Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (3441)
- Software Engineering (2143)
- Artificial Intelligence and Robotics (1664)
- Information Security (1056)
- Numerical Analysis and Scientific Computing (1024)
-
- Graphics and Human Computer Interfaces (921)
- Engineering (857)
- Social and Behavioral Sciences (661)
- Business (625)
- Theory and Algorithms (493)
- Computer Engineering (431)
- Operations Research, Systems Engineering and Industrial Engineering (399)
- Programming Languages and Compilers (379)
- OS and Networks (322)
- Communication (297)
- Social Media (240)
- Public Affairs, Public Policy and Public Administration (207)
- Transportation (185)
- Medicine and Health Sciences (178)
- Education (164)
- Management Information Systems (164)
- Data Storage Systems (160)
- E-Commerce (146)
- Health Information Technology (107)
- International and Area Studies (107)
- Asian Studies (106)
- Technology and Innovation (100)
- Digital Communications and Networking (96)
- Keyword
-
- Deep learning (122)
- Machine learning (121)
- Social media (74)
- Artificial intelligence (70)
- Reinforcement learning (69)
-
- Data mining (64)
- Privacy (61)
- Cloud computing (58)
- Deep Learning (56)
- Empirical study (54)
- Optimization (53)
- Security (53)
- Visualization (51)
- Software engineering (49)
- Training (49)
- Neural networks (48)
- Online learning (48)
- Task analysis (48)
- Anomaly detection (47)
- Singapore (47)
- Twitter (46)
- Feature extraction (45)
- Blockchain (44)
- Collaboration (44)
- Large Language Models (43)
- Semantics (43)
- Access control (41)
- Algorithms (40)
- Android (39)
- Machine Learning (38)
- Publication Year
- File Type
Articles 5521 - 5550 of 8479
Full-Text Articles in Computer Sciences
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 …
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 …
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 …
An Empirical Assessment Of Bellon's Clone Benchmark, Alan Charpentier, Jean-Rémy Falleri, David Lo, Laurent Reveillere
An Empirical Assessment Of Bellon's Clone Benchmark, Alan Charpentier, Jean-Rémy Falleri, David Lo, Laurent Reveillere
Research Collection School Of Computing and Information Systems
Context: Clone benchmarks are essential to the assessment and improvement of clone detection tools and algorithms. Among existing benchmarks, Bellon's benchmark is widely used by the research community. However, a serious threat to the validity of this benchmark is that reference clones it contains have been manually validated by Bellon alone. Other persons may disagree with Bellon's judgment. Objective: In this paper, we perform an empirical assessment of Bellon's benchmark. Method: We seek the opinion of eighteen participants on a subset of Bellon's benchmark to determine if researchers should trust the reference clones it contains. Results: Our experiment shows that …
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 …
Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim
Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Context data, collected either from mobile devices or from user-generated social media content, can help identify abnormal behavioural patterns in public spaces (e.g., shopping malls, college campuses or downtown city areas). Spatiotemporal analysis of such data streams provides a compelling new approach towards automatically creating real-time urban situational awareness, especially about events that are unanticipated or that evolve very rapidly. In this work, we use real-life datasets collected via SMU's LiveLabs testbed or via SMU's Palanteer software, to explore various discriminative features (both spatial and temporal - e.g., occupancy volumes, rate of change in topic{specific tweets or probabilistic distribution of …
High-Throughput Reliable Multicast In Multi-Hop Wireless Mesh Networks, Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, Sanjay K. Jha
High-Throughput Reliable Multicast In Multi-Hop Wireless Mesh Networks, Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, Sanjay K. Jha
Research Collection School Of Computing and Information Systems
This paper presents a cross-layer approach for enabling high-throughput reliable multicast in multi-hop wireless mesh networks. The building block of our approach is a multicast routing metric, called the expected multicast transmission count (EMTX). EMTX is designed to capture the combined effects of MAC-layer retransmission-based reliability, wireless broadcast advantage, and link quality awareness. The EMTX of single-hop transmission of a multicast packet from a sender is the expected number of multicast transmissions (including retransmissions) required for its next-hop recipients to receive the packet successfully. We formulate the EMTX-based multicast problem with the objective of minimizing the sum of EMTX over …
Memory Dynamics In Attractor Networks, Guoqi Li, Kiruthika Ramanathan, Ning Ning, Luping Shi, Changyun Wen
Memory Dynamics In Attractor Networks, Guoqi Li, Kiruthika Ramanathan, Ning Ning, Luping Shi, Changyun Wen
Research Collection School Of Computing and Information Systems
As can be represented by neurons and their synaptic connections, attractor networks are widely believed to underlie biological memory systems and have been used extensively in recent years to model the storage and retrieval process of memory. In this paper, we propose a new energy function, which is nonnegative and attains zero values only at the desired memory patterns. An attractor network is designed based on the proposed energy function. It is shown that the desired memory patterns are stored as the stable equilibrium points of the attractor network. To retrieve a memory pattern, an initial stimulus input is presented …
Maximizing Lifetime In Clustered Wsns With Energy Harvesting Relay: Profiling And Modeling, Pengfei Zhang, Hwee-Pink Tan, Gaoxi Xiao, Yi Yu
Maximizing Lifetime In Clustered Wsns With Energy Harvesting Relay: Profiling And Modeling, Pengfei Zhang, Hwee-Pink Tan, Gaoxi Xiao, Yi Yu
Research Collection School Of Computing and Information Systems
Inspired by clustering and energy harvesting techniques, we study multiple-cluster wireless sensor networks with energy harvesting (EH) sensors serving as relay for cluster heads. In this paper, we derive the model for realistic energy harvesting rate. Then we propose distributed matching algorithm for EHs to serve as relay for CHs. The proposed algorithm could find optimal/near-optimal CH-EH matching in short time and still achieve good performance. We evaluate the performance of our method through theoretical analysis as well as simulation.
