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Articles 2791 - 2820 of 4266
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Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan
Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan
Research Collection School Of Computing and Information Systems
Profitable tour problem (PTP) belongs to the class of vehicle routing problem (VRP) with profits seeking to maximize the difference between the total collected profit and the total cost incurred. Traditionally, PTP involves single vehicle. In this paper, we consider PTP with multiple vehicles. Unlike the classical VRP that seeks to serve all customers, PTP involves the strategic-level customer selection so as to maximize the total collected profit and the operational-level route optimization to minimize the total cost incurred. Therefore, PTP is essentially the knapsack problem at the strategic level with VRP at the operational level. That means the evolutionary …
Oscar: Online Selection Of Algorithm Portfolios With Case Study On Memetic Algorithms, Mustafa Misir, Stephanus Daniel Handoko, Hoong Chuin Lau
Oscar: Online Selection Of Algorithm Portfolios With Case Study On Memetic Algorithms, Mustafa Misir, Stephanus Daniel Handoko, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
This paper introduces an automated approach called OSCAR that combines algorithm portfolios and online algorithm selection. The goal of algorithm portfolios is to construct a subset of algorithms with diverse problem solving capabilities. The portfolio is then used to select algorithms from for solving a particular (set of) instance(s). Traditionally, algorithm selection is usually performed in an offline manner and requires the need of domain knowledge about the target problem; while online algorithm selection techniques tend not to pay much attention to a careful construction of algorithm portfolios. By combining algorithm portfolios and online selection, our hope is to design …
Characterizing Silent Users In Social Media Communities, Wei Gong, Ee-Peng Lim, Feida Zhu
Characterizing Silent Users In Social Media Communities, Wei Gong, Ee-Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
Silent users often constitute a significant proportion of an online user-generated content system. In the context of social media such as Twitter, users can opt to be silent all or most of the time. They are often called the invisible participants or lurkers. As lurkers contribute little to the online content, existing analysis often overlooks their presence and voices. However, we argue that understanding lurkers is important in many applications such as recommender systems, targeted advertising, and social sensing. This research therefore seeks to characterize lurkers in social media and propose methods to profile them. We examine 18 weeks of …
Matchmaking Game Players On Public Transport, Nairan Zhang, Youngki Lee, Rajesh Krishna Balan
Matchmaking Game Players On Public Transport, Nairan Zhang, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
This paper extends our recent work, called GameOn, which presented a system for allowing public transport commuters to engage in multiplayer games with fellow commuters traveling on the same bus or train. An important challenge for GameOn is to group players with reliable connections into the same game. In this case, the meaning of reliability has two dimensions. First, the network connectivity (TCP, UDP etc.) should be robust. Second, the players should be collocated with each other for a sufficiently long duration so that a game session will not be terminated by players leaving the public transport modality such as …
Towards Practical Graph-Based Verification For An Object-Oriented Concurrency Model, Alexander Heußner, Christopher M. Poskitt, Claudio Corrodi, Benjamin Morandi
Towards Practical Graph-Based Verification For An Object-Oriented Concurrency Model, Alexander Heußner, Christopher M. Poskitt, Claudio Corrodi, Benjamin Morandi
Research Collection School Of Computing and Information Systems
To harness the power of multi-core and distributed platforms, and to make the development of concurrent software more accessible to software engineers, different object-oriented concurrency models such as SCOOP have been proposed. Despite the practical importance of analysing SCOOP programs, there are currently no general verification approaches that operate directly on program code without additional annotations. One reason for this is the multitude of partially conflicting semantic formalisations for SCOOP (either in theory or by-implementation). Here, we propose a simple graph transformation system (GTS) based run-time semantics for SCOOP that grasps the most common features of all known semantics of …
Tlv: Abstraction Through Testing, Learning, And Validation, Jun Sun, Hao Xiao, Yang Liu, Shang-Wei Lin, Shengchao Qin
