Computer Sciences Commons^™

Starcraft Ii In-Game Action Lists, Gong Wei, Ee Peng Lim, Achananuparp Palakorn, Feida Zhu, David Lo, Freddy Chua

SMU Research Data

1732 event logs of actions performed by players in Starcraft II public replays downloaded from GameReplays.org.

The Data Set consists of 1732 log files (Size: 55 MB) compressed into a Zip archive (Size: 9.3 MB).

This dataset has accumulated 267 downloads from 19 July 2012 to 2 Nov 2017 before being transferred to another collection.

Old URL: http://ink.library.smu.edu.sg/data/1/

An Evolutionary Search Paradigm That Learns With Past Experiences, Liang Feng, Yew-Soon Ong, Ivor Tsang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

A major drawback of evolutionary optimization approaches in the literature is the apparent lack of automated knowledge transfers and reuse across problems. Particularly, evolutionary optimization methods generally start a search from scratch or ground zero state, independent of how similar the given new problem of interest is to those optimized previously. In this paper, we present a study on the transfer of knowledge in the form of useful structured knowledge or latent patterns that are captured from previous experiences of problem-solving to enhance future evolutionary search. The essential contributions of our present study include the meme learning and meme selection …

More Of A Receiver Than A Giver: Why Do People Unfollow In Twitter?, Haewoon Kwak, Sue Moon, Wonjae Lee

Research Collection School Of Computing and Information Systems

We propose a logistic regression model taking into ac- count two analytically different sets of factors–structure and action. The factors include individual, dyadic, and triadic properties between ego and alter whose tie breakup is under consideration. From the fitted model using a large-scale data, we discover 5 structural and 7 actional variables to have significant explanatory power for unfollow. One unique finding from our quantitative analysis is that people appreciate receiving acknowl- edgements from others even in virtually unilateral com- munication relationships and are less likely to unfollow them: people are more of a receiver than a giver.

Aligning Images In The Wild, Wen-Yan Lin, Linlin Liu, Yasuyuki Matsushita, Kok-Lim Low, Siying Liu

Research Collection School Of Computing and Information Systems

Aligning image pairs with significant appearance change is a long standing computer vision challenge. Much of this problem stems from the local patch descriptors’ instability to appearance variation. In this paper we suggest this instability is due less to descriptor corruption and more the difficulty in utilizing local information to canonically define the orientation (scale and rotation) at which a patch’s descriptor should be computed. We address this issue by jointly estimating correspondence and relative patch orientation, within a hierarchical algorithm that utilizes a smoothly varying parameterization of geometric transformations. By collectively estimating the correspondence and orientation of all the …

Where Should The Bugs Be Fixed? More Accurate Information Retrieval-Based Bug Localization Based On Bug Reports, Jian Zhou, Hongyu Zhang, David Lo

Research Collection School Of Computing and Information Systems

For a large and evolving software system, the project team could receive a large number of bug reports. Locating the source code files that need to be changed in order to fix the bugs is a challenging task. Once a bug report is received, it is desirable to automatically point out to the files that developers should change in order to fix the bug. In this paper, we propose BugLocator, an information retrieval based method for locating the relevant files for fixing a bug. BugLocator ranks all files based on the textual similarity between the initial bug report and the …

Exerlink: Enabling Pervasive Social Exergames With Heterogeneous Exercise Devices, Taiwoo Park, Inseok Hwang, Uichin Lee, Sunghoon Ivan Lee, Chungkuk Yoo, Youngki Lee, Hyukjae Jang, Sungwon Peter Choe, Souneil Park, Junehwa Song

Research Collection School Of Computing and Information Systems

We envision that diverse social exercising games, or exergames, will emerge, featuring much richer interactivity with immersive game play experiences. Further, the recent advances of mobile devices and wireless networking will make such social engagement more pervasive - people carry portable exergame devices (e.g., jump ropes) and interact with remote users anytime, anywhere. Towards this goal, we explore the potential of using heterogeneous exercise devices as game controllers for a multi-player social exergame; e.g., playing a boat paddling game with two remote exercisers (one with a jump rope, and the other with a treadmill). In this paper, we propose a …

Workitemexplorer: Visualizing Software Development Tasks Using An Interactive Exploration Environment, Christoph Treude, Patrick Gorman, Lars Grammel, Margaret-Anne Storey

Research Collection School Of Computing and Information Systems

This demo introduces WorkItemExplorer, an interactive environment to visually explore data from software development tasks. WorkItemExplorer enables developers and managers to investigate activity and correlations in their task management system by making data exploration flexible and interactive, and by utilizing multiple coordinated views. Our preliminary evaluation shows that WorkItemExplorer is able to answer questions that developers ask, while also enabling them to gain new insights through the free exploration of data.