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 …
Sensorem – An Efficient Mobile Platform For Wireless Sensor Network Visualization, Jin Ming Koh, Marcus Sak, Hwee Xian Tan, Huiguang Liang, Fachmin Folianto, Tony Quek
Sensorem – An Efficient Mobile Platform For Wireless Sensor Network Visualization, Jin Ming Koh, Marcus Sak, Hwee Xian Tan, Huiguang Liang, Fachmin Folianto, Tony Quek
Research Collection School Of Computing and Information Systems
No abstract provided.
Multi-Roles Affiliation Model For General User Profiling, Lizi Liao, Heyan Huang, Yashen Wang
Multi-Roles Affiliation Model For General User Profiling, Lizi Liao, Heyan Huang, Yashen Wang
Research Collection School Of Computing and Information Systems
Online social networks release user attributes, which is important for many applications. Due to the sparsity of such user attributes online, many works focus on profiling user attributes automatically. However, in order to profile a specific user attribute, an unique model is built and such model usually does not fit other profiling tasks. In our work, we design a novel, flexible general user profiling model which naturally models users’ friendships with user attributes. Experiments show that our method simultaneously profile multiple attributes with better performance.
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 …
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 …
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 …
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 …
Students’ Perspectives On Flipped Classroom Implementation In Higher Education, Joelle Elmaleh, Nachamma Sockalingam
Students’ Perspectives On Flipped Classroom Implementation In Higher Education, Joelle Elmaleh, Nachamma Sockalingam
Research Collection School Of Computing and Information Systems
This paper reports students' experiences with a Flipped Classroom pedagogy model in an undergraduate programming course and suggests ways to improve the Flipped Classroom implementation.
An Iterated Local Search Algorithm For Solving The Orienteering Problem With Time Windows, Aldy Gunawan, Hoong Chuin Lau, Kun Lu
An Iterated Local Search Algorithm For Solving The Orienteering Problem With Time Windows, Aldy Gunawan, Hoong Chuin Lau, Kun Lu
Research Collection School Of Computing and Information Systems
The Orienteering Problem with Time Windows (OPTW) is a variant of the Orienteering Problem (OP). Given a set of nodes including their scores, service times and time windows, the goal is to maximize the total of scores collected by a particular route considering a predefined time window during which the service has to start. We propose an Iterated Local Search (ILS) algorithm to solve the OPTW, which is based on several LocalSearch operations, such as swap, 2-opt, insert and replace. We also implement the combination between AcceptanceCriterion and Perturbation mechanisms to control the balance between diversification and intensification of the …
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 …
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 …
Measuring User Influence, Susceptibility And Cynicalness In Sentiment Diffusion, Roy Ka-Wei Lee, Ee Peng Lim
Measuring User Influence, Susceptibility And Cynicalness In Sentiment Diffusion, Roy Ka-Wei Lee, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Diffusion in social networks is an important research topic lately due to massive amount of information shared on social media and Web. As information diffuses, users express sentiments which can affect the sentiments of others. In this paper, we analyze how users reinforce or modify sentiment of one another based on a set of inter-dependent latent user factors as they are engaged in diffusion of event information. We introduce these sentiment-based latent user factors, namely influence, susceptibility and cynicalness. We also propose the ISC model to relate the three factors together and develop an iterative computation approach to …
Click-Boosting Multi-Modality Graph-Based Reranking For Image Search, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Chong-Wah Ngo, Tao Mei
Click-Boosting Multi-Modality Graph-Based Reranking For Image Search, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Chong-Wah Ngo, Tao Mei
Research Collection School Of Computing and Information Systems
Image reranking is an effective way for improving the retrieval performance of keyword-based image search engines. A fundamental issue underlying the success of existing image reranking approaches is the ability in identifying potentially useful recurrent patterns from the initial search results. Ideally, these patterns can be leveraged to upgrade the ranks of visually similar images, which are also likely to be relevant. The challenge, nevertheless, originates from the fact that keyword-based queries are used to be ambiguous, resulting in difficulty in predicting the search intention. Mining useful patterns without understanding query is risky, and may lead to incorrect judgment in …
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 …
