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Research Collection School Of Information Systems

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Full-Text Articles in Physical Sciences and Mathematics

When Human Cognitive Modeling Meets Pins: User-Independent Inter-Keystroke Timing Attacks, Ximing Liu, Yingjiu Li, Robert H. Deng, Bing Chang, Shujun Li Jan 2019

When Human Cognitive Modeling Meets Pins: User-Independent Inter-Keystroke Timing Attacks, Ximing Liu, Yingjiu Li, Robert H. Deng, Bing Chang, Shujun Li

Research Collection School Of Information Systems

This paper proposes the first user-independent inter-keystroke timing attacks on PINs. Our attack method is based on an inter-keystroke timing dictionary built from a human cognitive model whose parameters can be determined by a small amount of training data on any users (not necessarily the target victims). Our attacks can thus be potentially launched on a large scale in real-world settings. We investigate inter-keystroke timing attacks in different online attack settings and evaluate their performance on PINs at different strength levels. Our experimental results show that the proposed attack performs significantly better than random guessing attacks. We further demonstrate that ...


Secure Smart Health With Privacy-Aware Aggregate Authentication And Access Control In Internet Of Things, Yinghui Zhang, Robert H. Deng, Gang Han, Dong Zheng Dec 2018

Secure Smart Health With Privacy-Aware Aggregate Authentication And Access Control In Internet Of Things, Yinghui Zhang, Robert H. Deng, Gang Han, Dong Zheng

Research Collection School Of Information Systems

With the rapid technological advancements in the Internet of Things (IoT), wireless communication and cloud computing, smart health is expected to enable comprehensive and qualified healthcare services. It is important to ensure security and efficiency in smart health. However, existing smart health systems still have challenging issues, such as aggregate authentication, fine-grained access control and privacy protection. In this paper, we address these issues by introducing SSH, a Secure Smart Health system with privacy-aware aggregate authentication and access control in IoT. In SSH, privacy-aware aggregate authentication is enabled by an anonymous certificateless aggregate signature scheme, in which users' identity information ...


Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li Dec 2018

Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li

Research Collection School Of Information Systems

Modern Code Review (MCR) has been widely used by open source and proprietary software projects. Inspecting code changes consumes reviewers much time and effort since they need to comprehend patches, and many reviewers are often assigned to review many code changes. Note that a code change might be eventually abandoned, which causes waste of time and effort. Thus, a tool that predicts early on whether a code change will be merged can help developers prioritize changes to inspect, accomplish more things given tight schedule, and not waste reviewing effort on low quality changes. In this paper, motivated by the above ...


Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality, Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Mark Zhang Dec 2018

Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality, Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Mark Zhang

Research Collection School Of Information Systems

The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of urban air computing. The solutions to these topics can provide extremely useful information to support air pollution control, and consequently generate great societal and technical impacts. Most of the existing work solves the three problems separately by different models. In this paper, we propose a general and effective approach to solve the three problems in one model called the Deep Air Learning (DAL). The main idea of DAL lies in embedding feature selection and semi-supervised learning in different layers of the deep ...


Using Smart Card Data To Model Commuters’ Response Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng Dec 2018

Using Smart Card Data To Model Commuters’ Response Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng

Research Collection School Of Information Systems

The mass rapid transit (MRT) network is playingan increasingly important role in Singapore’s transit network,thanks to its advantages of higher capacity and faster speed.Unfortunately, due to aging infrastructure, increasing demand,and other reasons like adverse weather condition, commuters inSingapore recently have been facing increasing unexpected traindelays (UTDs), which has become a source of frustration forboth commuters and operators. Most, if not all, existing workson delay management do not consider commuters’ behavior. Wededicate this paper to the study of commuters’ behavior duringUTDs. We adopt a data-driven approach to analyzing the sixmonth’ real data collected by automated fare collection ...


Typing-Proof: Usable, Secure And Low-Cost Two-Factor Authentication Based On Keystroke Timings, Ximming Liu, Yingjiu Li, Robert H. Deng Dec 2018

Typing-Proof: Usable, Secure And Low-Cost Two-Factor Authentication Based On Keystroke Timings, Ximming Liu, Yingjiu Li, Robert H. Deng

Research Collection School Of Information Systems

Two-factor authentication (2FA) systems provide another layer of protection to users' accounts beyond password. Traditional hardware token based 2FA and software token based 2FA are not burdenless to users since they require users to read, remember, and type a onetime code in the process, and incur high costs in deployments or operations. Recent 2FA mechanisms such as Sound-Proof, reduce or eliminate users' interactions for the proof of the second factor; however, they are not designed to be used in certain settings (e.g., quiet environments or PCs without built-in microphones), and they are not secure in the presence of certain ...


Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin Dec 2018

Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin

Research Collection School Of Information Systems

In academic institutions, it is normal practice that at the end of each term, students are required to complete a questionnaire that is designed to gather students’ perceptions of the instructor and their learning experience in the course. Students’ feedback includes numerical answers to Likert scale questions and textual comments to open-ended questions. Within the textual comments given by the students are embedded suggestions. A suggestion can be explicit or implicit. Any suggestion provides useful pointers on how the instructor can further enhance the student learning experience. However, it is tedious to manually go through all the qualitative comments and ...


Predicting Episodes Of Non-Conformant Mobility In Indoor Environments, Kasthuri Jayarajah, Archan Misra Dec 2018

Predicting Episodes Of Non-Conformant Mobility In Indoor Environments, Kasthuri Jayarajah, Archan Misra

Research Collection School Of Information Systems

Traditional mobility prediction literature focuses primarily on improved methods to extract latent patterns from individual-specific movement data. When such predictions are incorrect, we ascribe it to 'random' or 'unpredictable' changes in a user's movement behavior. Our hypothesis, however, is that such apparently-random deviations from daily movement patterns can, in fact, of ten be anticipated. In particular, we develop a methodology for predicting Likelihood of Future Non-Conformance (LFNC), based on two central hypotheses: (a) the likelihood of future deviations in movement behavior is positively correlated to the intensity of such trajectory deviations observed in the user's recent past, and ...


Performance Characterization Of Deep Learning Models For Breathing-Based Authentication On Resource-Constrained Devices, Jagmohan Chauhan, Jathusan Rajasegaran, Surang Seneviratne, Archan Misra, Aruan Seneviratne, Youngki Lee Dec 2018

Performance Characterization Of Deep Learning Models For Breathing-Based Authentication On Resource-Constrained Devices, Jagmohan Chauhan, Jathusan Rajasegaran, Surang Seneviratne, Archan Misra, Aruan Seneviratne, Youngki Lee

Research Collection School Of Information Systems

Providing secure access to smart devices such as mobiles, wearables and various other IoT devices is becoming increasinglyimportant, especially as these devices store a range of sensitive personal information. Breathing acoustics-based authentication offers a highly usable and possibly a secondary authentication mechanism for such authorized access, especially as it canbe readily applied to small form-factor devices. Executing sophisticated machine learning pipelines for such authenticationon such devices remains an open problem, given their resource limitations in terms of storage, memory and computational power. To investigate this possibility, we compare the performance of an end-to-end system for both user identification anduser verification ...


Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun Han, Archan Misra, Shih-Fen Cheng Dec 2018

Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun Han, Archan Misra, Shih-Fen Cheng

Research Collection School Of Information Systems

This paper analyzes a human-centric framework, called SmartABLE, for easy retrieval of the sensor values from pervasively deployed smart objects in a campus-like environment. In this framework, smartphones carried by campus occupants act as data mules, opportunistically retrieving data from nearby BLE (Bluetooth Low Energy) equipped smart object sensors and relaying them to a backend repository. We focus specifically on dynamically varying the transmission power of the deployed BLE beacons, so as to extend their operational lifetime without sacrificing the frequency of sensor data retrieval. We propose a memetic algorithm-based power adaptation strategy that can handle deployments of thousands of ...


River: A Real-Time Influence Monitoring System On Social Media Stream, Mo Sha, Yuchen Li, Yanhao Wang, Wentian Guo, Kian-Lee Tan Nov 2018

River: A Real-Time Influence Monitoring System On Social Media Stream, Mo Sha, Yuchen Li, Yanhao Wang, Wentian Guo, Kian-Lee Tan

Research Collection School Of Information Systems

Social networks generate a massive amount of interaction data among users in the form of streams. To facilitate social network users to consume the continuously generated stream and identify preferred viral social contents, we present a real-time monitoring system called River to track a small set of influential social contents from high-speed streams in this demo. River has four novel features which distinguish itself from existing social monitoring systems: (1) River extracts a set of contents which collectively have the most significant influence coverage while reducing the influence overlaps; (2) River is topic-based and monitors the contents which are relevant ...