Tlv: Abstraction Through Testing, Learning, And Validation, Jun Sun, Hao Xiao, Yang Liu, Shang-Wei Lin, Shengchao Qin
Research Collection School Of Computing and Information Systems
A (Java) class provides a service to its clients (i.e., programs which use the class). The service must satisfy certain specifications. Different specifications might be expected at different levels of abstraction depending on the client's objective. In order to effectively contrast the class against its specifications, whether manually or automatically, one essential step is to automatically construct an abstraction of the given class at a proper level of abstraction. The abstraction should be correct (i.e., over-approximating) and accurate (i.e., with few spurious traces). We present an automatic approach, which combines testing, learning, and validation, to constructing an abstraction. Our approach …
Physio@Home: Exploring Visual Guidance And Feedback Techniques For Physiotherapy Exercises, Richard Tang, Xing-Dong Yang, Scott Bateman, Joaquim Jorge, Anthony Tang
Physio@Home: Exploring Visual Guidance And Feedback Techniques For Physiotherapy Exercises, Richard Tang, Xing-Dong Yang, Scott Bateman, Joaquim Jorge, Anthony Tang
Research Collection School Of Computing and Information Systems
Physiotherapy patients exercising at home alone are at risk of re-injury since they do not have corrective guidance from a therapist. To explore solutions to this problem, we designed Physio@Home, a prototype that guides people through pre-recorded physiotherapy exercises using realtime visual guides and multi-camera views. Our design addresses several aspects of corrective guidance, including: plane and range of movement, joint positions and angles, and extent of movement. We evaluated our design, comparing how closely people could follow exercise movements under various feedback conditions. Participants were most accurate when using our visual guide and multi-views. We provide suggestions for exercise …
Software Watermarking Using Return-Oriented Programming, Haoyu Ma, Kangjie Lu, Xinjie Ma, Haining Zhang, Chunfu Jia, Debin Gao
Software Watermarking Using Return-Oriented Programming, Haoyu Ma, Kangjie Lu, Xinjie Ma, Haining Zhang, Chunfu Jia, Debin Gao
Research Collection School Of Computing and Information Systems
We propose a novel dynamic software watermarking design based on Return-Oriented Programming (ROP). Our design formats watermarking code into well-crafted data arrangements that look like normal data but could be triggered to execute. Once triggered, the pre-constructed ROP execution will recover the hidden watermark message. The proposed ROP-based watermarking technique is more stealthy and resilient over existing techniques since the watermarking code is allocated dynamically into data region and therefore out of reach of attacks based on code analysis. Evaluations show that our design not only achieves satisfying stealth and resilience, but also causes significantly lower overhead to the watermarked …
Queuevadis: Queuing Analytics Using Smartphones, Tadashi Okoshii, Lu Yu, Chetna Vig, Youngki Lee, Rajesh Krishna Balan, Archan Misra
Queuevadis: Queuing Analytics Using Smartphones, Tadashi Okoshii, Lu Yu, Chetna Vig, Youngki Lee, Rajesh Krishna Balan, Archan Misra
Research Collection School Of Computing and Information Systems
We present QueueVadis, a system that addresses the problem of estimating, in real-time, the properties of queues at commonplace urban locations, such as coffee shops, taxi stands and movie theaters. Abjuring the use of any queuing-specific infrastructure sensors, QueueVadis uses participatory mobile sensing to detect both (i) the individual-level queuing episodes for any arbitrarily-shaped queue (by a characteristic locomotive signature of short bursts of "shuffling forward" between periods of "standing") and (ii) the aggregate-level queue properties (such as expected wait or service times) via appropriate statistical aggregation of multi-person data. Moreover, for venues where multiple queues are too close …
Exploring Cyberbullying And Other Toxic Behavior In Team Competition Online Games, Haewoon Kwak, Jeremy Blackburn, Seungyeop. Han
Exploring Cyberbullying And Other Toxic Behavior In Team Competition Online Games, Haewoon Kwak, Jeremy Blackburn, Seungyeop. Han
Research Collection School Of Computing and Information Systems
In this work we explore cyberbullying and other toxic behavior in team competition online games. Using a dataset of over 10 million player reports on 1.46 million toxic players along with corresponding crowdsourced decisions, we test several hypotheses drawn from theories explaining toxic behavior. Besides providing large-scale, empirical based understanding of toxic behavior, our work can be used as a basis for building systems to detect, prevent, and counter-act toxic behavior.
