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Articles 5401 - 5430 of 8597
Full-Text Articles in Entire DC Network
Should Fixing These Failures Be Delegated To Automated Program Repair?, Le Dinh Xuan Bach, Le Bui Tien Duy, David Lo
Should Fixing These Failures Be Delegated To Automated Program Repair?, Le Dinh Xuan Bach, Le Bui Tien Duy, David Lo
Research Collection School Of Computing and Information Systems
Program repair constitutes one of the major components of software maintenance that usually incurs a significant cost in software production. Automated program repair is supposed to help in reducing the software maintenance cost by automatically fixing software defects. Despite the recent advances in automated software repair, it is still very costly to wait for repair tools to produce valid repairs of defects. This paper addresses the following question: "Will an automated program repair technique find a repair for a defect within a reasonable time?". To answer this question, we build an oracle that can predict whether fixing a failure should …
Not All Trips Are Equal: Analyzing Foursquare Check-Ins Of Trips And City Visitors, Wen Haw Chong, Bingtian Dai, Ee Peng Lim
Not All Trips Are Equal: Analyzing Foursquare Check-Ins Of Trips And City Visitors, Wen Haw Chong, Bingtian Dai, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Location-Based Social Networks (LBSN) such as Foursquare allow users to indicate venue visits via check-ins. This results in much fine grained context-rich data, useful for studying user mobility. In this work, we use check-ins to characterize trips and visitors to two cities, where visitors are defined as having their home cities elsewhere. First, we divide trips into two duration types: long and short. We then show that trip types differ in check-in distributions over venue categories, time slots, as well as check-in intensity. Based on the trip types, we then divide visitors into long-term and short-term visitors. We compare visitor …
Real-Time Detection Of Seat Occupancy And Hogging, Huy Hoang Nguyen, Nakul Gulati, Youngki Lee, Rajesh Krishna Balan
Real-Time Detection Of Seat Occupancy And Hogging, Huy Hoang Nguyen, Nakul Gulati, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we propose a cheap and effective solution to detect if specific seats at a shared public table are occupied -- either by humans or by objects (i.e., the seats are being "hogged"). The hogging of seats, in particular, is a big problem for our campus library and required a large amount of manpower to correct (to find and clear hogged seats). We propose using two different cheap sensors, a capacitance sensor and an infrared (IR) sensor, to solve this problem. In the rest of this paper, we show how using these sensors can accurately determine if a …
Modelling Cascades Over Time In Microblogs, Xie Wei, Feida Zhu, Siyuan Liu, Ke Wang
Modelling Cascades Over Time In Microblogs, Xie Wei, Feida Zhu, Siyuan Liu, Ke Wang
Research Collection School Of Computing and Information Systems
One of the most important features of microblogging services such as Twitter is how easy it is to re-share a piece of information across the network through various user connections, forming what we call a "cascade". Business applications such as viral marketing have driven a tremendous amount of research effort predicting whether a certain cascade will go viral. Yet the rarity of viral cascades in real data poses a challenge to all existing prediction methods. One solution is to simulate cascades that well fit the real viral ones, which requires our ability to tell how a certain cascade grows over …
Analysis Of Aspects And Star Ratings In Consumer Reviews, Maruthi Prithivirajan, Vivian Lai, Kyong Jin Shim
Analysis Of Aspects And Star Ratings In Consumer Reviews, Maruthi Prithivirajan, Vivian Lai, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
This paper presents an analysis of star ratings in consumer reviews in Yelp, an online social platform for sharing consumer reviews about local businesses. In particular, we analyze consumer reviews about food businesses. We analyze how well or poorly the star ratings (on a scale of one star to five stars) associated with these reviews tally with the sentiment derived from the textual portion of the consumer review.
