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Research Collection School Of Computing and Information Systems

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2013

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Designing Optimal Innovation Portfolio, Arcot Desai Narasimhalu Dec 2013

Designing Optimal Innovation Portfolio, Arcot Desai Narasimhalu

Research Collection School Of Computing and Information Systems

There have been many approaches towards investing in innovation projects. There has been very little discussion about the need to align such investments with the mission, vision, goals, leadership style, value discipline and risk appetite of an organization. This paper reviews existing approaches to innovation related investments and suggests the setting up of a proper innovation portfolio management process along with three dashboards that will help make innovation related investment decisions in an informed manner. The resulting innovation portfolio will be optimal in its alignment with an organizations mission and vision. We expect this method to be used by all …

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An Integrated Model Of Team Motivation And Worker Skills For A Computer-Based Project Management Simulation, Wee Leong Lee Dec 2013

An Integrated Model Of Team Motivation And Worker Skills For A Computer-Based Project Management Simulation, Wee Leong Lee

Research Collection School Of Computing and Information Systems

In this paper, I shall propose an integrated model of worker skills and team motivation for a computer-based simulation game that can be used to provide experiential learning to students. They can act as project managers here without being burdened by the costs and risks associated with unsuccessful projects. I shall present an approach of classifying skills into five different types (relevant to IT projects) and apply a five-point competency scale to each skill type. The Pearson Correlation will be applied to the scores of each skill type to generate an efficiency index that will characterize the effectiveness of a …

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Factors Influencing Research Contributions And Researcher Interactions In Software Engineering: An Empirical Study, Subhajit Datta, A. S. M. Sajeev, Santonu Sarkar, Nishant Kumar Dec 2013

Factors Influencing Research Contributions And Researcher Interactions In Software Engineering: An Empirical Study, Subhajit Datta, A. S. M. Sajeev, Santonu Sarkar, Nishant Kumar

Research Collection School Of Computing and Information Systems

Research into software engineering (SE) education is largely concentrated on teaching and learning issues in coursework programs. This paper, in contrast, provides a meta analysis of research publications in software engineering to help with research education in SE. Studying publication patterns in a discipline will assist research students and supervisors gain a deeper understanding of how successful research has occurred in the discipline. We present results from a large scale empirical study covering over three and a half decades of software engineering research publications. We identify how different factors of publishing relate to the number of papers published as well …

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A Secure And Effective Anonymous User Authentication Scheme For Roaming Service In Global Mobility Networks, Fengtong Wen, Willy Susilo, Guomin Yang Dec 2013

A Secure And Effective Anonymous User Authentication Scheme For Roaming Service In Global Mobility Networks, Fengtong Wen, Willy Susilo, Guomin Yang

Research Collection School Of Computing and Information Systems

In global mobility networks, anonymous user authentication is an essential task for enabling roaming service. In a recent paper, Jiang et al. proposed a smart card based anonymous user authentication scheme for roaming service in global mobility networks. This scheme can protect user privacy and is believed to have many abilities to resist a range of network attacks, even if the secret information stored in the smart card is compromised. In this paper, we analyze the security of Jiang et al.’s scheme, and show that the scheme is in fact insecure against the stolen-verifier attack and replay attack. Then, we …

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A Simple Integration Of Social Relationship And Text Data For Identifying Potential Customers In Microblogging, Guansong Pang, Shengyi Jiang, Dongyi Chen Dec 2013

A Simple Integration Of Social Relationship And Text Data For Identifying Potential Customers In Microblogging, Guansong Pang, Shengyi Jiang, Dongyi Chen

Research Collection School Of Computing and Information Systems

Identifying potential customers among a huge number of users in microblogging is a fundamental problem for microblog marketing. One challenge in potential customer detection in microblogging is how to generate an accurate characteristic description for users, i.e., user profile generation. Intuitively, the preference of a user’s friends (i.e., the person followed by the user in microblogging) is of great importance to capture the characteristic of the user. Also, a user’s self-defined tags are often concise and accurate carriers for the user’s interests. In this paper, for identifying potential customers in microblogging, we propose a method to generate user profiles via …

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Dynamic Joint Sentiment-Topic Mode, Yulan He, Chenghua Lin, Wei Gao, Kam-Fai Wong Dec 2013

Dynamic Joint Sentiment-Topic Mode, Yulan He, Chenghua Lin, Wei Gao, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Social media data are produced continuously by a large and uncontrolled number of users. The dynamic nature of such data requires the sentiment and topic analysis model to be also dynamically updated, capturing the most recent language use of sentiments and topics in text. We propose a dynamic Joint Sentiment-Topic model (dJST) which allows the detection and tracking of views of current and recurrent interests and shifts in topic and sentiment. Both topic and sentiment dynamics are captured by assuming that the current sentiment-topic-specific word distributions are generated according to the word distributions at previous epochs. We study three different …

