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Effect Of Business Intelligence And It Infrastructure Flexibility On Organizational Agility, Xiaofeng Chen, Keng Siau
Effect Of Business Intelligence And It Infrastructure Flexibility On Organizational Agility, Xiaofeng Chen, Keng Siau
Research Collection School Of Computing and Information Systems
There is a growing use of business intelligence (BI) for better management decisions in different industries. However, empirical studies on BI are still scarce in academic research. This research investigates BI from an organizational agility perspective. Organizational agility is the ability to sense and respond to market opportunities and threats with speed. Drawing on systems theory and literature on organizational agility, business intelligence, and IT infrastructure flexibility, we hypothesize that BI use and IT infrastructure flexibility are two major antecedents to organizational agility. We developed a research model to examine the effect of BI use and IT infrastructure flexibility on …
Critical Success Factors Of Location-Based Services, Natalie J. P. Chin, Keng Siau
Critical Success Factors Of Location-Based Services, Natalie J. P. Chin, Keng Siau
Research Collection School Of Computing and Information Systems
Location-based services evolved with the advancement in mobile technology and wireless technology. Researchers have studied location-based services in terms of privacy, trust, and user acceptance. Statistics suggest the percentage of location-based services users is still relatively low. Therefore, the main objective of this study was to gain a comprehensive and holistic understanding of the critical success factors of location-based services. The electronic brainstorming approach was used to gather the opinions of an expert group of practitioners, researchers, and users on the critical success factors of location-based services. Through grouping similar factors together based on past literature, 15 categories of critical …
Fame, Soft Flock Formation Control For Collective Behavior Studies And Rapid Games Development, Choon Sing Ho, Yew-Soon Ong, Xianshun Chen, Ah-Hwee Tan
Fame, Soft Flock Formation Control For Collective Behavior Studies And Rapid Games Development, Choon Sing Ho, Yew-Soon Ong, Xianshun Chen, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
We present FAME, a comprehensive C# software library package providing soft formation control for large flocks of agents. While many existing available libraries provide means to create flocks of agent equipped with simple steering behavior, none so far, to the best of our knowledge, provides an easy and hassle free approach to control the formation of the flock. Here, besides the basic flocking mechanisms, FAME provides an extensive range of advanced features that gives enhanced soft formation control over multiple flocks. These soft formation features include defining flocks in any user-defined formation, automated self-organizing agent within formation, manipulating formation shape …
Community-Based Classification Of Noun Phrases In Twitter, Freddy Chong Tat Chua, William W. Cohen, Justin Betterridge, Ee-Peng Lim
Community-Based Classification Of Noun Phrases In Twitter, Freddy Chong Tat Chua, William W. Cohen, Justin Betterridge, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Many event monitoring systems rely on counting known keywords in streaming text data to detect sudden spikes in frequency. But the dynamic and conversational nature of Twitter makes it hard to select known keywords for monitoring. Here we consider a method of automatically finding noun phrases (NPs) as keywords for event monitoring in Twitter. Finding NPs has two aspects, identifying the boundaries for the subsequence of words which represent the NP, and classifying the NP to a specific broad category such as politics, sports, etc. To classify an NP, we define the feature vector for the NP using not just …
Semi-Automated Verification Of Defense Against Sql Injection In Web Applications, Kaiping Liu, Hee Beng Kuan Tan, Lwin Khin Shar
Semi-Automated Verification Of Defense Against Sql Injection In Web Applications, Kaiping Liu, Hee Beng Kuan Tan, Lwin Khin Shar
Research Collection School Of Computing and Information Systems
Recent reports reveal that majority of the attacks to Web applications are input manipulation attacks. Among these attacks, SQL injection attack malicious input is submitted to manipulate the database in a way that was unintended by the applications' developers is one such attack. This paper proposes an approach for assisting to code verification process on the defense against SQL injection. The approach extracts all such defenses implemented in code. With the use of the proposed approach, developers, testers or auditors can then check the defenses extracted from code to verify their adequacy. We have evaluated the feasibility, effectiveness, and usefulness …