Security And Privacy Of Electronic Health Information Systems: Editorial, Elisa Bertino, Robert H. Deng, Xinyi Huang, Jianying Zhou
Security And Privacy Of Electronic Health Information Systems: Editorial, Elisa Bertino, Robert H. Deng, Xinyi Huang, Jianying Zhou
Research Collection School Of Computing and Information Systems
Digital technologies have dramatically transformed our daily lives by bringing countless conveniences and benefits. As an evolving concept, electronic health information has become the focus of attention in both academia and industry. By leveraging modern digital technologies like the internet and the cloud, electronic health information systems will be a key enabling technology in improving the quality and convenience of patient care, encouraging patient participation in their care, reducing medical errors, improving practice efficiencies, and saving time and cost. The complexity of electronic health information systems, however, raises several new security and privacy issues. It is thus critical to investigate …
Interpolation Guided Compositional Verification, Shang-Wei Lin, Jun Sun, Truong Khanh Nguyen, Yang Liu, Jin Song Dong
Interpolation Guided Compositional Verification, Shang-Wei Lin, Jun Sun, Truong Khanh Nguyen, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Model checking suffers from the state space explosion problem. Compositional verification techniques such as assume-guarantee reasoning (AGR) have been proposed to alleviate the problem. However, there are at least three challenges in applying AGR. Firstly, given a system M1 M2, how do we automatically construct and refine (in the presence of spurious counterexamples) an assumption A2, which must be an abstraction of M2? Previous approaches suggest to incrementally learn and modify the assumption through multiple invocations of a model checker, which could be often time consuming. Secondly, how do we keep the state space small when checking M1 A2 |= …
Automating The Performance Deviation Analysis For Multiple System Releases: An Evolutionary Study, Felipe Pinto, Uirá Kulesza, Christoph Treude
Automating The Performance Deviation Analysis For Multiple System Releases: An Evolutionary Study, Felipe Pinto, Uirá Kulesza, Christoph Treude
Research Collection School Of Computing and Information Systems
This paper presents a scenario-based approach for the evaluation of the quality attribute of performance, measured in terms of execution time (response time). The approach is implemented by a framework that uses dynamic analysis and repository mining techniques to provide an automated way for revealing potential sources of performance degradation of scenarios between releases of a software system. The approach defines four phases: (i) preparation – choosing the scenarios and preparing the target releases; (ii) dynamic analysis – determining the performance of scenarios and methods by calculating their execution time; (iii) degradation analysis – processing and comparing the results of …
Deep Multimodal Learning For Affective Analysis And Retrieval, Lei Pang, Shiai Zhu, Chong-Wah Ngo
Deep Multimodal Learning For Affective Analysis And Retrieval, Lei Pang, Shiai Zhu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Social media has been a convenient platform for voicing opinions through posting messages, ranging from tweeting a short text to uploading a media file, or any combination of messages. Understanding the perceived emotions inherently underlying these user-generated contents (UGC) could bring light to emerging applications such as advertising and media analytics. Existing research efforts on affective computation are mostly dedicated to single media, either text captions or visual content. Few attempts for combined analysis of multiple media are made, despite that emotion can be viewed as an expression of multimodal experience. In this paper, we explore the learning of highly …
Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case, Yi-Jie Lu, Maaike De Boer, Hao Zhang, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case, Yi-Jie Lu, Maaike De Boer, Hao Zhang, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
No abstract provided.
Using Gamification As A Collaboration Motivator For Software Development Teams: A Preliminary Framework, Flavio Steffens, Sabrina Marczak, Fernando Figueira Filho, Christoph Treude, Leif Singer, David Redmiles, Ban Al-Ani
Using Gamification As A Collaboration Motivator For Software Development Teams: A Preliminary Framework, Flavio Steffens, Sabrina Marczak, Fernando Figueira Filho, Christoph Treude, Leif Singer, David Redmiles, Ban Al-Ani
Research Collection School Of Computing and Information Systems
Gamification is the use of game elements in non-game context to engage and to motivate people to achieve goals. Its use is becoming very popular in software development organizations due to work being based upon human-centric and brain-intensive activity. This paper presents the topics of collaboration and gamification in the context of software engineering, and proposes a framework that identifies the most common collaboration issues that affect software development teams, and how to apply game elements to motivate a change on their behaviors.