Semi-Supervised Hierarchical Clustering For Personalized Web Image Organization, Lei Meng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Existing efforts on web image organization usually transform the task into surrounding text clustering. However, Current text clustering algorithms do not address the problem of insufficient statistical information for image representation and noisy tags which greatly decreases the clustering performance while increases the computational cost. In this paper, we propose a two-step semi-supervised hierarchical clustering algorithm, Personalized Hierarchical Theme-based Clustering (PHTC), for web image organization. In the first step, the Probabilistic Fusion ART (PF-ART) is proposed for grouping semantically similar images and simultaneously learning the probabilistic distribution of tag occurrence for mining the key tags/topics of clusters. In this way, …

Mobicon: Mobile Context Monitoring Platform: Incorporating Context-Awareness To Smartphone-Centric Personal Sensor Networks, Youngki Lee, Younghyun Ju, Chuihong Min, Jihun Yu, Junehwa Song

Research Collection School Of Computing and Information Systems

In this demonstration, we will show MobiCon, a context monitoring platform; it runs over smartphones and sensor OSs, and facilitates development and deployment of everyday context-aware applications. For many years, lots of research efforts have been made in building low-cost, yet effective sensor networks for various application domains such as structural health monitoring of bridges, disaster recovery, automated ventilation of buildings. Integration of sensors into smartphones and the advent of wearable devices open a new opportunity for mobile applications to leverage in-situ user contexts such as his/her location, activity, social relationship, health status. In recent studies of mobile and pervasive …

When A Friend In Twitter Is A Friend In Life, Wei Xie, Cheng Li, Feida Zhu, Ee-Peng Lim, Xueqing Gong

Research Collection School Of Computing and Information Systems

Twitter is a fast-growing online social network service (SNS) where users can "follow" any other user to receive his or her mini-blogs which are called "tweets". In this paper, we study the problem of identifying a user's off-line real-life social community, which we call the user'sTwitter off-line community, purely from examining Twitter network structure. Based on observations from our user-verified Twitter data and results from previous works, we propose three principles about Twitter off-line communities. Incorporating these principles, we develop a novel algorithm to iteratively discover the Twitter off-line community based on a new way of measuring user closeness. According …

Self-Organizing Neural Networks For Learning Air Combat Maneuvers, Teck-Hou Teng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper reports on an agent-oriented approach for the modeling of adaptive doctrine-equipped computer generated force (CGF) using a commercial-grade simulation platform known as CAE STRIVECGF. A self- organizing neural network is used for the adaptive CGF to learn and generalize knowledge in an online manner during the simulation. The challenge of defining the state space and action space and the lack of domain knowledge to initialize the adaptive CGF are addressed using the doctrine used to drive the non-adaptive CGF. The doctrine contains a set of specialized knowledge for conducting 1-v-1 dogfights. The hierarchical structure and symbol representation of …

Energy-Efficient Continuous Activity Recognition On Mobile Phones: An Activity-Adaptive Approach, Zhixian Yan, Vigneshwaran Subbaraju, Dipanjan Chakraborty, Archan Misra, Karl Aberer

Research Collection School Of Computing and Information Systems

Power consumption on mobile phones is a painful obstacle towards adoption of continuous sensing driven applications, e.g., continuously inferring individual’s locomotive activities (such as ‘sit’, ‘stand’ or ‘walk’) using the embedded accelerometer sensor. To reduce the energy overhead of such continuous activity sensing, we first investigate how the choice of accelerometer sampling frequency & classification features affects, separately for each activity, the “energy overhead” vs. “classification accuracy” tradeoff. We find that such tradeoff is activity specific. Based on this finding, we introduce an activity-sensitive strategy (dubbed “A3R” – Adaptive Accelerometer-based Activity Recognition) for continuous activity recognition, where the choice of …