Latent Dirichlet Allocation For Textual Student Feedback Analysis, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin Nov 2018

Latent Dirichlet Allocation For Textual Student Feedback Analysis, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin

Research Collection School Of Information Systems

Education institutions collect feedback from students upon course completionand analyse it to improve curriculum design, delivery methodology and students' learningexperience. A large part of feedback comes in the form textual comments, which pose achallenge in quantifying and deriving insights. In this paper, we present a novel approach ofthe Latent Dirichlet Allocation (LDA) model to address this difficulty in handling textualstudent feedback. The analysis of quantitative part of student feedback provides generalratings and helps to identify aspects of the teaching that are successful and those that canimprove. The reasons for the failure or success, however, can only be deduced by analysingthe ...


Heterogeneous Embedding Propagation For Large-Scale E-Commerce User Alignment, Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Zhenjie Zhang, Kian-Lee Tan Nov 2018

Heterogeneous Embedding Propagation For Large-Scale E-Commerce User Alignment, Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Zhenjie Zhang, Kian-Lee Tan

Research Collection School Of Information Systems

We study the important problem of user alignment in e-commerce: to predict whether two online user identitiesthat access an e-commerce site from different devices belong toone real-world person. As input, we have a set of user activitylogs from Taobao and some labeled user identity linkages. Useractivity logs can be modeled using a heterogeneous interactiongraph (HIG), and subsequently the user alignment task canbe formulated as a semi-supervised HIG embedding problem.HIG embedding is challenging for two reasons: its heterogeneousnature and the presence of edge features. To address thechallenges, we propose a novel Heterogeneous Embedding Prop-agation (HEP) model. The core idea is ...


Vpsearch: Achieving Verifiability For Privacy-Preserving Multi-Keyword Search Over Encrypted Cloud Data, Zhiguo Wan, Robert H. Deng Nov 2018

Vpsearch: Achieving Verifiability For Privacy-Preserving Multi-Keyword Search Over Encrypted Cloud Data, Zhiguo Wan, Robert H. Deng

Research Collection School Of Information Systems

Although cloud computing offers elastic computation and storage resources, it poses challenges on verifiability of computations and data privacy. In this work we investigate verifiability for privacy-preserving multi-keyword search over outsourced documents. As the cloud server may return incorrect results due to system faults or incentive to reduce computation cost, it is critical to offer verifiability of search results and privacy protection for outsourced data at the same time. To fulfill these requirements, we design aVerifiablePrivacy-preserving keywordSearch scheme, called VPSearch, by integrating an adapted homomorphic MAC technique with a privacy-preserving multi-keyword search scheme. The proposed scheme enables the client to ...


A Tribute To Robert U. Ayres For A Lifetime Of Work In Technological Forecasting And Related Areas, Steven Mark Miller Nov 2018

A Tribute To Robert U. Ayres For A Lifetime Of Work In Technological Forecasting And Related Areas, Steven Mark Miller

Research Collection School Of Information Systems

Bob Ayres was born in the UnitedStates in 1932. For his university studies at the bachelors, masters and PhDlevels, he concentrated in physics and mathematics. When we think of Bob today,we think of his pioneering work across the areas of technological forecasting,industrial metabolism and industrial ecology, and the role of energy andthermodynamics in economic growth. How did a person with a strong fundamentaleducation as a physicist end up as a pioneering thinker and thought leader atthe intersection of energy, environment and economics?


Experiences & Challenges With Server-Side Wifi Indoor Localization Using Existing Infrastructure, Dheryta Jaisinghani, Rajesh Krishna Balan, Vinayak Naik, Archan Misra, Youngki Lee Nov 2018

Experiences & Challenges With Server-Side Wifi Indoor Localization Using Existing Infrastructure, Dheryta Jaisinghani, Rajesh Krishna Balan, Vinayak Naik, Archan Misra, Youngki Lee

Research Collection School Of Information Systems

Real-world deployments of WiFi-based indoor localization in large public venues are few and far between as most state-of-the-art solutions require either client or infrastructure-side changes. Hence, even though high location accuracy is possible with these solutions, they are not practical due to cost and/or client adoption reasons. Majority of the public venues use commercial controller-managed WLAN solutions, that neither allow client changes nor infrastructure changes. In fact, for such venues we have observed highly heterogeneous devices with very low adoption rates for client-side apps. In this paper, we present our experiences in deploying a scalable location system for such ...


