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Full-Text Articles in Entire DC Network
On Modeling Brand Preferences In Item Adoptions, Minh Duc Luu, Ee Peng Lim, Freddy Chong-Tat Chua
On Modeling Brand Preferences In Item Adoptions, Minh Duc Luu, Ee Peng Lim, Freddy Chong-Tat Chua
Research Collection School Of Computing and Information Systems
In marketing and advertising, developing and managingbrands value represent the core activities performedby companies. Successful brands attract buyers andadopters, which in turn increase the companies’ value.Given a set of user-item adoption data, can we inferbrand effects from users adopting items? To answerthis question, we develop the Brand Item Topic Model(BITM) that incorporates users’ brand preferences inthe process of item adoption by the users. We evaluateour model using synthetic and two real world datasetsagainst baseline models which do not consider brand effects.The results show that BITM can determine userswho demonstrate brand preferences and predict itemadoptions more accurately.
Sew-Ing A Simple Endorsement Web To Incentivize Trustworthy Participatory Sensing, T. Luo, S. Kanhere, Hwee-Pink Tan
Sew-Ing A Simple Endorsement Web To Incentivize Trustworthy Participatory Sensing, T. Luo, S. Kanhere, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Two crucial issues to the success of participatory sensing are (a) how to incentivize the large crowd of mobile users to participate and (b) how to ensure the sensing data to be trustworthy. While they are traditionally being studied separately in the literature, this paper proposes a Simple Endorsement Web (SEW) to address both issues in a synergistic manner. The key idea is (a) introducing a social concept called nepotism into participatory sensing, by linking mobile users into a social “web of participants” with endorsement relations, and (b) overlaying this network with investment-like economic implications. The social and economic layers …
Bootstrapping Simulation-Based Algorithms With A Suboptimal Policy, Nguyen T., Silander T., Lee W., Tze-Yun Leong
Bootstrapping Simulation-Based Algorithms With A Suboptimal Policy, Nguyen T., Silander T., Lee W., Tze-Yun Leong
Research Collection School Of Computing and Information Systems
Finding optimal policies for Markov Decision Processes with large state spaces is in general intractable. Nonetheless, simulation-based algorithms inspired by Sparse Sampling (SS) such as Upper Confidence Bound applied in Trees (UCT) and Forward Search Sparse Sampling (FSSS) have been shown to perform reasonably well in both theory and practice, despite the high computational demand. To improve the efficiency of these algorithms, we adopt a simple enhancement technique with a heuristic policy to speed up the selection of optimal actions. The general method, called Aux, augments the look-ahead tree with auxiliary arms that are evaluated by the heuristic policy. In …
On Efficient Reverse Skyline Query Processing, Yunjun Gao, Qing Liu, Baihua Zheng, Gang Chen
On Efficient Reverse Skyline Query Processing, Yunjun Gao, Qing Liu, Baihua Zheng, Gang Chen
Research Collection School Of Computing and Information Systems
Given a D-dimensional data set P and a query point q, a reverse skyline query (RSQ) returns all the data objects in P whose dynamic skyline contains q. It is important for many real life applications such as business planning and environmental monitoring. Currently, the state-of-the-art algorithm for answering the RSQ is the reverse skyline using skyline approximations (RSSA) algorithm, which is based on the precomputed approximations of the skylines. Although RSSA has some desirable features, e.g., applicability to arbitrary data distributions and dimensions, it needs for multiple accesses of the same nodes, incurring redundant I/O and CPU costs. In …
Sewordsim: Software-Specific Word Similarity Database, Yuan Tian, David Lo, Julia Lawall
Sewordsim: Software-Specific Word Similarity Database, Yuan Tian, David Lo, Julia Lawall
Research Collection School Of Computing and Information Systems