A Method And System For Sentiment Classification And Emotion Classification [Us Patent 20170308523a1], Zhaoxia Wang, Rick Siow Mong Goh, Yinping Yang
A Method And System For Sentiment Classification And Emotion Classification [Us Patent 20170308523a1], Zhaoxia Wang, Rick Siow Mong Goh, Yinping Yang
Research Collection School Of Computing and Information Systems
A system and a method for classifying text messages, such as social media messages into sentiment valence categories are provided. The system comprising a module for decomposing text messages, a module for cleaning text messages, a module for producing feature data of text messages, and a module for classifying text messages into sentiment valence categories. The module for decomposing text messages is configured to: receive a text message, parse the text message into separate portions in response to parsing criteria based on sentence delimiters, wherein the separate portions are sentences, phrases and words, and rejoin at least some of the …
Human Action Recognition In Unconstrained Videos By Explicit Motion Modeling, Yu-Gang Jiang, Qi Dai, Wei Liu, Xiangyang Xue, Chong-Wah Ngo
Human Action Recognition In Unconstrained Videos By Explicit Motion Modeling, Yu-Gang Jiang, Qi Dai, Wei Liu, Xiangyang Xue, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Human action recognition in unconstrained videos is a challenging problem with many applications. Most state-of-the-art approaches adopted the well-known bag-of-features representations, generated based on isolated local patches or patch trajectories, where motion patterns, such as object-object and object-background relationships are mostly discarded. In this paper, we propose a simple representation aiming at modeling these motion relationships. We adopt global and local reference points to explicitly characterize motion information, so that the final representation is more robust to camera movements, which widely exist in unconstrained videos. Our approach operates on the top of visual codewords generated on dense local patch trajectories, …
Vireo-Tno @ Trecvid 2015: Multimedia Event Detection, Hao Zhang, Yi-Jie Lu, Maaike De Boer, Frank Ter Haar, Zhaofan Qiu, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Vireo-Tno @ Trecvid 2015: Multimedia Event Detection, Hao Zhang, Yi-Jie Lu, Maaike De Boer, Frank Ter Haar, Zhaofan Qiu, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper presents an overview and comparative analysis of our systems designed for the TRECVID 2015 [1] multimedia event detection (MED) task. We submitted 17 runs, of which 5 each for the zeroexample, 10-example and 100-example subtasks for the Pre-Specified (PS) event detection and 2 runs for the 10-example subtask for the Ad-Hoc (AH) event detection. We did not participate in the Interactive Run. This year we focus on three different parts of the MED task: 1) extending the size of our concept bank and combining it with improved dense trajectories; 2) exploring strategies for semantic query generation (SQG); and …
Multimedia Event Detection: Strong By Integration, Hao Zhang, Maaike De Boer, Yi-Jie Lu, Klamer Schutte, Chong-Wah Ngo, Chong-Wah Ngo
Multimedia Event Detection: Strong By Integration, Hao Zhang, Maaike De Boer, Yi-Jie Lu, Klamer Schutte, Chong-Wah Ngo, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
No abstract provided.
Event Detection In Wireless Sensor Networks In Random Spatial Sensors Deployments, Pengfei Zhang, Ido Nevat, Gareth W. Peters, Gaoxi Xiao, Hwee-Pink Tan
Event Detection In Wireless Sensor Networks In Random Spatial Sensors Deployments, Pengfei Zhang, Ido Nevat, Gareth W. Peters, Gaoxi Xiao, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
We develop a new class of event detection algorithms in Wireless Sensor Networks where the sensors are randomly deployed spatially. We formulate the detection problem as a binary hypothesis testing problem and design the optimal decision rules for two scenarios, namely the Poisson Point Process and Binomial Point Process random deployments. To calculate the intractable marginal likelihood density, we develop three types of series expansion methods which are based on an Askey-orthogonal polynomials. In addition, we develop a novel framework to provide guidance on which series expansion is most suitable (i.e., most accurate) to use for different system parameters. Extensive …
Assessing Developer Contribution With Repository Mining-Based Metrics, Jalerson Lima, Christoph Treude, Fernando Figueira Filho, Uirá Kulesza
Assessing Developer Contribution With Repository Mining-Based Metrics, Jalerson Lima, Christoph Treude, Fernando Figueira Filho, Uirá Kulesza
Research Collection School Of Computing and Information Systems
Productivity as a result of individual developers' contributions is an important aspect for software companies to maintain their competitiveness in the market. However, there is no consensus in the literature on how to measure productivity or developer contribution. While some repository mining-based metrics have been proposed, they lack validation in terms of their applicability and usefulness from the individuals who will use them to assess developer contribution: team and project leaders. In this paper, we propose the design of a suite of metrics for the assessment of developer contribution, based on empirical evidence obtained from project and team leaders. In …
Face Recognition On Large-Scale Video In The Wild With Hybrid Euclidean-And-Riemannian Metric Learning, Zhiwu Huang, R. Wang, S. Shan, X Chen
Face Recognition On Large-Scale Video In The Wild With Hybrid Euclidean-And-Riemannian Metric Learning, Zhiwu Huang, R. Wang, S. Shan, X Chen