An Automated Pathological Class Level Annotation System For Volumetric Brain Images, Thien Anh Dinh, Tomi Silander, C. C. Tchoyoson Lim, Tze-Yun Leong
An Automated Pathological Class Level Annotation System For Volumetric Brain Images, Thien Anh Dinh, Tomi Silander, C. C. Tchoyoson Lim, Tze-Yun Leong
Research Collection School Of Computing and Information Systems
We introduce an automated, pathological class level annotation system for medical volumetric brain images. While much of the earlier work has mainly focused on annotating regions of interest in medical images, our system does not require annotated region level training data nor assumes perfect segmentation results for the regions of interest; the time and effort needed for acquiring training data are hence significantly reduced. This capability of handling high-dimensional noisy data, however, poses additional technical challenges, since statistical estimation of models for such data is prone to over-fitting. We propose a framework that combines a regularized logistic regression method and …
Knowledge-Driven Autonomous Commodity Trading Advisor, Yee Pin Lim, Shih-Fen Cheng
Knowledge-Driven Autonomous Commodity Trading Advisor, Yee Pin Lim, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
The myth that financial trading is an art has been mostly destroyed in the recent decade due to the proliferation of algorithmic trading. In equity markets, algorithmic trading has already bypass human traders in terms of traded volume. This trend seems to be irreversible, and other asset classes are also quickly becoming dominated by the machine traders. However, for asset that requires deeper understanding of physicality, like the trading of commodities, human traders still have significant edge over machines. The primary advantage of human traders in such market is the qualitative expert knowledge that requires traders to consider not just …
A Mechanism For Organizing Last-Mile Service Using Non-Dedicated Fleet, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau
A Mechanism For Organizing Last-Mile Service Using Non-Dedicated Fleet, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Unprecedented pace of urbanization and rising income levels have fueled the growth of car ownership in almost all newly formed megacities. Such growth has congested the limited road space and significantly affected the quality of life in these megacities. Convincing residents to give up their cars and use public transport is the most effective way in reducing congestion; however, even with sufficient public transport capacity, the lack of last-mile (from the transport hub to the destination) travel services is the major deterrent for the adoption of public transport. Due to the dynamic nature of such travel demands, fixed-size fleets will …
On Recommending Hashtags In Twitter Networks, Su Mon Kywe, Tuan-Anh Hoang, Ee Peng Lim, Feida Zhu
On Recommending Hashtags In Twitter Networks, Su Mon Kywe, Tuan-Anh Hoang, Ee Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
Twitter network is currently overwhelmed by massive amount of tweets generated by its users. To effectively organize and search tweets, users have to depend on appropriate hashtags inserted into tweets. We begin our research on hashtags by first analyzing a Twitter dataset generated by more than 150,000 Singapore users over a three-month period. Among several interesting findings about hashtag usage by this user community, we have found a consistent and significant use of new hashtags on a daily basis. This suggests that most hashtags have very short life span. We further propose a novel hashtag recommendation method based on collaborative …
Diffusion Of Software Features: An Exploratory Study, Ferdian Thung, David Lo, Lingxiao Jiang
Diffusion Of Software Features: An Exploratory Study, Ferdian Thung, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
New features are frequently proposed in many software libraries. These features include new methods, classes, packages, etc. These features are utilized in many open source and commercial software systems. Some of these features are adopted very quickly, while others take a long time to be adopted. Each feature takes much resource to develop, test, and document. Library developers and managers need to decide what feature to prioritize and what to develop next. As a first step to aid these stakeholders, we perform an exploratory study on the diffusion or rate of adoption of features in Java Development Kit (JDK) library. …
Scalable Malware Clustering Through Coarse-Grained Behavior Modeling, Mahinthan Chandramohan, Hee Beng Kuan Tan, Lwin Khin Shar