Measuring the similarity of words is important in accurately representing and comparing documents, and thus improves the results of many natural language processing (NLP) tasks. The NLP community has proposed various measurements based on WordNet, a lexical database that contains relationships between many pairs of words. Recently, a number of techniques have been proposed to address software engineering issues such as code search and fault localization that require understanding natural language documents, and a measure of word similarity could improve their results. However, WordNet only contains information about words senses in general-purpose conversation, which often differ from word senses in …
Boat: An Experimental Platform For Researchers To Comparatively And Reproducibly Evaluate Bug Localization Techniques, Xinyu Wang, David Lo, Xin Xia, Xingen Wang, Pavneet Singh Kochhar, Yuan Tian, Xiaohu Yang, Shanping Li, Jianling Sun, Bo Zhou
Boat: An Experimental Platform For Researchers To Comparatively And Reproducibly Evaluate Bug Localization Techniques, Xinyu Wang, David Lo, Xin Xia, Xingen Wang, Pavneet Singh Kochhar, Yuan Tian, Xiaohu Yang, Shanping Li, Jianling Sun, Bo Zhou
Research Collection School Of Computing and Information Systems
Bug localization refers to the process of identifying source code files that contain defects from descriptions of these defects which are typically contained in bug reports. There have been many bug localization techniques proposed in the literature. However, often it is hard to compare these techniques since different evaluation datasets are used. At times the datasets are not made publicly available and thus it is difficult to reproduce reported results. Furthermore, some techniques are only evaluated on small datasets and thus it is not clear whether the results are generalizable. Thus, there is a need for a platform that allows …
Graph-Based Semi-Supervised Learning: Realizing Pointwise Smoothness Probabilistically, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw
Graph-Based Semi-Supervised Learning: Realizing Pointwise Smoothness Probabilistically, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw
Research Collection School Of Computing and Information Systems
As the central notion in semi-supervised learning, smoothness is often realized on a graph representation of the data. In this paper, we study two complementary dimensions of smoothness: its pointwise nature and probabilistic modeling. While no existing graph-based work exploits them in conjunction, we encompass both in a novel framework of Probabilistic Graph-based Pointwise Smoothness (PGP), building upon two foundational models of data closeness and label coupling. This new form of smoothness axiomatizes a set of probability constraints, which ultimately enables class prediction. Theoretically, we provide an error and robustness analysis of PGP. Empirically, we conduct extensive experiments to show …
Cross-Language Bug Localization, Xin Xia, David Lo, Xingen Wang, Chenyi Zhang, Xinyu Wang
Cross-Language Bug Localization, Xin Xia, David Lo, Xingen Wang, Chenyi Zhang, Xinyu Wang
Research Collection School Of Computing and Information Systems
Bug localization refers to the process of identifying source code files that contain defects from textual descriptions in bug reports. Existing bug localization techniques work on the assumption that bug reports, and identifiers and comments in source code files, are written in the same language (i.e., English). However, software users from non-English speaking countries (e.g., China) often use their native languages (e.g., Chinese) to write bug reports. For this setting, existing studies on bug localization would not work as the terms that appear in the bug reports do not appear in the source code. We refer to this problem as …
A Hybrid Model Of Connectors In Cyber-Physical Systems, Xiaohong Chen, Jun Sun, Meng Sun Sun
A Hybrid Model Of Connectors In Cyber-Physical Systems, Xiaohong Chen, Jun Sun, Meng Sun Sun
Research Collection School Of Computing and Information Systems