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Query-Document-Dependent Fusion: A Case Study Of Multimodal Music Retrieval, Zhonghua Li, Bingjun Zhang, Yi Yu, Jialie Shen, Ye Wang Dec 2013

Query-Document-Dependent Fusion: A Case Study Of Multimodal Music Retrieval, Zhonghua Li, Bingjun Zhang, Yi Yu, Jialie Shen, Ye Wang

Research Collection School Of Computing and Information Systems

In recent years, multimodal fusion has emerged as a promising technology for effective multimedia retrieval. Developing the optimal fusion strategy for different modality (e.g. content, metadata) has been the subject of intensive research. Given a query, existing methods derive a unified fusion strategy for all documents with the underlying assumption that the relative significance of a modality remains the same across all documents. However, this assumption is often invalid. We thus propose a general multimodal fusion framework, query-document-dependent fusion (QDDF), which derives the optimal fusion strategy for each query-document pair via intelligent content analysis of both queries and documents. By …

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Topicsketch: Real-Time Bursty Topic Detection From Twitter, Wei Xie, Feida Zhu, Jing Jiang, Ee Peng Lim, Ke Wang Dec 2013

Topicsketch: Real-Time Bursty Topic Detection From Twitter, Wei Xie, Feida Zhu, Jing Jiang, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

Twitter has become one of the largest platforms for users around the world to share anything happening around them with friends and beyond. A bursty topic in Twitter is one that triggers a surge of relevant tweets within a short time, which often reflects important events of mass interest. How to leverage Twitter for early detection of bursty topics has therefore become an important research problem with immense practical value. Despite the wealth of research work on topic modeling and analysis in Twitter, it remains a huge challenge to detect bursty topics in real-time. As existing methods can hardly scale …

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Dense Image Correspondence Under Large Appearance Variations, Linlin Liu, Kok-Lim Low, Wen-Yan Lin Dec 2013

Dense Image Correspondence Under Large Appearance Variations, Linlin Liu, Kok-Lim Low, Wen-Yan Lin

Research Collection School Of Computing and Information Systems

This paper addresses the difficult problem of finding dense correspondence across images with large appearance variations. Our method uses multiple feature samples at each pixel to deal with the appearance variations based on our observation that pre-defined single feature sample provides poor results in nearest neighbor matching. We apply the idea in a flow-based matching framework and utilize the best feature sample for each pixel to determine the flow field. We propose a novel energy function and use dual-layer loopy belief propagation to minimize it where the correspondence, the feature scale and rotation parameters are solved simultaneously. Our method is …

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Decision Trees To Model The Impact Of Disruption And Recovery In Supply Chain Networks, Loganathan Ponnanbalam, L. Wenbin, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh Dec 2013

Decision Trees To Model The Impact Of Disruption And Recovery In Supply Chain Networks, Loganathan Ponnanbalam, L. Wenbin, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh

Research Collection School Of Computing and Information Systems

Increase in the frequency of disruptions in the recent times and their impact have increased the attention in supply chain disruption management research. The objective of this paper is to understand as to how a disruption might affect the supply chain network - depending upon the network structure, the node that is disrupted, the disruption in production capacity of the disrupted node and the period of the disruption - via decision trees. To this end, we first developed a 5-tier agent-based supply chain model and then simulated it for various what-if disruptive scenarios for 3 different network structures (80 trials …

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Adaptive Computer‐Generated Forces For Simulator‐Based Training, Expert Systems With Applications, Teck-Hou Teng, Ah-Hwee Tan, Loo-Nin Teow Dec 2013

Adaptive Computer‐Generated Forces For Simulator‐Based Training, Expert Systems With Applications, Teck-Hou Teng, Ah-Hwee Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Simulator-based training is in constant pursuit of increasing level of realism. The transition from doctrine-driven computer-generated forces (CGF) to adaptive CGF represents one such effort. The use of doctrine-driven CGF is fraught with challenges such as modeling of complex expert knowledge and adapting to the trainees’ progress in real time. Therefore, this paper reports on how the use of adaptive CGF can overcome these challenges. Using a self-organizing neural network to implement the adaptive CGF, air combat maneuvering strategies are learned incrementally and generalized in real time. The state space and action space are extracted from the same hierarchical doctrine …