A New Framework For Privacy Of Rfid Path Authentication, Shaoying Cai, Robert H. Deng, Yingjiu Li, Yunlei Zhao

Research Collection School Of Computing and Information Systems

RFID-based path authentication enables supply chain managers to verify the exact path that a tag has taken. In this paper, we introduce a new oracle Move that models a tag's movement along a designed or an arbitrary path in a supply chain. With this oracle, we refine the existing security and privacy notions for RFID-based path authentication. In addition, we propose a new privacy notion, called path privacy, for RFID-based path authentication. Our privacy notion captures the privacy of both tag identity and path information in a single game. Compared to existing two-game based privacy notions, it is more rigorous, …

Active Malware Analysis Using Stochastic Games, Simon Williamson, Pradeep Reddy Varakantham, Debin Gao, Chen Hui Ong

Research Collection School Of Computing and Information Systems

Cyber security is increasingly important for defending computer systems from loss of privacy or unauthorised use. One important aspect is threat analysis - how does an attacker infiltrate a system and what do they want once they are inside. This paper considers the problem of Active Malware Analysis, where we learn about the human or software intruder by actively interacting with it with the goal of learning about its behaviours and intentions, whilst at the same time that intruder may be trying to avoid detection or showing those behaviours and intentions. This game-theoretic active learning is then used to obtain …

A Novel Unbalanced Tree Structure For Low-Cost Authentication Of Streaming Content On Mobile And Sensor Devices, Thivya Kandappu, Vijay Sivaraman, Roksana Boreli

Research Collection School Of Computing and Information Systems

We consider stored content being streamed to a resource-poor device (such as a sensor node or a mobile phone), and address the issue of authenticating such content in realtime at the receiver. Per-packet digital signatures incur high computational cost, while per-block signatures impose high delays. A Merkle hash tree combines the benefits of the two by having a single signature per-block (at the root of the tree), while allowing immediate per-packet verification by following a hash-path logarithmic in the number of packets. In this paper we explore how the structure of the Merkle tree can be adapted to improve playback …

Resource-Aware Video Multicasting Via Access Gateways In Wireless Mesh Networks, Wanqing Tu, Cormac Sreenan, Chun Tung Chou, Archan Misra, Sanjay Jha

Research Collection School Of Computing and Information Systems

This paper studies video multicasting in large scale areas using wireless mesh networks. The focus is on the use of Internet access gateways that allow a choice of alternative routes to avoid potentially lengthy and low capacity multi-hop wireless paths. A set of heuristic-based algorithms are described that together aim to maximize network capacity: the two-tier integrated architecture algorithm, the weighted gateway uploading algorithm, the link controlled routing tree algorithm, and the dynamic group management algorithm. These algorithms use different approaches to arrange nodes involved in video multicasting into a clustered and two-tier integrated architecture in which network protocols can …

Adaptive Data Acquisition Strategies For Energy-Efficient, Smartphone-Based, Continuous Processing Of Sensor Streams, Lipyeow Lim, Archan Misra, Tianli Mo

Research Collection School Of Computing and Information Systems

There is a growing interest in applications that utilize continuous sensing of individual activity or context, via sensors embedded or associated with personal mobile devices (e.g., smartphones). Reducing the energy overheads of sensor data acquisition and processing is essential to ensure the successful continuous operation of such applications, especially on battery-limited mobile devices. To achieve this goal, this paper presents a framework, called ACQUA, for ‘acquisition-cost’ aware continuous query processing. ACQUA replaces the current paradigm, where the data is typically streamed (pushed) from the sensors to the one or more smartphones, with a pull-based asynchronous model, where a smartphone retrieves …

Comon: Cooperative Ambience Monitoring Platform With Continuity And Benefit Awareness, Youngki Lee, Younghyun Ju, Chulhong Min, Seungwoo Kang, Inseok Hwang, Junehwa Song