Compositional coordination models and languages play an important role in cyber-physical systems (CPSs). In this paper, we introduce a formal model for describing hybrid behaviors of connectors in CPSs. We extend the constraint automata model, which is used as the semantic model for the exogenous channel-based coordination language Reo, to capture the dynamic behavior of connectors in CPSs where the discrete and continuous dynamics co-exist and interact with each other. In addition to the formalism, we also provide a theoretical compositional approach for constructing the product automata for a Reo circuit, which is typically obtained by composing several primitive connectors …
Practical Analysis Framework For Software-Based Attestation Scheme, Li Li, Hong Hu, Jun Sun, Yang Liu, Dong Jin Song
Practical Analysis Framework For Software-Based Attestation Scheme, Li Li, Hong Hu, Jun Sun, Yang Liu, Dong Jin Song
Research Collection School Of Computing and Information Systems
An increasing number of ”smart” embedded devices are employed in our living environment nowadays. Unlike traditional computer systems, these devices are often physically accessible to the attackers. It is therefore almost impossible to guarantee that they are un-compromised, i.e., that indeed the devices are executing the intended software. In such a context, software-based attestation is deemed as a promising solution to validate their software integrity. It guarantees that the software running on the embedded devices are un-compromised without any hardware support. However, designing software-based attestation protocols are shown to be error-prone. In this work, we develop a framework for design …
Gpu Accelerated Counterexample Generation In Ltl Model Checking, Zhimin Wu, Yang Liu, Yun Liang, Jun Sun
Gpu Accelerated Counterexample Generation In Ltl Model Checking, Zhimin Wu, Yang Liu, Yun Liang, Jun Sun
Research Collection School Of Computing and Information Systems
Strongly Connected Component (SCC) based searching is one of the most popular LTL model checking algorithms. When the SCCs are huge, the counterexample generation process can be time-consuming, especially when dealing with fairness assumptions. In this work, we propose a GPU accelerated counterexample generation algorithm, which improves the performance by parallelizing the Breadth First Search (BFS) used in the counterexample generation. BFS work is irregular, which means it is hard to allocate resources and may suffer from imbalanced load. We make use of the features of latest CUDA Compute Architecture-NVIDIA Kepler GK110 to achieve the dynamic parallelism and memory hierarchy …
Scc-Based Improved Reachability Analysis For Markov Decision Processes, Lin Gui, Jun Sun, Songzheng Song, Yang Liu, Jin Song Dong
Scc-Based Improved Reachability Analysis For Markov Decision Processes, Lin Gui, Jun Sun, Songzheng Song, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Markov decision processes (MDPs) are extensively used to model systems with both probabilistic and nondeterministic behavior. The problem of calculating the probability of reaching certain system states (hereafter reachability analysis) is central to the MDP-based system analysis. It is known that existing approaches on reachability analysis for MDPs are often inefficient when a given MDP contains a large number of states and loops, especially with the existence of multiple probability distributions. In this work, we propose a method to eliminate strongly connected components (SCCs) in an MDP using a divide-and-conquer algorithm, and actively remove redundant probability distributions in the MDP …
Tauth: Verifying Timed Security Protocols, Li Li, Jun Sun, Yang Liu, Jin Song Dong
Tauth: Verifying Timed Security Protocols, Li Li, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Quantitative timing is often relevant to the security of systems, like web applications, cyber-physical systems, etc. Verifying timed security protocols is however challenging as both arbitrary attacking behaviors and quantitative timing may lead to undecidability. In this work, we develop a service framework to support intuitive modeling of the timed protocol, as well as automatic verification with an unbounded number of sessions. The partial soundness and completeness of our verification algorithms are formally defined and proved. We implement our method into a tool called TAuth and the experiment results show that our approach is efficient and effective in both finding …