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Social Media For Supply Chain Risk Management, Xiuju Fu, Rick S. M. Goh, J. C. Tong, Loganathan Ponnanbalam, Xiaofeng Yin, Zhaoxia Wang, H. Y. Xu, Sifei Lu Dec 2013

Social Media For Supply Chain Risk Management, Xiuju Fu, Rick S. M. Goh, J. C. Tong, Loganathan Ponnanbalam, Xiaofeng Yin, Zhaoxia Wang, H. Y. Xu, Sifei Lu

Research Collection School Of Computing and Information Systems

With the rapid increase of online social network users worldwide, social media feeds have become a rich and valuable information resource and attract great attention across diversified domains. In social media data, there are abundant contents of two-way and interactive communication about products, demand, customer services and supply. This makes social media a valuable channel for listening to the voices from the market and measuring supply chain risks and new market trends for companies. In this study, we surveyed the potential value of social media in supply chain risk management (SCRM) and examined how they can be applied to SCRM …

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Hibernating Process: Modeling Mobile Calls At Multiple Scales, Siyuan Liu, Lei Li, Ramayya Krishnan Dec 2013

Hibernating Process: Modeling Mobile Calls At Multiple Scales, Siyuan Liu, Lei Li, Ramayya Krishnan

Research Collection School Of Computing and Information Systems

Do mobile phone calls at larger granularities behave in the same pattern as in smaller ones? How can we forecast the distribution of a whole month's phone calls with only one day's observation? There are many models developed to interpret large scale social graphs. However, all of the existing models focus on graph at one time scale. Many dynamical behaviors were either ignored, or handled at one scale. In particular new users might join or current users quit social networks at any time. In this paper, we propose HiP, a novel model to capture longitudinal behaviors in modeling degree distribution …

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A Dynamic Programming Approach To Achieving An Optimal End State Along A Serial Production Line, Shih-Fen Cheng, Blake E. Nicholson, Marina A. Epelman, Daniel J. Reaume, Robert L. Smith Dec 2013

A Dynamic Programming Approach To Achieving An Optimal End State Along A Serial Production Line, Shih-Fen Cheng, Blake E. Nicholson, Marina A. Epelman, Daniel J. Reaume, Robert L. Smith

Research Collection School Of Computing and Information Systems

In modern production systems, it is critical to perform maintenance, calibration, installation, and upgrade tasks during planned downtime. Otherwise, the systems become unreliable and new product introductions are delayed. For reasons of safety, testing, and access, task performance often requires the vicinity of impacted equipment to be left in a specific “end state” when production halts. Therefore, planning the shutdown of a production system to balance production goals against enabling non-production tasks yields a challenging optimization problem. In this paper, we propose a mathematical formulation of this problem and a dynamic programming approach that efficiently finds optimal shutdown policies for …

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An Agent-Based Simulation Approach To Experience Management In Theme Parks, Shih-Fen Cheng, Larry Junjie Lin, Jiali Du, Hoong Chuin Lau, Pradeep Reddy Varakantham Dec 2013

An Agent-Based Simulation Approach To Experience Management In Theme Parks, Shih-Fen Cheng, Larry Junjie Lin, Jiali Du, Hoong Chuin Lau, Pradeep Reddy Varakantham

Research Collection School Of Computing and Information Systems

In this paper, we illustrate how massive agent-based simulation can be used to investigate an exciting new application domain of experience management in theme parks, which covers topics like congestion control, incentive design, and revenue management. Since all visitors are heterogeneous and self-interested, we argue that a high-quality agent-based simulation is necessary for studying various problems related to experience management. As in most agent-base simulations, a sound understanding of micro-level behaviors is essential to construct high-quality models. To achieve this, we designed and conducted a first-of-its-kind real-world experiment that helps us understand how typical visitors behave in a theme-park environment. …

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The Influence Of Online Word-Of-Mouth On Long Tail Formation, Bin Gu, Qian Tang, Andrew B. Whinston Dec 2013

The Influence Of Online Word-Of-Mouth On Long Tail Formation, Bin Gu, Qian Tang, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

The long tail phenomenon has been attributed to both supply side and demand side economies. While the cause on the supply side is well-known, research on the demand side has largely focused on the awareness effect of online information that helps consumers discover new and often niche products. This study expands the demand side factors by showing that online information also influences the long tail phenomenon through the informative effect, which affects consumers' evaluation of product quality. We examine the informative effect in the context of online WOM. Two sets of theories suggest opposite directions for the implication of the …

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A Local Social Network Approach For Research Management, Xiaoyan Liu, Zhiling Guo, Zhenjiang Lin, Jian Ma Dec 2013