Research Collection School Of Computing and Information Systems

Mobile applications that sense continuously, such as location monitoring, are emerging. Despite their usefulness, their adoption in real-world deployment situations has been extremely slow. Many smartphone users are turned away by the drastic battery drain caused by continuous sensing and processing. Also, the extractable contexts from the phone are quite limited due to its position and sensing modalities. In this paper, we propose CoMon, a novel cooperative ambience monitoring platform, which newly addresses the energy problem through opportunistic cooperation among nearby mobile users. To maximize the benefit of cooperation, we develop two key techniques, (1) continuity-aware cooperator detection and (2) …

Identifying Linux Bug Fixing Patches, Yuan Tian, Julia Lawall, David Lo

Research Collection School Of Computing and Information Systems

In the evolution of an operating system there is a continuing tension between the need to develop and test new features, and the need to provide a stable and secure execution environment to users. A compromise, adopted by the developers of the Linux kernel, is to release new versions, including bug fixes and new features, frequently, while maintaining some older “longterm” versions. This strategy raises the problem of how to identify bug fixing patches that are submitted to the current version but should be applied to the longterm versions as well. The current approach is to rely on the individual …

Stochastic Dominance In Stochastic Dcops For Risk-Sensitive Applications, Nguyen Duc Thien, William Yeoh, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Distributed constraint optimization problems (DCOPs) are well-suited for modeling multi-agent coordination problems where the primary interactions are between local subsets of agents. However, one limitation of DCOPs is the assumption that the constraint rewards are without uncertainty. Researchers have thus extended DCOPs to Stochastic DCOPs (SDCOPs), where rewards are sampled from known probability distribution reward functions, and introduced algorithms to find solutions with the largest expected reward. Unfortunately, such a solution might be very risky, that is, very likely to result in a poor reward. Thus, in this paper, we make three contributions: (1) we propose a stricter objective for …

Distributed Incomplete Pattern Matching Via A Novelweighted Bloom Filter, Siyuan Liu, Lei Kang, Lei Chen, Lionel Ni

Research Collection School Of Computing and Information Systems

In this paper, we first propose a very interesting and practical problem, pattern matching in a distributed mobile environment. Pattern matching is a well-known problem and extensive research has been conducted for performing effective and efficient search. However, previous proposed approaches assume that data are centrally stored, which is not the case in a mobile environment (e.g., mobile phone networks), where one person’s pattern could be separately stored in a number of different stations, and such a local pattern is incomplete compared with the global pattern. A simple solution to pattern matching over a mobile environment is to collect all …

Memory Formation, Consolidation, And Forgetting In Learning Agents, Budhitama Subagdja, Wenwen Wang, Ah-Hwee Tan, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Memory enables past experiences to be remembered and acquired as useful knowledge to support decision making, especially when perception and computational resources are limited. This paper presents a neuropsychological-inspired dual memory model for agents, consisting of an episodic memory that records the agent’s experience in real time and a semantic memory that captures factual knowledge through a parallel consolidation process. In addition, the model incorporates a natural forgetting mechanism that prevents memory overloading by removing transient memory traces. Our experimental study based on a real-time first-person-shooter video game has indicated that the memory consolidation and forgetting processes are not only …

A Biologically-Inspired Affective Model Based On Cognitive Situational Appraisal, Feng Shu, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Although various emotion models have been proposed based on appraisal theories, most of them focus on designing specific appraisal rules and there is no unified framework for emotional appraisal. Moreover, few existing emotion models are biologically-inspired and are inadequate in imitating emotion process of human brain. This paper proposes a bio-inspired computational model called Cognitive Regulated Affective Architecture (CRAA), inspired by the cognitive regulated emotion theory and the network theory of emotion. This architecture is proposed by taking the following positions: (1) Cognition and emotion are not separated but interacted systems; (2) The appraisal of emotion depends on and should …

Memory Formation, Consolidation, And Forgetting In Learning Agents, Budhitama Susnagdja, Wenwen Wang, Ah-Hwee Tan, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Memory enables past experiences to be remembered and acquired as useful knowledge to support decision making, especially when perception and computational resources are limited. This paper presents a neuropsychological- inspired dual memory model for agents, consisting of an episodic memory that records the agent's experience in real time and a semantic memory that captures factual knowledge through a parallel consolidation process. In addition, the model incorporates a natural forgetting mechanism that prevents memory overloading by removing transient memory traces. Our experimental study based on a real-time first-person-shooter video game has indicated that the memory consolidation and forgetting processes are not …