Using Support Vector Machine Ensembles For Target Audience Classification On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Using Support Vector Machine Ensembles For Target Audience Classification On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Research Collection School Of Computing and Information Systems
The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results …
Cofaçade: A Customizable Assistive Approach For Elders And Their Helpers, Jason Chen Zhao, Richard Christopher Davis, Pin Sym Foong, Shengdong Zhao
Cofaçade: A Customizable Assistive Approach For Elders And Their Helpers, Jason Chen Zhao, Richard Christopher Davis, Pin Sym Foong, Shengdong Zhao
Research Collection School Of Computing and Information Systems
We present CoFaçade, a novel approach to helping elders reach their goals with IT products by working collaboratively with helpers. In this approach, the elder uses an interface with a small number of triggers, where each trigger is a single button (or card) that can execute a procedure. The helper uses a customization interface to link triggers to procedures that accomplish frequently-recurring high-level goals with IT products. Customization can be done either locally or remotely. We conducted an experiment to compare the CoFaçade approach with a baseline approach where helpers taught elders to perform IT tasks. Our results showed that …
Best Upgrade Plans For Single And Multiple Source-Destination Pairs, Yimin Lin, Kyriakos Mouratidis
Best Upgrade Plans For Single And Multiple Source-Destination Pairs, Yimin Lin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
In this paper, we study Resource Constrained Best Upgrade Plan (BUP) computation in road network databases. Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. In the single-pair version of BUP, the input includes a source and a destination in G, and a budget B (resource constraint). The goal is to identify which upgradable edges should be upgraded so that the shortest path distance between source and …
Evaluating Defect Prediction Using A Massive Set Of Metrics, Xiao Xuan, David Lo, Xin Xia, Yuan Tian
Evaluating Defect Prediction Using A Massive Set Of Metrics, Xiao Xuan, David Lo, Xin Xia, Yuan Tian
Research Collection School Of Computing and Information Systems
To evaluate the performance of a within-project defect prediction approach, people normally use precision, recall, and F-measure scores. However, in machine learning literature, there are a large number of evaluation metrics to evaluate the performance of an algorithm, (e.g., Matthews Correlation Coefficient, G-means, etc.), and these metrics evaluate an approach from different aspects. In this paper, we investigate the performance of within-project defect prediction approaches on a large number of evaluation metrics. We choose 6 state-of-the-art approaches including naive Bayes, decision tree, logistic regression, kNN, random forest and Bayesian network which are widely used in defect prediction literature. And we …
Mining Business Competitiveness From User Visitation Data, Doan Thanh Nam, Freddy Chong Tat Chua, Ee-Peng Lim
Mining Business Competitiveness From User Visitation Data, Doan Thanh Nam, Freddy Chong Tat Chua, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Ranking businesses by competitiveness is useful in many applications including business (e.g., restaurant) recommendation, and estimation of intrinsic value of businesses for mergers and acquisitions. Our literature reveals that previous methods of business ranking have ignored the competing relationship among businesses within their geographical areas. To account for competition, we propose the use of PageRank model and its variant to derive the Competitive Rankof businesses. We use the check-ins of users from Foursquare, a location-based social network, to model the winners of competitions among stores. The results of our experiments show that Competitive Rank works well when evaluated against ground …
Effect Of Machine Translation In Interlingual Conversation: Lessons From A Formative Study, Kotaro Hara, Shamsi T. Iqbal
Effect Of Machine Translation In Interlingual Conversation: Lessons From A Formative Study, Kotaro Hara, Shamsi T. Iqbal
Research Collection School Of Computing and Information Systems
Language barrier is the primary challenge for effectivecross-lingual conversations. Spoken language translation(SLT) is perceived as a cost-effective alternative to lessaffordable human interpreters, but little research has beendone on how people interact with such technology. Using aprototype translator application, we performed a formativeevaluation to elicit how people interact with the technologyand adapt their conversation style. We conducted two setsof studies with a total of 23 pairs (46 participants).Participants worked on storytelling tasks to simulate naturalconversations with 3 different interface settings. Ourfindings show that collocutors naturally adapt their style ofspeech production and comprehension to compensate forinadequacies in SLT. We conclude the paper …
Mobility Increases Localizability: A Survey On Wireless Indoor Localization Using Inertial Sensors, Zheng Yang, Chenshu Wu, Zimu Zhou, Xinglin Zhang, Xu Wang, Yunhao Liy
Mobility Increases Localizability: A Survey On Wireless Indoor Localization Using Inertial Sensors, Zheng Yang, Chenshu Wu, Zimu Zhou, Xinglin Zhang, Xu Wang, Yunhao Liy
Research Collection School Of Computing and Information Systems
Wireless indoor positioning has been extensively studied for the past two decades and continuously attracted growing research efforts in mobile computing context. As the integration of multiple inertial sensors (e.g., accelerometer, gyroscope, and magnetometer) to nowadays smartphones in recent years, human-centric mobility sensing is emerging and coming into vogue. Mobility information, as a new dimension in addition to wireless signals, can benefit localization in a number of ways, since location and mobility are by nature related in physical world. In this article, we survey this new trend of mobility enhancing smartphone-based indoor localization. Specifically, we first study how to measure …
Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Research Collection School Of Computing and Information Systems
Given the proliferation of review content, and the fact that reviews are highly diverse and often unnecessarily verbose, users frequently face the problem of selecting the appropriate reviews to consume. Micro-reviews are emerging as a new type of online review content in the social media. Micro-reviews are posted by users of check-in services such as Foursquare. They are concise (up to 200 characters long) and highly focused, in contrast to the comprehensive and verbose reviews. In this paper, we propose a novel mining problem, which brings together these two disparate sources of review content. Specifically, we use coverage of micro-reviews …
Chalk And Cheese In Twitter: Discriminating Personal And Organization Accounts, Richard Jayadi Oentaryo, Jia-Wei Low, Ee Peng Lim