Research Collection School Of Computing and Information Systems
Face recognition on large-scale video in the wild is becoming increasingly important due to the ubiquity of video data captured by surveillance cameras, handheld devices, Internet uploads, and other sources. By treating each video as one image set, set-based methods recently have made great success in the field of video-based face recognition. In the wild world, videos often contain extremely complex data variations and thus pose a big challenge of set modeling for set-based methods. In this paper, we propose a novel Hybrid Euclidean-and-Riemannian Metric Learning (HERML) method to fuse multiple statistics of image set. Specifically, we represent each image …
Detect Rumors Using Time Series Of Social Context Information On Microblogging Websites, Jing Ma, Wei Gao, Zhongyu Wei, Yueming Lu, Kam-Fai Wong
Detect Rumors Using Time Series Of Social Context Information On Microblogging Websites, Jing Ma, Wei Gao, Zhongyu Wei, Yueming Lu, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Automatically identifying rumors from online social media especially microblogging websites is an important research issue. Most of existing work for rumor detection focuses on modeling features related to microblog contents, users and propagation patterns, but ignore the importance of the variation of these social context features during the message propagation over time. In this study, we propose a novel approach to capture the temporal characteristics of these features based on the time series of rumor's lifecycle, for which time series modeling technique is applied to incorporate various social context information. Our experiments using the events in two microblog datasets confirm …
Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik
Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik
Research Collection School Of Computing and Information Systems
Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact …
Constrained Feature Selection For Localizing Faults, Tien-Duy B. Le, David Lo, Ming Li
Constrained Feature Selection For Localizing Faults, Tien-Duy B. Le, David Lo, Ming Li
Research Collection School Of Computing and Information Systems
Developers often take much time and effort to find buggy program elements. To help developers debug, many past studies have proposed spectrum-based fault localization techniques. These techniques compare and contrast correct and faulty execution traces and highlight suspicious program elements. In this work, we propose constrained feature selection algorithms that we use to localize faults. Feature selection algorithms are commonly used to identify important features that are helpful for a classification task. By mapping an execution trace to a classification instance and a program element to a feature, we can transform fault localization to the feature selection problem. Unfortunately, existing …
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
Research Collection School Of Computing and Information Systems
The Internet has brought about fundamental changes in the way peoples generate and exchange media information. Over the last decade, unsolicited message images (image spams) have become one of the most serious problems for Internet service providers (ISPs), business firms and general end users. In this paper, we report a novel system called RoBoTs (Robust BoosTrap based spam detector) to support accurate and robust image spam filtering. The system is developed based on multiple visual properties extracted from different levels of granularity, aiming to capture more discriminative contents for effective spam image identification. In addition, a resampling based learning framework …
Mood Self-Assessment On Smartphones, Le Minh Khue, Eng Lieh Ouh, Stan Jarzabek
Mood Self-Assessment On Smartphones, Le Minh Khue, Eng Lieh Ouh, Stan Jarzabek
Research Collection School Of Computing and Information Systems
Mood has been systematically studied by psychologists for over 100 years. As mood is a subjective feeling, any study of mood must take into account and accurately capture user’s perception of an experienced feeling. In last 40 years, a number of pen-andpaper mood self-assessment scales have been proposed. Typically, a person is asked to separately rate various dimensions of the experienced feeling (e.g., pleasure and arousal) or mood items (interested, agitated, excited, etc.) on numeric scales (e.g., between 0 and 10). These partial ratings are then combined into an overall mood rating (or into its positive and negative affect). Penand-paper …
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Research Collection School Of Computing and Information Systems
Relative similarity learning, as an important learning scheme for information retrieval, aims to learn a bi-linear similarity function from a collection of labeled instance-pairs, and the learned function would assign a high similarity value for a similar instance-pair and a low value for a dissimilar pair. Existing algorithms usually assume the labels of all the pairs in data streams are always made available for learning. However, this is not always realistic in practice since the number of possible pairs is quadratic to the number of instances in the database, and manually labeling the pairs could be very costly and time …
Automated Prediction Of Bug Report Priority Using Multi-Factor Analysis, Yuan Tian, David Lo, Chengnian Sun, Xin Xia
Automated Prediction Of Bug Report Priority Using Multi-Factor Analysis, Yuan Tian, David Lo, Chengnian Sun, Xin Xia
