these patterns, classes play specific roles in the system, such as Controllers or Entities, which means that each of these classes has specific characteristics in terms of object-oriented class design and implementation. Indeed, as we have shown in a previous study, architectural roles are different from each other in terms of code metrics. In this paper, we present a study in a software development company in which we captured developers’ perceptions on object-oriented design aspects of the architectural roles in their …
Leveraging Competency Framework To Improve Teaching And Learning: A Methodological Approach, Venky Shankararaman, Joelle Elmaleh
Leveraging Competency Framework To Improve Teaching And Learning: A Methodological Approach, Venky Shankararaman, Joelle Elmaleh
Research Collection School Of Computing and Information Systems
A number of engineering education programs have defined learning outcomes and course-level competencies, and conducted assessments at the program level to determine areas for continuous improvement. However, many of these programs have not implemented a comprehensive competency framework to support the actual delivery and assessment of an individual course. This paper highlights how a competency framework can be used across the life cycle of a course to effectively deliver and assess course content, and give valuable, timely feedback to students thus, improving teaching, student motivation and learning. A framework for leveraging course competencies during course design and delivery is presented, …
Towards Autonomous Behavior Learning Of Non-Player Characters In Games, Shu Feng, Ah-Hwee Tan
Towards Autonomous Behavior Learning Of Non-Player Characters In Games, Shu Feng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Non-Player-Characters (NPCs), as found in computer games, can be modelled as intelligent systems, which serve to improve the interactivity and playability of the games. Although reinforcement learning (RL) has been a promising approach to creating the behavior models of non-player characters (NPC), an initial stage of exploration and low performance is typically required. On the other hand, imitative learning (IL) is an effective approach to pre-building a NPC’s behavior model by observing the opponent’s actions, but learning by imitation limits the agent’s performance to that of its opponents. In view of their complementary strengths, this paper proposes a computational model …
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
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 …
Fast Covariant Vlad For Image Search, Wan-Lei Zhao, Chong-Wah Ngo, Hanzi Wang
Fast Covariant Vlad For Image Search, Wan-Lei Zhao, Chong-Wah Ngo, Hanzi Wang
Research Collection School Of Computing and Information Systems
Vector of locally aggregated descriptor (VLAD) is a popular image encoding approach for its simplicity and better scalability over conventional bag-of-visual-word approach. In order to enhance its distinctiveness and geometric invariance, covariant VLAD (CVLAD) is proposed to pool local features based on their dominant orientations/characteristic scales, which leads to a geometric-aware representation. This representation achieves rotation/scale invariance when being associated with circular matching. However, the circular matching induces several times of computation overhead, which makes CVLAD hardly suitable for large-scale retrieval tasks. In this paper, the issue of computation overhead is alleviated by performing the circular matching in CVLAD's frequency …
Topic Extraction From Microblog Posts Using Conversation Structures, Jing Li, Ming Liao, Wei Gao, Yulan He, Kam-Fai Wong
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 …
Singapore In Motion: Insights On Public Transport Service Level Through Farecard And Mobile Data Analytics, Hasan Poonawala, Vinay Kolar, Sebastien Blandin, Laura Wynter, Sambit Sahu
Singapore In Motion: Insights On Public Transport Service Level Through Farecard And Mobile Data Analytics, Hasan Poonawala, Vinay Kolar, Sebastien Blandin, Laura Wynter, Sambit Sahu
Research Collection School Of Computing and Information Systems
Given the changing dynamics of mobility patterns and rapid growth of cities, transport agencies seek to respond more rapidly to needs of the public with the goal of offering an effective and competitive public transport system. A more data-centric approach for transport planning is part of the evolution of this process. In particular, the vast penetration of mobile phones provides an opportunity to monitor and derive insights on transport usage. Real time and historical analyses of such data can give a detailed understanding of mobility patterns of people and also suggest improvements to current transit systems. On its own, however, …
Enhancing Local Search With Adaptive Operator Ordering And Its Application To The Time Dependent Orienteering Problem, Aldy Gunawan, Hoong Chuin Lau, Kun Lu
Enhancing Local Search With Adaptive Operator Ordering And Its Application To The Time Dependent Orienteering Problem, Aldy Gunawan, Hoong Chuin Lau, Kun Lu
Research Collection School Of Computing and Information Systems
No abstract provided.