Scalable Malware Clustering Through Coarse-Grained Behavior Modeling, Mahinthan Chandramohan, Hee Beng Kuan Tan, Lwin Khin Shar
Research Collection School Of Computing and Information Systems
Anti-malware vendors receive several thousand new malware (malicious software) variants per day. Due to large volume of malware samples, it has become extremely important to group them based on their malicious characteristics. Grouping of malware variants that exhibit similar behavior helps to generate malware signatures more efficiently. Unfortunately, exponential growth of new malware variants and huge-dimensional feature space, as used in existing approaches, make the clustering task very challenging and difficult to scale. Furthermore, malware behavior modeling techniques proposed in the literature do not scale well, where malware feature space grows in proportion with the number of samples under examination. …
Action Disambiguation Analysis Using Normalized Google-Like Distance Correlogram, Qianru Sun, Hong Liu
Action Disambiguation Analysis Using Normalized Google-Like Distance Correlogram, Qianru Sun, Hong Liu
Research Collection School Of Computing and Information Systems
Classifying realistic human actions in video remains challenging for existing intro-variability and inter-ambiguity in action classes. Recently, Spatial-Temporal Interest Point (STIP) based local features have shown great promise in complex action analysis. However, these methods have the limitation that they typically focus on Bag-of-Words (BoW) algorithm, which can hardly discriminate actions’ ambiguity due to ignoring of spatial-temporal occurrence relations of visual words. In this paper, we propose a new model to capture this contextual relationship in terms of pairwise features’ co-occurrence. Normalized Google-Like Distance (NGLD) is proposed to numerically measuring this co-occurrence, due to its effectiveness in semantic correlation analysis. …
Audit Mechanisms For Provable Risk Management And Accountable Data Governance, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha
Audit Mechanisms For Provable Risk Management And Accountable Data Governance, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha
Research Collection School Of Computing and Information Systems
Organizations that collect and use large volumes of personal information are expected under the principle of accountable data governance to take measures to protect data subjects from risks that arise from inapproriate uses of this information. In this paper, we focus on a specific class of mechanisms—audits to identify policy violators coupled with punishments—that organizations such as hospitals, financial institutions, and Web services companies may adopt to protect data subjects from privacy and security risks stemming from inappropriate information use by insiders. We model the interaction between the organization (defender) and an insider (adversary) during the audit process as a …
Joint Topic Modeling For Event Summarization Across News And Social Media Streams, Wei Gao, Peng Li, Kareem Darwish
Joint Topic Modeling For Event Summarization Across News And Social Media Streams, Wei Gao, Peng Li, Kareem Darwish
Research Collection School Of Computing and Information Systems
Social media streams such as Twitter are regarded as faster first-hand sources of information generated by massive users. The content diffused through this channel, although noisy, provides important complement and sometimes even a substitute to the traditional news media reporting. In this paper, we propose a novel unsupervised approach based on topic modeling to summarize trending subjects by jointly discovering the representative and complementary information from news and tweets. Our method captures the content that enriches the subject matter by reinforcing the identification of complementary sentence-tweet pairs. To valuate the complementarity of a pair, we leverage topic modeling formalism by …
Snap-And-Ask: Answering Multimodal Question By Naming Visual Instance, Wei Zhang, Lei Pang, Chong-Wah Ngo
Snap-And-Ask: Answering Multimodal Question By Naming Visual Instance, Wei Zhang, Lei Pang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
In real-life, it is easier to provide a visual cue when asking a question about a possibly unfamiliar topic, for example, asking the question, “Where was this crop circle found?”. Providing an image of the instance is far more convenient than texting a verbose description of the visual properties, especially when the name of the query instance is not known. Nevertheless, having to identify the visual instance before processing the question and eventually returning the answer makes multimodal question-answering technically challenging. This paper addresses the problem of visual-totext naming through the paradigm of answering-by-search in a two-stage computational framework, which …