Research Collection School Of Computing and Information Systems
Bugs are prevalent. To improve software quality, developers often allow users to report bugs that they found using a bug tracking system such as Bugzilla. Users would specify among other things, a description of the bug, the component that is affected by the bug, and the severity of the bug. Based on this information, bug triagers would then assign a priority level to the reported bug. As resources are limited, bug reports would be investigated based on their priority levels. This priority assignment process however is a manual one. Could we do better? In this paper, we propose an automated …
A Note On The Security Of Khl Scheme, Jian Weng, Yunlei Zhao, Deng, Robert H., Shengli Liu, Yanjiang Yang, Kouichi Sakurai
A Note On The Security Of Khl Scheme, Jian Weng, Yunlei Zhao, Deng, Robert H., Shengli Liu, Yanjiang Yang, Kouichi Sakurai
Research Collection School Of Computing and Information Systems
A public key trace and revoke scheme combines the functionality of broadcast encryption with the capability of traitor tracing. In Asiacrypt 2003, Kim, Hwang and Lee proposed a public key trace and revoke scheme (referred to as KHL scheme), and gave the security proof to support that their scheme is z-resilient against adaptive chosen-ciphertext attacks, in which the adversary is allowed to adaptively issue decryption queries as well as adaptively corrupt up to z users. In the passed ten years, KHL scheme has been believed as one of the most efficient public key trace and revoke schemes with z-resilience against …
Social Tag Relevance Estimation Via Ranking-Oriented Neighbour Voting, Chaoran Cui, Jialie Shen, Jun Ma, Tao Lian
Social Tag Relevance Estimation Via Ranking-Oriented Neighbour Voting, Chaoran Cui, Jialie Shen, Jun Ma, Tao Lian
Research Collection School Of Computing and Information Systems
User-generated tags associated with social images are frequently imprecise and incomplete. Therefore, a fundamental challenge in tag-based applications is the problem of tag relevance estimation, which concerns how to interpret and quantify the relevance of a tag with respect to the contents of an image. In this paper, we address the key problem from a new perspective of learning to rank, and develop a novel approach to facilitate tag relevance estimation to directly optimize the ranking performance of tag-based image search. A supervision step is introduced into the neighbour voting scheme, in which tag relevance is estimated by accumulating votes …
Seeing Your Face Is Not Enough: An Inertial Sensor-Based Liveness Detection For Face Authentication, Yan Li, Yingjiu Li, Qiang Yan, Hancong Kong, Robert H. Deng
Seeing Your Face Is Not Enough: An Inertial Sensor-Based Liveness Detection For Face Authentication, Yan Li, Yingjiu Li, Qiang Yan, Hancong Kong, Robert H. Deng
Research Collection School Of Computing and Information Systems
Leveraging built-in cameras on smartphones and tablets, face authentication provides an attractive alternative of legacy passwords due to its memory-less authentication process. However, it has an intrinsic vulnerability against the media-based facial forgery (MFF) where adversaries use photos/videos containing victims' faces to circumvent face authentication systems. In this paper, we propose FaceLive, a practical and robust liveness detection mechanism to strengthen the face authentication on mobile devices in fighting the MFF-based attacks. FaceLive detects the MFF-based attacks by measuring the consistency between device movement data from the inertial sensors and the head pose changes from the facial video captured by …
Structural Constraints For Multipartite Entity Resolution With Markov Logic Network, Tengyuan Ye, Hady W. Lauw
Structural Constraints For Multipartite Entity Resolution With Markov Logic Network, Tengyuan Ye, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Multipartite entity resolution seeks to match entity mentions across several collections. An entity mention is presumed unique within a collection, and thus could match at most one entity mention in each of the other collections. In addition to domain-specific features considered in entity resolution, there are a number of domain-invariant structural contraints that apply in this scenario, including one-to-one assignment as well as cross-collection transitivity. We propose a principled solution to the multipartite entity resolution problem, building on the foundation of Markov Logic Network (MLN) that combines probabilistic graphical model and first-order logic. We describe how the domain-invariant structural constraints …
Targeted Blended Learning Through Competency Assessment In An Undergraduate Information Systems Program, Joelle Elmaleh, Shankararaman, Venky
Targeted Blended Learning Through Competency Assessment In An Undergraduate Information Systems Program, Joelle Elmaleh, Shankararaman, Venky
Research Collection School Of Computing and Information Systems
In this paper we report our study on the problem of competency acquisition when students progress from one course to another and more generally, from one term to the next. We observed that some students moved on to a second programming course without acquiring some of the competencies in the first programming course. This leads to problem in the second course, especially when these competencies are pre-requisites for this course. We applied blended learning, which allows a student to learn at least in part through delivery of content and instruction via online media, to overcome this problem. Our approach is …