Chalk And Cheese In Twitter: Discriminating Personal And Organization Accounts, Richard Jayadi Oentaryo, Jia-Wei Low, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Social media have been popular not only for individuals to share contents, but also for organizations to engage users and spread information. Given the trait differences between personal and organization accounts, the ability to distinguish between the two account types is important for developing better search/recommendation engines, marketing strategies, and information dissemination platforms. However, such task is non-trivial and has not been well studied thus far. In this paper, we present a new generic framework for classifying personal and organization accounts, based upon which comprehensive and systematic investigation on a rich variety of content, social, and temporal features can be …
Understanding The Test Automation Culture Of App Developers, Pavneet Singh Kochhar, Ferdian. Thung, Nachiappan Nagappan, Thomas Zimmermann, David Lo
Understanding The Test Automation Culture Of App Developers, Pavneet Singh Kochhar, Ferdian. Thung, Nachiappan Nagappan, Thomas Zimmermann, David Lo
Research Collection School Of Computing and Information Systems
Smartphone applications (apps) have gained popularity recently. Millions of smartphone applications (apps) are available on different app stores which gives users plethora of options to choose from, however, it also raises concern if these apps are adequately tested before they are released for public use. In this study, we want to understand the test automation culture prevalent among app developers. Specifically, we want to examine the current state of testing of apps, the tools that are commonly used by app developers, and the problems faced by them. To get an insight on the test automation culture, we conduct two different …
Markov Decision Processes With Applications In Wireless Sensor Networks: A Survey, Abu Mohammad Alsheikh, Dinh Thai Hoang, Dusit Niyato, Hwee-Pink Tan
Markov Decision Processes With Applications In Wireless Sensor Networks: A Survey, Abu Mohammad Alsheikh, Dinh Thai Hoang, Dusit Niyato, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are used to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process …
Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan
Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
While mobile and wearable sensing can capture unique insights into fine-grained activities (such as gestures and limb-based actions) at an individual level, their energy overheads are still prohibitive enough to prevent them from being executed continuously. In this paper, we explore practical alternatives to addressing this challenge-by exploring how cheap infrastructure sensors or information sources (e.g., BLE beacons) can be harnessed with such mobile/wearable sensors to provide an effective solution that reduces energy consumption without sacrificing accuracy. The key idea is that many fine-grained activities that we desire to capture are specific to certain location, movement or background context: infrastructure …
Beyond Support And Confidence: Exploring Interestingness Measures For Rule-Based Specification Mining, Bui Tien Duy Le, David Lo
Beyond Support And Confidence: Exploring Interestingness Measures For Rule-Based Specification Mining, Bui Tien Duy Le, David Lo
Research Collection School Of Computing and Information Systems
Numerous rule-based specification mining approaches have been proposed in the literature. Many of these approaches analyze a set of execution traces to discover interesting usage rules, e.g., whenever lock() is invoked, eventually unlock() is invoked. These techniques often generate and enumerate a set of candidate rules and compute some interestingness scores. Rules whose interestingness scores are above a certain threshold would then be output. In past studies, two measures, namely support and confidence, which are well-known measures, are often used to compute these scores. However, aside from these two, many other interestingness measures have been proposed. It is thus unclear …
The Case For Smartwatch-Based Diet Monitoring, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
The Case For Smartwatch-Based Diet Monitoring, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
We explore the use of gesture recognition on a wrist-worn smartwatch as an enabler of an automated eating activity (and diet monitoring) system. We show, using small-scale user studies, how it is possible to use the accelerometer and gyroscope data from a smartwatch to accurately separate eating episodes from similar non-eating activities, and to additionally identify the mode of eating (i.e., using a spoon, bare hands or chopsticks). Additionally, we investigate the likelihood of automatically triggering the smartwatch's camera to capture clear images of the food being consumed, for possible offline analysis to identify what (and how much) the user …
Improving Public Transit Accessibility For Blind Riders By Crowdsourcing Bus Stop Landmark Locations With Google Street View: An Extended Analysis, Kotaro Hara, Shiri Azenkot, Megan Campbell, Cynthia L. Bennett, Vicki Le, Sean Pannella, Robert Moore, Kelly Minckler, Rochelle H. Ng, Jon E. Froehlich
Improving Public Transit Accessibility For Blind Riders By Crowdsourcing Bus Stop Landmark Locations With Google Street View: An Extended Analysis, Kotaro Hara, Shiri Azenkot, Megan Campbell, Cynthia L. Bennett, Vicki Le, Sean Pannella, Robert Moore, Kelly Minckler, Rochelle H. Ng, Jon E. Froehlich
Research Collection School Of Computing and Information Systems
Low-vision and blind bus riders often rely on known physical landmarks to help locate and verify bus stoplocations (e.g., by searching for an expected shelter, bench, or newspaper bin). However, there are currentlyfew, if any, methods to determine this information a priori via computational tools or services. In thisarticle, we introduce and evaluate a new scalable method for collecting bus stop location and landmarkdescriptions by combining online crowdsourcing and Google Street View (GSV). We conduct and report onthree studies: (i) a formative interview study of 18 people with visual impairments to inform the designof our crowdsourcing tool, (ii) a comparative …
Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis
Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis
Research Collection School Of Computing and Information Systems
The diffusion of social networks introduces new challenges and opportunities for advanced services, especially so with their ongoing addition of location-based features. We show how applications like company and friend recommendation could significantly benefit from incorporating social and spatial proximity, and study a query type that captures these two-fold semantics. We develop highly scalable algorithms for its processing, and enhance them with elaborate optimizations. Finally, we use real social network data to empirically verify the efficiency and efficacy of our solutions.