Intermediaries Vs Peer-To-Peer: A Study Of Lenders’ Incentive On A Donation-Based Crowdfunding Platform, Ling Ge, Zhiling Guo, Xuechen Luo
Intermediaries Vs Peer-To-Peer: A Study Of Lenders’ Incentive On A Donation-Based Crowdfunding Platform, Ling Ge, Zhiling Guo, Xuechen Luo
Research Collection School Of Computing and Information Systems
Donation-based crowdfunding platform Kiva seems to hold the promise of peer-to-peer lending with zero interest rate to help the poor. However, it is actually intermediated by microfinance institutions, which raise funds from Kiva lenders, disburse the funds to borrowers and collect high interest. Later Kiva launched another platform Kiva Zip that implements interest-free loans directly from lenders to borrowers. This unique setup enables us to examine how lenders choose between Kiva and Kiva Zip, i.e. a platform with intermediaries and a real P2P platform. We develop a theoretical model and explicate that the lenders trade-off is between the sustainability of …
Extending The Network: The Influence Of Offline Friendship On Twitter Network, Young Soo Kim, Kyungsub Stephen Choi, Felicia Natali
Extending The Network: The Influence Of Offline Friendship On Twitter Network, Young Soo Kim, Kyungsub Stephen Choi, Felicia Natali
Research Collection School Of Computing and Information Systems
Twitter effectively provides a communication platform that allows users to strengthen or augment relationships with their close ones. It is a common scene to see groups of people in continuing group communication from offline to online using tools such as Twitter. Furthermore, it is also possible to meet new friends via online encounter. Under these circumstances, there would be friends who are both offline and online, or only in online. Many of earlier Twitter network studies focused on the network effects’ direction going from online to offline network. This paper explores the opposite direction, going from offline to online network. …
Safegpu: Contract- And Library-Based Gpgpu For Object-Oriented Languages, Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz
Safegpu: Contract- And Library-Based Gpgpu For Object-Oriented Languages, Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz
Research Collection School Of Computing and Information Systems
Using GPUs as general-purpose processors has revolutionized parallel computing by providing, for a large and growing set of algorithms, massive data-parallelization on desktop machines. An obstacle to their widespread adoption, however, is the difficulty of programming them and the low-level control of the hardware required to achieve good performance. This paper proposes a programming approach, SafeGPU, that aims to make GPU data-parallel operations accessible through high-level libraries for object-oriented languages, while maintaining the performance benefits of lower-level code. The approach provides data-parallel operations for collections that can be chained and combined to express compound computations, with data synchronization and device …
Api Recommendation System For Software Development, Ferdian Thung
Api Recommendation System For Software Development, Ferdian Thung
Research Collection School Of Computing and Information Systems
Nowadays, software developers often utilize existing third party libraries and make use of Application Programming Interface (API) to develop a software. However, it is not always obvious which library to use or whether the chosen library will play well with other libraries in the system. Furthermore, developers need to spend some time to understand the API to the point that they can freely use the API methods and putting the right parameters inside them. In this work, I plan to automatically recommend relevant APIs to developers. This API recommendation can be divided into multiple stages. First, we can recommend relevant …
Comon+: A Cooperative Context Monitoring System For Multi-Device Personal Sensing Environments, Youngki Lee, Seungwoo Kang, Chulhong Min, Younghyun Ju, Inseok Hwang, Junehwa Song
Comon+: A Cooperative Context Monitoring System For Multi-Device Personal Sensing Environments, Youngki Lee, Seungwoo Kang, Chulhong Min, Younghyun Ju, Inseok Hwang, Junehwa Song
Research Collection School Of Computing and Information Systems
Continuous mobile sensing applications are emerging. Despite their usefulness, their real-world adoption has been slow. Many users are turned away by the drastic battery drain caused by continuous sensing and processing. In this paper, we propose CoMon+, a novel cooperative context monitoring system, which addresses the energy problem through opportunistic cooperation among nearby users. For effective cooperation, we develop a benefit-aware negotiation method to maximize the energy benefit of context sharing. CoMon+ employs heuristics to detect cooperators who are likely to remain in the vicinity for a long period of time, and the negotiation method automatically devises a cooperation plan …
User Identity Linkage By Latent User Space Modelling, Xin Mu, Feida Zhu, Ee-Peng Lim, Jing Xiao, Jianzong Wang, Zhi-Hua Zhou
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 …