Unsupervised User Identity Linkage Via Factoid Embedding, Xie, Ka Wei, Roy Lee, Roy Ka-Wei Lee, Feida Zhu, Ee-Peng Lim Nov 2018

Unsupervised User Identity Linkage Via Factoid Embedding, Xie, Ka Wei, Roy Lee, Roy Ka-Wei Lee, Feida Zhu, Ee-Peng Lim

Research Collection School Of Information Systems

User identity linkage (UIL), the problem of matching user account across multiple online social networks (OSNs), is widely studied and important to many real-world applications. Most existing UIL solutions adopt a supervised or semisupervised approach which generally suffer from scarcity of labeled data. In this paper, we propose Factoid Embedding, a novel framework that adopts an unsupervised approach. It is designed to cope with different profile attributes, content types and network links of different OSNs. The key idea is that each piece of information about a user identity describes the real identity owner, and thus distinguishes the owner from other ...


Linky: Visualizing User Identity Linkage Results For Multiple Online Social Networks (Demo), Lee, Ming Shan Hee, Philips Kokoh Prasetyo, Ee-Peng Lim Nov 2018

Linky: Visualizing User Identity Linkage Results For Multiple Online Social Networks (Demo), Lee, Ming Shan Hee, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Information Systems

User identity linkage across online social networks is an emerging research topic that has attracted attention in recent years. Many user identity linkage methods have been proposed so far and most of them utilize user profile, content and network information to determine if two social media accounts belong to the same person. In most cases, user identity linkage methods are evaluated by performing some prediction tasks with the results presented using some overall accuracy measures. However, the methods are rarely compared at the individual user level where a predicted matched (or linked) pair of user identities from different online social ...


Heterogeneous Embedding Propagation For Large-Scale E-Commerce User Alignment, Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Yuan Fang, Zhenjie Zhang, Kian-Lee Tan, Kevin Chen-Chuan Chang Nov 2018

Heterogeneous Embedding Propagation For Large-Scale E-Commerce User Alignment, Vincent W. Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Yuan Fang, Zhenjie Zhang, Kian-Lee Tan, Kevin Chen-Chuan Chang

Research Collection School Of Information Systems

We study the important problem of user alignment in e-commerce: to predict whether two online user identitiesthat access an e-commerce site from different devices belong toone real-world person. As input, we have a set of user activitylogs from Taobao and some labeled user identity linkages. Useractivity logs can be modeled using a heterogeneous interactiongraph (HIG), and subsequently the user alignment task canbe formulated as a semi-supervised HIG embedding problem.HIG embedding is challenging for two reasons: its heterogeneousnature and the presence of edge features. To address thechallenges, we propose a novel Heterogeneous Embedding Prop-agation (HEP) model. The core idea is ...


Jobsense: A Data-Driven Career Knowledge Exploration Framework And System, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim, Philips Kokoh Prasetyo Nov 2018

Jobsense: A Data-Driven Career Knowledge Exploration Framework And System, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim, Philips Kokoh Prasetyo

Research Collection School Of Information Systems

Today’s job market sees rapid changes due to technology and business model disruptions. To fully tap on one’s potential in career development, one has to acquire job and skill knowledge through working on different jobs. Another approach is to seek consultation with career coaches who are trained to offer career advice in various industry sectors. The above two approaches, nevertheless, suffer from several shortcomings. The on-the-job career development approach is highly inefficient for today’s fast changing job market. The latter career coach assisted approach could help to speed up knowledge acquisition but it relies on expertise of ...


Influence Maximization On Social Graphs: A Survey, Yuchen Li, Ju Fan, Yanhao Wang, Kian-Lee Tan Oct 2018

Influence Maximization On Social Graphs: A Survey, Yuchen Li, Ju Fan, Yanhao Wang, Kian-Lee Tan

Research Collection School Of Information Systems

Influence Maximization (IM), which selects a set of k users (called seed set) from a social network to maximize the expected number of influenced users (called influence spread), is a key algorithmic problem in social influence analysis. Due to its immense application potential and enormous technical challenges, IM has been extensively studied in the past decade. In this paper, we survey and synthesize a wide spectrum of existing studies on IM from an algorithmic perspective, with a special focus on the following key aspects (1) a review of well-accepted diffusion models that capture information diffusion process and build the foundation ...