Learning Directional Co-Occurrence For Human Action Classification, Hong Liu, Mengyuan Liu, Qianru Sun
Learning Directional Co-Occurrence For Human Action Classification, Hong Liu, Mengyuan Liu, Qianru Sun
Research Collection School Of Computing and Information Systems
Spatio-temporal interest point (STIP) based methods have shown promising results for human action classification. However, state-of-art works typically utilize bag-of-visual words (BoVW), which focuses on the statistical distribution of features but ignores their inherent structural relationships. To solve this problem, a descriptor, namely directional pair-wise feature (DPF), is proposed to encode the mutual direction information between pairwise words, aiming at adding more spatial discriminant to BoVW. Firstly, STIP features are extracted and classified into a set of labeled words. Then in each frame, the DPF is constructed for every pair of words with different labels, according to their assigned directional …
Lifi: Line-Of-Sight Identification With Wifi, Zimu Zhou, Zheng Yang, Chenshu Wu, Wei Sun, Yunhao Liu
Lifi: Line-Of-Sight Identification With Wifi, Zimu Zhou, Zheng Yang, Chenshu Wu, Wei Sun, Yunhao Liu
Research Collection School Of Computing and Information Systems
Wireless LANs, especially WiFi, have been pervasively deployed and have fostered myriad wireless communication services and ubiquitous computing applications. A primary concern in designing each scenario-tailored application is to combat harsh indoor propagation environments, particularly Non-LineOf-Sight (NLOS) propagation. The ability to distinguish LineOf-Sight (LOS) path from NLOS paths acts as a key enabler for adaptive communication, cognitive radios, robust localization, etc. Enabling such capability on commodity WiFi infrastructure, however, is prohibitive due to the coarse multipath resolution with mere MAC layer RSSI. In this work, we dive into the PHY layer and strive to eliminate irrelevant noise and NLOS paths …
Supporting Non-Verbal Visual Communication In Online Group Art Therapy, Brennan Jones, Kate Collie, Sara Prins Hankinson, Anthony Tang
Supporting Non-Verbal Visual Communication In Online Group Art Therapy, Brennan Jones, Kate Collie, Sara Prins Hankinson, Anthony Tang
Research Collection School Of Computing and Information Systems
Art therapy provides therapeutic benefit to people suffering from chronic pain, and recent work has explored supporting art therapy through online tools such as chat forums and discussion boards. These tools give people the benefit of engaging in art therapy without the burden of having to leave one’s home (when transportation may be a challenge), and allowing people to reveal their identities through dialogue and activity rather than through one’s appearance. However, these tools also do not provide much opportunity for collaboration and shared art making. Because group members are not aware of each other’s actions and non-verbal cues in …
One Space: Shared Visual Scenes For Active Free Play, Maayan Cohen, Kody Dillman, Haley Macleod, Seth Hunter, Anthony Tang
One Space: Shared Visual Scenes For Active Free Play, Maayan Cohen, Kody Dillman, Haley Macleod, Seth Hunter, Anthony Tang
Research Collection School Of Computing and Information Systems
Children engage in free play for emotional, physical and social development; researchers have explored supporting free play between physically remote playmates using videoconferencing tools. We show that the configuration of the video conferencing setup affects play. Specifically, we show that a shared visual scene configuration promotes fundamentally active forms of engaged, co-operative play.
Simple Effective Named Entity Recognition For Microblogs: Arabic As An Example, Kareem Darwish, Wei Gao
Simple Effective Named Entity Recognition For Microblogs: Arabic As An Example, Kareem Darwish, Wei Gao
Research Collection School Of Computing and Information Systems
No abstract provided.