Analysis And Improvement On A Biometric-Based Remote User Authentication Scheme Using Smart Cards, Fengtong Wen, Willy Susilo, Guomin Yang
Analysis And Improvement On A Biometric-Based Remote User Authentication Scheme Using Smart Cards, Fengtong Wen, Willy Susilo, Guomin Yang
Research Collection School Of Computing and Information Systems
In a recent paper (BioMed Research International, 2013/491289), Khan et al. proposed an improved biometrics-based remote user authentication scheme with user anonymity. The scheme is believed to be secure against password guessing attack, user impersonation attack, server masquerading attack, and provide user anonymity, even if the secret information stored in the smart card is compromised. In this paper, we analyze the security of Khan et al.’s scheme, and demonstrate that their scheme doesn’t provide user anonymity. This also renders that their scheme is insecure against other attacks, such as off-line password guessing attack, user impersonation attacks. Subsequently, we propose a …
Biometric Authentication On Iphone And Android: Usability, Perceptions, And Influences On Adoption, Rasekhar Bhagavatula, Blase Ur, Kevin Iacovino, Su Mon Kywe, Lorrie Faith Cranor, Marios Savvides
Biometric Authentication On Iphone And Android: Usability, Perceptions, And Influences On Adoption, Rasekhar Bhagavatula, Blase Ur, Kevin Iacovino, Su Mon Kywe, Lorrie Faith Cranor, Marios Savvides
Research Collection School Of Computing and Information Systems
While biometrics have long been promoted as the future of authentication, the recent introduction of Android face unlock and iPhone fingerprint unlock are among the first large-scale deployments of biometrics for consumers. In a 10-participant, within-subjects lab study and a 198-participant online survey, we investigated the usability of these schemes, along with users ’ experiences, attitudes, and adoption decisions. Participants in our lab study found both face unlock and fingerprint unlock easy to use in typical scenarios. The notable exception was that face unlock was completely unusable in a dark room. Most participants preferred fingerprint unlock over face unlock or …
Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua
Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
The vocabulary gap between health seekers and providers has hindered the cross-system operability and the interuser reusability. To bridge this gap, this paper presents a novel scheme to code the medical records by jointly utilizing local mining and global learning approaches, which are tightly linked and mutually reinforced. Local mining attempts to code the individual medical record by independently extracting the medical concepts from the medical record itself and then mapping them to authenticated terminologies. A corpus-aware terminology vocabulary is naturally constructed as a byproduct, which is used as the terminology space for global learning. Local mining approach, however, may …
Will This Be Quick? A Case Study Of Bug Resolution Times Across Industrial Projects, Subhajit Datta, Prasanth Lade
Will This Be Quick? A Case Study Of Bug Resolution Times Across Industrial Projects, Subhajit Datta, Prasanth Lade
Research Collection School Of Computing and Information Systems
Resolution of problem tickets is a source of significant revenue in the worldwide software services industry. Due to the high volume of problem tickets in any large scale customer engagement, automated techniques are necessary to segregate related incoming tickets into groups. Existing techniques focus on this classification problem. In this paper, we present a case study built around the position that predicting the category of resolution times within a class of tickets and also the actual resolution times, is strongly beneficial to ticket resolution. We present an approach based on topic analysis to predict the category of resolution times of …