Teaching Adult Learners On Software Architecture Design Skills, Eng Lieh Ouh, Yunghans Irawan Oct 2018

Teaching Adult Learners On Software Architecture Design Skills, Eng Lieh Ouh, Yunghans Irawan

Research Collection School Of Information Systems

Software architectures present high-level views ofsystems, enabling developers to abstract away the unnecessarydetails and focus on the overall big picture. Designing a softwarearchitecture is an essential skill in software engineering and adultlearners are seeking this skill to further progress in their career.With the technology revolution and advancements in this rapidlychanging world, the proportion of adult learners attendingcourses for continuing education are increasing. Their learningobjectives are no longer to obtain good grades but the practicalskills to enable them to perform better in their work and advancein their career. Teaching software architecture to upskill theseadult learners requires contending with the problem ...


Unearthing The X-Streams:Visualizing Water Contamination, Akangsha Bandalkul, Angad Srivastava, Kishan Bharadwaj Shridhar, Jason Guan Jie Ong, Yanrong Zhang Oct 2018

Unearthing The X-Streams:Visualizing Water Contamination, Akangsha Bandalkul, Angad Srivastava, Kishan Bharadwaj Shridhar, Jason Guan Jie Ong, Yanrong Zhang

Research Collection School Of Information Systems

The datasets released for VAST 2018 Mini Challenge 2 pertain to sensor readings capturing chemical concentrations and physical properties from water bodies in the Boonsong Lekagul wildlife preserve. This challenge is in continuation to the VAST 2017 Challenge, where the company Kasios was identified as the culprit in dumping the chemical - Methylosmoline. In the absence of actual chemical measurements in the soil, challenge participants need to visualize chemical contamination based on the proximal water bodies to identify trends of interest. A horizon plot developed helps to narrow down the complete list of 106 chemicals provided to only 7, from where ...


Simknn: A Scalable Method For In-Memory Knn Search Over Moving Objects In Road Networks, Bin Cao, Chenyu Hou, Suifei Li, Jing Fan, Jianwei Yin, Baihua Zheng, Jie Bao Oct 2018

Simknn: A Scalable Method For In-Memory Knn Search Over Moving Objects In Road Networks, Bin Cao, Chenyu Hou, Suifei Li, Jing Fan, Jianwei Yin, Baihua Zheng, Jie Bao

Research Collection School Of Information Systems

Nowadays, many location-based applications require the ability of querying k-nearest neighbors over a very large scale of5 moving objects in road networks, e.g., taxi-calling and ride-sharing services. Traditional grid index with equal-sized cells can not adapt6 to the skewed distribution of moving objects in real scenarios. Thus, to obtain the fast querying response time, the grid needs to be split7 into more smaller cells which introduces the side-effect of higher memory cost, i.e., maintaining such a large volume of cells requires a8 much larger memory space at the server side. In this paper, we present SIMkNN, a scalable ...


I4s: Capturing Shopper’S In-Store Interactions, Sougata Sen, Archan Misra, Vigneshwaran Subbaraju, Karan Grover, Meeralakshmi Radhakrishnan, Rajesh K. Balan, Youngki Lee Oct 2018

I4s: Capturing Shopper’S In-Store Interactions, Sougata Sen, Archan Misra, Vigneshwaran Subbaraju, Karan Grover, Meeralakshmi Radhakrishnan, Rajesh K. Balan, Youngki Lee

Research Collection School Of Information Systems

In this paper, we present I4S, a system that identifies item interactions of customers in a retail store through sensor data fusion from smartwatches, smartphones and distributed BLE beacons. To identify these interactions, I4S builds a gesture-triggered pipeline that (a) detects the occurrence of “item picks”, and (b) performs fine-grained localization of such pickup gestures. By analyzing data collected from 31 shoppers visiting a midsized stationary store, we show that we can identify person-independent picking gestures with a precision of over 88%, and identify the rack from where the pick occurred with 91%+ precision (for popular racks).


Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan Oct 2018

Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan

Research Collection School Of Information Systems

This paper provides a fog-based approach to solving the traffic light optimization problem which utilizes the Adaptive Traffic Signal Control (ATSC) model. ATSC systems demand the ability to strictly reflect real-time traffic state. The proposed fog computing framework, namely FogFly, aligns with this requirement by its natures in location-awareness, low latency and affordability to the changes in traffic conditions. As traffic data is updated timely and processed at fog nodes deployed close to data sources (i.e., vehicles at intersections) traffic light cycles can be optimized efficiently while virtualized resources available at network edges are efficiently utilized. Evaluation results show ...


Exploring Experiential Learning Model And Risk Management Process For An Undergraduate Software Architecture Course, Eng Lieh Ouh, Yunghans Irawan Oct 2018

Exploring Experiential Learning Model And Risk Management Process For An Undergraduate Software Architecture Course, Eng Lieh Ouh, Yunghans Irawan

Research Collection School Of Information Systems

This paper shares our insights on exploring theexperiential learning model and risk management process todesign an undergraduate software architecture course. The keychallenge for undergraduate students to appreciate softwarearchitecture design is usually their limited experience in thesoftware industry. In software architecture, the high-level designprinciples are heuristics lacking the absoluteness of firstprinciples which for inexperienced undergraduate students, thisis a frustrating divergence from what they used to value. From aneducator's perspective, teaching software architecture requirescontending with the problem of how to express this level ofabstraction practically and also make the learning realistic. Inthis paper, we propose a model adapting the concepts ofexperiential ...


Inferring Trip Occupancies In The Rise Of Ride-Hailing Services, Chiang, Ee-Peng Lim, Wang-Chien Lee, Tuan-Anh Hoang Oct 2018

Inferring Trip Occupancies In The Rise Of Ride-Hailing Services, Chiang, Ee-Peng Lim, Wang-Chien Lee, Tuan-Anh Hoang

Research Collection School Of Information Systems

The knowledge of all occupied and unoccupied trips made by self-employed drivers are essential for optimized vehicle dispatch by ride-hailing services (e.g., Didi Dache, Uber, Lyft, Grab, etc.). However, the occupancy status of vehicles is not always known to the service operators due to adoption of multiple ride-hailing apps. In this paper, we propose a novel framework, Learning to INfer Trips (LINT), to infer occupancy of car trips by exploring characteristics of observed occupied trips. Two main research steps, stop point classification and structural segmentation, are included in LINT. In the stop point classification step, we represent a vehicle ...


Multiperspective Graph-Theoretic Similarity Measure, Duy Dung Le, Hady Wirawan Lauw Oct 2018

Multiperspective Graph-Theoretic Similarity Measure, Duy Dung Le, Hady Wirawan Lauw

Research Collection School Of Information Systems

Determining the similarity between two objects is pertinent to many applications. When the basis for similarity is a set of object-to-object relationships, it is natural to rely on graph-theoretic measures. One seminal technique for measuring the structural-context similarity between a pair of graph vertices is SimRank, whose underlying intuition is that two objects are similar if they are connected by similar objects. However, by design, SimRank as well as its variants capture only a single view or perspective of similarity. Meanwhile, in many real-world scenarios, there emerge multiple perspectives of similarity, i.e., two objects may be similar from one ...


Traffic-Cascade: Mining And Visualizing Lifecycles Of Traffic Congestion Events Using Public Bus Trajectories, Kwee, Philips Kokoh Prasetyo, Meng-Fen Chiang, Ee-Peng Lim, P. Prasetyo, M. Chiang, E. Lim Oct 2018

Traffic-Cascade: Mining And Visualizing Lifecycles Of Traffic Congestion Events Using Public Bus Trajectories, Kwee, Philips Kokoh Prasetyo, Meng-Fen Chiang, Ee-Peng Lim, P. Prasetyo, M. Chiang, E. Lim

Research Collection School Of Information Systems

As road transportation supports both economic and social activities in developed cities, it is important to maintain smooth traffic on all highways and local roads. Whenever possible, traffic congestions should be detected early and resolved quickly. While existing traffic monitoring dashboard systems have been put in place in many cities, these systems require high-cost vehicle speed monitoring instruments and detect traffic congestion as independent events. There is a lack of low-cost dashboards to inspect and analyze the lifecycle of traffic congestion which is critical in assessing the overall impact of congestion, determining the possible the source(s) of congestion and ...