Persistent Community Detection In Dynamic Social Networks, Siyuan Liu, Shuhui Wang, Ramayya Krishnan
Persistent Community Detection In Dynamic Social Networks, Siyuan Liu, Shuhui Wang, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
While community detection is an active area of research in social network analysis, little effort has been devoted to community detection using time-evolving social network data. We propose an algorithm, Persistent Community Detection (PCD), to identify those communities that exhibit persistent behavior over time, for usage in such settings. Our motivation is to distinguish between steady-state network activity, and impermanent behavior such as cascades caused by a noteworthy event. The results of extensive empirical experiments on real-life big social networks data show that our algorithm performs much better than a set of baseline methods, including two alternative models and the …
Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu
Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu
Research Collection School Of Computing and Information Systems
Mining trajectory datasets has many important applications. Real trajectory data often involve uncertainty due to inadequate sampling rates and measurement errors. For some trajectories, their precise positions cannot be recovered and the exact routes that vehicles traveled cannot be accurately reconstructed. In this paper, we investigate the uncertainty problem in trajectory data and present a visual analytics system to reveal, analyze, and solve the uncertainties associated with trajectory samples. We first propose two novel visual encoding schemes called the road map analyzer and the uncertainty lens for discovering road map errors and visually analyzing the uncertainty in trajectory data respectively. …
Towards Semantically Secure Outsourcing Of Association Rule Mining On Categorical Data, Junzuo Lai, Yingjiu Li, Robert H. Deng, Jian Weng, Chaowen Guan, Qiang Yan
Towards Semantically Secure Outsourcing Of Association Rule Mining On Categorical Data, Junzuo Lai, Yingjiu Li, Robert H. Deng, Jian Weng, Chaowen Guan, Qiang Yan
Research Collection School Of Computing and Information Systems
When outsourcing association rule mining to cloud, it is critical for data owners to protect both sensitive raw data and valuable mining results from being snooped at cloud servers. Previous solutions addressing this concern add random noise to the raw data and/or encrypt the raw data with a substitution mapping. However, these solutions do not provide semantic security; partial information about raw data or mining results can be potentially discovered by an adversary at cloud servers under a reasonable assumption that the adversary knows some plaintext–ciphertext pairs. In this paper, we propose the first semantically secure solution for outsourcing association …
Handling Location Uncertainty In Event Driven Experimentation, Kartik Muralidharan, Srinivasan Seshan, Narayan Ramasubbu, Rajesh Krishna Balan
Handling Location Uncertainty In Event Driven Experimentation, Kartik Muralidharan, Srinivasan Seshan, Narayan Ramasubbu, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
The wide spread use of smart phones has ushered in a wave of context-based advertising services that operate on pre-defined user events. A prime example is Location Based Advertising. What is missing though, is the ability to experiment with these services under varying event conditions with real users using their regular phones in real-world environments. Such experiments provide greater insight into user needs for and responsiveness towards context-based advertising applications. However, these event-driven experiments rely on data that arrive from sources such as mobile sensors which have inherent uncertainties associated with them. This effects the interpretation of the outcome of …
Decentralized Multi-Agent Reinforcement Learning In Average-Reward Dynamic Dcops, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein
Decentralized Multi-Agent Reinforcement Learning In Average-Reward Dynamic Dcops, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Researchers have introduced the Dynamic Distributed Constraint Optimization Problem (Dynamic DCOP) formulation to model dynamically changing multi-agent coordination problems, where a dynamic DCOP is a sequence of (static canonical) DCOPs, each partially different from the DCOP preceding it. Existing work typically assumes that the problem in each time step is decoupled from the problems in other time steps, which might not hold in some applications. Therefore, in this paper, we make the following contributions: (i) We introduce a new model, called Markovian Dynamic DCOPs (MD-DCOPs), where the DCOP in the next time step is a function of the value assignments …
Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni
Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni
Research Collection School Of Computing and Information Systems
Sensing data from mobile phones provide us exciting and profitable applications. Recent research focuses on sensing indoor environment, but suffers from inaccuracy because of the limited reachability of human traces or requires human intervention to perform sophisticated tasks. In this paper, we present ShopProfiler, a shop profiling system on crowdsourcing data. First, we extract customer movement patterns from traces. Second, we improve accuracy of building floor plan by adopting a gradient-based approach and then localize shops through WiFi heat map. Third, we categorize shops by designing an SVM classifier in shop space to support multi-label classification. Finally, we infer brand …