Microblog Search And Filtering With Time Sensitive Feedback And Thresholding Based On Bm25, Wei Gao, Zhongyu Wei, Kam-Fai Wong
Microblog Search And Filtering With Time Sensitive Feedback And Thresholding Based On Bm25, Wei Gao, Zhongyu Wei, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Microblogs such as Twitter are considered faster first-hand sources of information with many real-time fashions. We report our work in the real-time adhoc search and filtering tasks of TREC 2012 microblog track. Our system is built based on the traditional BM25 relevance model, in which specific techniques are tried out to respond to the ne.ed of frnding relevant tweets, ln thc real-time adhoc task, we applied a peak detection algorithm for the process of blind feedback, We also tried to automatically combine the search results of multiple retrieval techniques. In the real-time filtering pilot task, we examine the effectiveness of …
An Analytical And Experimental Comparison Of Csp Extensions And Tools, Ling Shi, Yang Liu, Jun Sun, Jin Song Dong, Gustavo Carvalho
An Analytical And Experimental Comparison Of Csp Extensions And Tools, Ling Shi, Yang Liu, Jun Sun, Jin Song Dong, Gustavo Carvalho
Research Collection School Of Computing and Information Systems
Communicating Sequential Processes (CSP) has been widely applied to modeling and analyzing concurrent systems. There have been considerable efforts on enhancing CSP by taking data and other system aspects into account. For instance, CSP M combines CSP with a functional programming language whereas CSP# integrates high-level CSP-like process operators with low-level procedure code. Little work has been done to systematically compare these CSP extensions, which may have subtle and substantial differences. In this paper, we compare CSP M and CSP# not only on their syntax, but also operational semantics as well as their supporting tools such as FDR, ProB, and …
Poster Abstract: Towards Crowd-Aware Sensing Platform For Metropolitan Environments, Saumay Pushp, Chulhong Min, Youngki Lee, Chi Harold Liu, Junehwa Song
Poster Abstract: Towards Crowd-Aware Sensing Platform For Metropolitan Environments, Saumay Pushp, Chulhong Min, Youngki Lee, Chi Harold Liu, Junehwa Song
Research Collection School Of Computing and Information Systems
In this paper, we propose an in-situ Crowd-aware Sensing Platform, called "CrowdMon", which envisions the cooperation among mobile users in highly crowded urban areas such as metro and square. CrowdMon establishes a spontaneous connection from co-located users in a semantic proximity and enables them to share contextual information such as location, ambient music, and mood of places. To the best of our knowledge, CrowdMon is the first attempt to support crowd-aware services at a platform level. We show interesting use cases of CrowdMon and an initial system design to realize the crowd-based context sharing.
Mining Coherent Anomaly Collections On Web Data, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang
Mining Coherent Anomaly Collections On Web Data, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
The recent boom of weblogs and social media has attached increasing importance to the identification of suspicious users with unusual behavior, such as spammers or fraudulent reviewers. A typical spamming strategy is to employ multiple dummy accounts to collectively promote a target, be it a URL or a product. Consequently, these suspicious accounts exhibit certain coherent anomalous behavior identifiable as a collection. In this paper, we propose the concept of Coherent Anomaly Collection (CAC) to capture this kind of collections, and put forward an efficient algorithm to simultaneously find the top-K disjoint CACs together with their anomalous behavior patterns. Compared …
Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou
Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou
Research Collection School Of Computing and Information Systems
Multimedia contents such as images and videos are widely used in social network sites nowadays. Sina Weibo, a Chinese microblogging service, is one of the first microblog platforms to incorporate multimedia content sharing features. This work provides statistical analysis on how multimedia contents are produced, consumed, and propagated in Sina Weibo. Based on 230 million tweets and 1.8 million user profiles in Sina Weibo, we study the impact of multimedia contents on the popularity of both users and tweets as well as tweet life span. Our preliminary study shows that multimedia tweets dominant pure text ones in SinaWeibo. Multimedia contents …