Fast Semantic Diffusion For Large-Scale Context-Based Image And Video Annotation, Yu-Gang Jiang, Qi Dai, Jun Wang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Exploring context information for visual recognition has recently received significant research attention. This paper proposes a novel and highly efficient approach, which is named semantic diffusion, to utilize semantic context for large-scale image and video annotation. Starting from the initial annotation of a large number of semantic concepts (categories), obtained by either machine learning or manual tagging, the proposed approach refines the results using a graph diffusion technique, which recovers the consistency and smoothness of the annotations over a semantic graph. Different from the existing graph-based learning methods that model relations among data samples, the semantic graph captures context by …

Sammple: Detecting Semantic Indoor Activities In Practical Settings Using Locomotive Signatures, Zhixian Yan, Dipanjan Chakraborty, Archan Misra, Hoyoung Jeung, Karl Aberer

Research Collection School Of Computing and Information Systems

We analyze the ability of mobile phone-generated accelerometer data to detect high-level (i.e., at the semantic level) indoor lifestyle activities, such as cooking at home and working at the workplace, in practical settings. We design a 2-T ier activity extraction framework (called SAMMPLE) for our purpose. Using this, we evaluate discriminatory power of activity structures along the dimension of statistical features and after a transformation to a sequence of individual locomotive micro-activities (e.g. sitting or standing). Our findings from 152 days of real-life behavioral traces reveal that locomotive signatures achieve an average accuracy of 77.14%, an improvement of 16.37% over …

Active Refinement Of Clone Anomaly Reports, Lucia, David Lo, Lingxiao Jiang, Aditya Budi

Research Collection School Of Computing and Information Systems

Software clones have been widely studied in the recent literature and shown useful for finding bugs because inconsistent changes among clones in a clone group may indicate potential bugs. However, many inconsistent clone groups are not real bugs (true positives). The excessive number of false positives could easily impede broad adoption of clone-based bug detection approaches. In this work, we aim to improve the usability of clone-based bug detection tools by increasing the rate of true positives found when a developer analyzes anomaly reports. Our idea is to control the number of anomaly reports a user can see at a …

What Does Software Engineering Community Microblog About?, Yuan Tian, Palakorn Achananuparp, Ibrahim Nelman Lubis, David Lo, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Microblogging is a new trend to communicate and to disseminate information. One microblog post could potentially reach millions of users. Millions of microblogs are generated on a daily basis on popular sites such as Twitter. The popularity of microblogging among programmers, software engineers, and software users has also led to their use of microblogs to communicate software engineering issues apart from using emails and other traditional communication channels.Understanding how millions of users use microblogs in software engineering related activities would shed light on ways we could leverage the fast evolving microblogging content to aid software development efforts. In this work, …

Are Faults Localizable?, Lucia Lucia, Ferdian Thung, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Many fault localization techniques have been proposed to facilitate debugging activities. Most of them attempt to pinpoint the location of faults (i.e., localize faults) based on a set of failing and correct executions and expect debuggers to investigate a certain number of located program elements to find faults. These techniques thus assume that faults are localizable, i.e., only one or a few lines of code that are close to one another are responsible for each fault. However, in reality, are faults localizable? In this work, we investigate hundreds of real faults in several software systems, and find that many faults …

Modeling Diffusion In Social Networks Using Network Properties, Duc Minh Luu, Ee Peng Lim, Tuan Anh Hoang, Chong Tat Freddy Chua

Research Collection School Of Computing and Information Systems

"Diffusion of items occurs in social networks due to spreading of items through word of mouth and exogenous factors. These items may be news, products, videos, advertisements or contagious viruses. When a user purchases or consumes one of such items, we say that she adopts the item and she becomes an item adopter. Previous research has studied diffusion process at both the macro and micro levels. The former models the number of item adopters in the diffusion process while the latter determines which individuals adopt item. Both macro and micro level models have their merits and limitations. In this paper, …