On Efficient K-Optimal-Location-Selection Query Processing In Metric Spaces, Yunjun Gao, Shuyao Qi, Lu Chen, Baihua Zheng, Xinhan Li
On Efficient K-Optimal-Location-Selection Query Processing In Metric Spaces, Yunjun Gao, Shuyao Qi, Lu Chen, Baihua Zheng, Xinhan Li
Research Collection School Of Computing and Information Systems
This paper studies the problem of k-optimal-location-selection (kOLS) retrieval in metric spaces. Given a set DA of customers, a set DB of locations, a constrained region R , and a critical distance dc, a metric kOLS (MkOLS) query retrieves k locations in DB that are outside R but have the maximal optimality scores. Here, the optimality score of a location l∈DB located outside R is defined as the number of the customers in DA that are inside R and meanwhile have their distances to l bounded by …
Project Sourcing For Capstone Course Experience From An Undergraduate Program, Benjamin Gan, Venky Shankararaman
Project Sourcing For Capstone Course Experience From An Undergraduate Program, Benjamin Gan, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Capstone project courses give students experience solving a substantial problem using concepts that span several topic areas in the program of study. Having 280 students graduate every year, requires a substantial effort towards sourcing appropriate projects from the industry and academia that provide hands-on opportunity to apply IT solutions to problems. This paper presents two sourcing models for supporting the sourcing of capstone projects. For each model, the various project origination sources, the distinct attributes, the challenges and lessons learnt are discussed.
Code Coverage And Test Suite Effectiveness: Empirical Study With Real Bugs In Large Systems, Pavneet Singh Kochhar, Ferdian Thung, David Lo
Code Coverage And Test Suite Effectiveness: Empirical Study With Real Bugs In Large Systems, Pavneet Singh Kochhar, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
During software maintenance, testing is a crucial activity to ensure the quality of program code as it evolves over time. With the increasing size and complexity of software, adequate software testing has become increasingly important. Code coverage is often used as a yardstick to gauge the comprehensiveness of test cases and the adequacy of testing. A test suite quality is often measured by the number of bugs it can find (aka. kill). Previous studies have analysed the quality of a test suite by its ability to kill mutants, i.e., artificially seeded faults. However, mutants do not necessarily represent real bugs. …
Nirmal: Automatic Identification Of Software Relevant Tweets Leveraging Language Model, Abishek Sharma, Yuan Tian, David Lo
Nirmal: Automatic Identification Of Software Relevant Tweets Leveraging Language Model, Abishek Sharma, Yuan Tian, David Lo
Research Collection School Of Computing and Information Systems
Twitter is one of the most widely used social media platforms today. It enables users to share and view short 140-character messages called 'tweets'. About 284 million active users generate close to 500 million tweets per day. Such rapid generation of user generated content in large magnitudes results in the problem of information overload. Users who are interested in information related to a particular domain have limited means to filter out irrelevant tweets and tend to get lost in the huge amount of data they encounter. A recent study by Singer et al. found that software developers use Twitter to …
Managing Technical Debt: Insights From Recent Empirical Evidence, Narayan Ramasubbu, Chris F. Kemerer, C. Jason Woodard
Managing Technical Debt: Insights From Recent Empirical Evidence, Narayan Ramasubbu, Chris F. Kemerer, C. Jason Woodard
Research Collection School Of Computing and Information Systems
Technical debt refers to maintenance obligations that software teams accumulate as a result of their actions. Empirical research has led researchers to suggest three dimensions along which software development teams should map their technical-debt metrics: customer satisfaction needs, reliability needs, and the probability of technology disruption.
Reconstruction Privacy: Enabling Statistical Learning, Ke Wang, Chao Han, Ada Waichee Fu, Raymond C. Wong, Philip S. Yu
Reconstruction Privacy: Enabling Statistical Learning, Ke Wang, Chao Han, Ada Waichee Fu, Raymond C. Wong, Philip S. Yu
Research Collection School Of Computing and Information Systems
Non-independent reasoning (NIR) allows the information about one record in the data to be learnt from the information of other records in the data. Most posterior/prior based privacy criteria consider NIR as a privacy violation and require to smooth the distribution of published data to avoid sensitive NIR. The drawback of this approach is that it limits the utility of learning statistical relationships. The differential privacy criterion considers NIR as a non-privacy violation, therefore, enables learning statistical relationships, but at the cost of potential disclosures through NIR. A question is whether it is possible to (1) allow learning statistical relationships, …