Automatic Generation Of Provably Correct Embedded Systems, Shang-Wei Lin, Yang Liu, Pao-Ann Hsiung, Jun Sun, Jin Song Dong
Automatic Generation Of Provably Correct Embedded Systems, Shang-Wei Lin, Yang Liu, Pao-Ann Hsiung, Jun Sun, Jin Song Dong
Research Collection School Of Computing and Information Systems
With the demand for new and complicated features, embedded systems are becoming more and more difficult to design and verify. Even if the design of a system is verified, how to guarantee the consistency between the design and its implementation remains a big issue. As a solution, we propose a framework that can help a system designer to model his or her embedded system using a high-level modeling language, verify the design of the system, and automatically generate executable software codes whose behavior semantics are consistent with that of the high-level model. We use two case studies to demonstrate the …
More Anti-Chain Based Refinement Checking, Ting Wang, Songzheng Song, Jun Sun, Yang Liu, Jin Song Dong, Xinyu Wang, Shanping Li
More Anti-Chain Based Refinement Checking, Ting Wang, Songzheng Song, Jun Sun, Yang Liu, Jin Song Dong, Xinyu Wang, Shanping Li
Research Collection School Of Computing and Information Systems
Refinement checking plays an important role in system verification. It establishes properties of an implementation by showing a refinement relationship between the implementation and a specification. Recently, it has been shown that anti-chain based approaches increase the efficiency of trace refinement checking significantly. In this work, we study the problem of adopting anti-chain for stable failures refinement checking, failures-divergence refinement checking and probabilistic refine checking (i.e., a probabilistic implementation against a non-probabilistic specification). We show that the first two problems can be significantly improved, because the state space of the product model may be reduced dramatically. Though applying anti-chain for …
A Generalized Cluster Centroid Based Classifier For Text Categorization, Guansong Pang, Shengyi Jiang
A Generalized Cluster Centroid Based Classifier For Text Categorization, Guansong Pang, Shengyi Jiang
Research Collection School Of Computing and Information Systems
In this paper, a Generalized Cluster Centroid based Classifier (GCCC) and its variants for text categorization are proposed by utilizing a clustering algorithm to integrate two wellknown classifiers, i.e., the K-nearest-neighbor (KNN) classifier and the Rocchio classifier. KNN, a lazy learning method, suffers from inefficiency in online categorization while achieving remarkable effectiveness. Rocchio, which has efficient categorization performance, fails to obtain an expressive categorization model due to its inherent linear separability assumption. Our proposed method mainly focuses on two points: one point is that we use a clustering algorithm to strengthen the expressiveness of the Rocchio model; another one is …
Cross-View Graph Embedding, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, X. Chen
Cross-View Graph Embedding, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, X. Chen
Research Collection School Of Computing and Information Systems
Recently, more and more approaches are emerging to solve the cross-view matching problem where reference samples and query samples are from different views. In this paper, inspired by Graph Embedding, we propose a unified framework for these cross-view methods called Cross-view Graph Embedding. The proposed framework can not only reformulate most traditional cross-view methods (e.g., CCA, PLS and CDFE), but also extend the typical single-view algorithms (e.g., PCA, LDA and LPP) to cross-view editions. Furthermore, our general framework also facilitates the development of new cross-view methods. In this paper, we present a new algorithm named Cross-view Local Discriminant Analysis (CLODA) …
An Empirical Study Of Bugs In Machine Learning Systems, Ferdian Thung, Shaowei Wang, David Lo, Lingxiao Jiang
An Empirical Study Of Bugs In Machine Learning Systems, Ferdian Thung, Shaowei Wang, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Many machine learning systems that include various data mining, information retrieval, and natural language processing code and libraries have being used in real world applications. Search engines, internet advertising systems, product recommendation systems are sample users of these algorithm intensive code and libraries. Machine learning code and toolkits have also been used in many recent studies on software mining and analytics that aim to automate various software engineering tasks. With the increasing number of important applications of machine learning systems, the reliability of such systems is also becoming increasingly important. A necessary step for ensuring reliability of such systems is …