Declarative-Procedural Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow, Tan Yuan-Sin
Declarative-Procedural Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow, Tan Yuan-Sin
Research Collection School Of Computing and Information Systems
It has been well recognized that human makes use of both declarative memory and procedural memory for decision making and problem solving. In this paper, we propose a computational model with the overall architecture and individual processes for realizing the interaction between the declarative and procedural memory based on self-organizing neural networks. We formalize two major types of memory interactions and show how each of them can be embedded into autonomous reinforcement learning agents. Our experiments based on the Toad and Frog puzzle and a strategic game known as Starcraft Broodwar have shown that the cooperative interaction between declarative knowledge …
How Many Eyeballs Does A Bug Need? An Empirical Validation Of Linus' Law, Subhajit Datta, Proshanta Sarkar, Sutirtha Das, Sonu Sreshtha, Prasanth Lade, Subhashis Majumder
How Many Eyeballs Does A Bug Need? An Empirical Validation Of Linus' Law, Subhajit Datta, Proshanta Sarkar, Sutirtha Das, Sonu Sreshtha, Prasanth Lade, Subhashis Majumder
Research Collection School Of Computing and Information Systems
Linus’ Law reflects on a key characteristic of open source software development: developers’ tendency to closely work together in the bug resolution process. In this paper we empirically examine Linus’ Law using a data-set of 1,000+ Android bugs, owned by 70+ developers. Our results indicate that encouraging developers to work closely with one another has nuanced implications; while one form of contact may help reduce bug resolution time, another form can have quite the opposite effect. We present statistically significant evidence in support of our results and discuss their relevance at the individual and organizational levels.
On Understanding Diffusion Dynamics Of Patrons At A Theme Park, Jiali Du, Akshat Kumar, Pradeep Reddy Varakantham
On Understanding Diffusion Dynamics Of Patrons At A Theme Park, Jiali Du, Akshat Kumar, Pradeep Reddy Varakantham
Research Collection School Of Computing and Information Systems
In this work, we focus on the novel application of learning the diffusion dynamics of visitors among attractions at a large theme park using only aggregate information about waiting times at attractions. Main contributions include formulating optimisation models to compute diffusion dynamics. We also developed algorithm capable of dealing with noise in the data to populate parameters in the optimization model. We validated our approach using cross validation on a real theme park data set. Our approach provides an accuracy of about 80$% for popular attractions, providing solid empirical support for our diffusion models.
Canaries In The Urban Data Mine: Analytics For Smarter City Life, Robert J. Kauffman
Canaries In The Urban Data Mine: Analytics For Smarter City Life, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
Technology-based sensors and data analytics have created unprecendented levels of informedness for consumers, corporations, the public and government agencies. The information they generated provides a basis for smarter cities and more sustainable urban living.
Physio@Home: Design Explorations To Support Movement Guidance, Richard Tang, Hesam Alizadeh, Anthony Tang, Scott Bateman, Joaquim A.P. Jorge
Physio@Home: Design Explorations To Support Movement Guidance, Richard Tang, Hesam Alizadeh, Anthony Tang, Scott Bateman, Joaquim A.P. Jorge
Research Collection School Of Computing and Information Systems
Patients typically undergo physiotherapy with the help of a physiotherapist who teaches, guides, and corrects the patients as they perform exercises. It would be nice if people could repeat these exercises at home, potentially improving their recovery rate. However, without guidance and/or corrective feedback from a physiotherapist, the patient will not know whether they are doing their exercises correctly. To address this problem, we implemented a prototype that guides patients through pre-recorded exercise movements using visual guides overlaid atop a mirror-view of the patient on a wall-mounted display. We conducted informal evaluations and pilot studies to assess our prototype and …
On Coordinating Pervasive Persuasive Agents, Budhitama Subagdja, Ah-Hwee Tan
On Coordinating Pervasive Persuasive Agents, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
There is a growing interest in applying multiagent systems for smart-home environment supporting self-caring elderly. In this paper we investigate situations and conditions for coordination for such kind of system. We specify a high level architecture of it based on the notions of beliefs, desires, and intentions for both individual and group behavior of the agents including the human occupant's. The framework enables flexible coordinations among loosely-coupled heterogeneous agents that converse with the user. This work is conducted towards producing a coordination framework for agents and people in such a kind of smart-home environment as mentioned.