An Improved Authentication Scheme For H.264/Svc And Its Performance Evaluation Over Non-Stationary Wireless Mobile Networks, Yifan Zhao, Swee-Won Lo, Robert H. Deng, Xuhua Ding
An Improved Authentication Scheme For H.264/Svc And Its Performance Evaluation Over Non-Stationary Wireless Mobile Networks, Yifan Zhao, Swee-Won Lo, Robert H. Deng, Xuhua Ding
Research Collection School Of Computing and Information Systems
In this paper, a bit stream-based authentication scheme for H.264/Scalable Video Coding (SVC) is proposed. The proposed scheme seamlessly integrates cryptographic algorithms and erasure correction codes (ECCs) to SVC video streams such that the authenticated streams are format compliant with the SVC specifications and preserve the three dimensional scalability (i. e., spatial, quality and temporal) of the original streams. We implement our scheme on a smart phone and study its performance over a realistic bursty packet-lossy wireless mobile network. Our analysis and experimental results show that the scheme achieves very high verification rates with lower communication overhead and much smaller …
Science And Technology Parks As An Open Innovation Catalyst For Valorization, Arcot Desai Narasimhalu
Science And Technology Parks As An Open Innovation Catalyst For Valorization, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
This paper sets out by reviewing the key elements of a Science or Technology Park in the context of open innovation. This is followed by a broad scan of Science and Technology Park activity in South and South East Asia. The paper proceeds to discuss Singapore’s continuous efforts to create new Science and Technology park models and presents a new approach the Singapore Management University has pursued for catalyzing valorization. Insights into and recommendations on key issues related to intellectual property, licensing and venture capital that would be of interest to any Science Park are presented later.
Fast And Accurate Psd Matrix Estimation By Row Reduction, Hiroshi Kuwajima, Takashi Washio, Ee Peng Lim
Fast And Accurate Psd Matrix Estimation By Row Reduction, Hiroshi Kuwajima, Takashi Washio, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Fast and accurate estimation of missing relations, e.g., similarity, distance and kernel, among objects is now one of the most important techniques required by major data mining tasks, because the missing information of the relations is needed in many applications such as economics, psychology, and social network communities. Though some approaches have been proposed in the last several years, the practical balance between their required computation amount and obtained accuracy are insufficient for some class of the relation estimation. The objective of this paper is to formalize a problem to quickly and efficiently estimate missing relations among objects from the …
Tournament-Based Teaching, Shannon Christopher Boesch, Sandra Boesch
Tournament-Based Teaching, Shannon Christopher Boesch, Sandra Boesch
Research Collection School Of Computing and Information Systems
Over the past two years we have collaborated to develop a process and set of online games to enable additional feedback to both students and instructors in a classroom setting. We have named the resulting process Tournament-based Teaching due to the extensive use of tournament-based feedback for groups and individuals throughout course delivery. Tournament-based Teaching enables individualized and peer-based learning in a classroom setting and provides additional motivation for students to prepare for classroom sessions. It also provides feedback to instructors, which can be leveraged to provide better schedule classroom sessions.
Information And Competitive Strategy In A Networked Economy, Robert J. Kauffman, Thomas A. Weber, D. J. Wu
Information And Competitive Strategy In A Networked Economy, Robert J. Kauffman, Thomas A. Weber, D. J. Wu
Research Collection School Of Computing and Information Systems
>One of the transformative changes over the past decade has been the way networks have enabled the distributed generation of value and how businesses and organizations have managed to capture a portion of this value. This has resulted in a plethora of innovative business ideas and new strategies. The present special section deals with the incentives for distributed content generation; counterintuitive network effects in the security software market, which features an intrinsic negative externality; and the possibility for collaboration between different platforms in a two-sided market. The included papers offer an interesting mix of theoretical and practical insights. All of …