A Local Social Network Approach For Research Management, Xiaoyan Liu, Zhiling Guo, Zhenjiang Lin, Jian Ma

Research Collection School Of Computing and Information Systems

Traditional methods to evaluate research performance focus on citation count, quality and quantity of research output by individual researchers. These measures overlook the roles an individual plays in research collaboration, which is critical in an institutional research management environment due to the inherent interdependency among research entities. In order to address the organizational research management needs, we propose a research social network approach to better analyze local collaboration networks. For this purpose, we develop a new “collaboration supportiveness” measure to quantify an individual researcher's collaboration ability. Insights derived from this research are very helpful for managers to effectively allocate resources, …

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Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Queue Management, Kar Way Tan, Hoong Chuin Lau, Francis Chun Yue Lee Dec 2013

Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Queue Management, Kar Way Tan, Hoong Chuin Lau, Francis Chun Yue Lee

Research Collection School Of Computing and Information Systems

Addressing issue of crowding in an Emergency Department (ED) typically takes the form of process engineering or single-faceted queue management strategies such as demand restriction, queue prioritization or staffing the ED. This work provides an integrated framework to manage queue dynamically from both demand and supply perspectives. More precisely, we introduce intelligent dynamic patient prioritization strategies to manage the demand concurrently with dynamic resource adjustment policies to manage supply. Our framework allows decision-makers to select both the demand-side and supply-side strategies to suit the needs of their ED. We verify through a simulation that such a framework improves the patients' …

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Fundamental Limits On End-To-End Throughput Of Network Coding In Multi-Rate And Multicast Wireless Networks, Luiz Felipe Viera, Mario Gerla, Archan Misra Dec 2013

Fundamental Limits On End-To-End Throughput Of Network Coding In Multi-Rate And Multicast Wireless Networks, Luiz Felipe Viera, Mario Gerla, Archan Misra

Research Collection School Of Computing and Information Systems

This paper investigates the interaction between network coding and link-layer transmission rate diversity in multi-hop wireless networks. By appropriately mixing data packets at intermediate nodes, network coding allows a single multicast flow to achieve higher throughput to a set of receivers. Broadcast applications can also exploit link-layer rate diversity, whereby individual nodes can transmit at faster rates at the expense of corresponding smaller coverage area. We first demonstrate how combining rate-diversity with network coding can provide a larger capacity for data dissemination of a single multicast flow, and how consideration of rate diversity is critical for maximizing system throughput. Next …

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Modeling Temporal Adoptions Using Dynamic Matrix Factorization, Freddy Chong-Tat Chua, Richard Jayadi Oentaryo, Ee Peng Lim Dec 2013

Modeling Temporal Adoptions Using Dynamic Matrix Factorization, Freddy Chong-Tat Chua, Richard Jayadi Oentaryo, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The problem of recommending items to users is relevant to many applications and the problem has often been solved using methods developed from Collaborative Filtering (CF). Collaborative Filtering model-based methods such as Matrix Factorization have been shown to produce good results for static rating-type data, but have not been applied to time-stamped item adoption data. In this paper, we adopted a Dynamic Matrix Factorization (DMF) technique to derive different temporal factorization models that can predict missing adoptions at different time steps in the users' adoption history. This DMF technique is an extension of the Non-negative Matrix Factorization (NMF) based on …

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Adaptive Regret Minimization In Bounded-Memory Games, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha Nov 2013

Adaptive Regret Minimization In Bounded-Memory Games, 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 often use security audits to protect data subjects from inappropriate uses of this information by authorized insiders. In face of unknown incentives of employees, a reasonable audit strategy for the organization is one that minimizes its regret. While regret minimization has been extensively studied in repeated games, the standard notion of regret for repeated games cannot capture the complexity of the interaction between the organization (defender) and an adversary, which arises from dependence of rewards and actions on history. To account for this generality, we introduce a richer class of …

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A Scalable Approach For Malware Detection Through Bounded Feature Space Behavior Modeling, Mahinthan Chandramohan, Hee Beng Kuan Tan, Lionel C Briand, Lwin Khin Shar, Bindu Madhavi Padmanabhuni Nov 2013

A Scalable Approach For Malware Detection Through Bounded Feature Space Behavior Modeling, Mahinthan Chandramohan, Hee Beng Kuan Tan, Lionel C Briand, Lwin Khin Shar, Bindu Madhavi Padmanabhuni

Research Collection School Of Computing and Information Systems

In recent years, malware (malicious software) has greatly evolved and has become very sophisticated. The evolution of malware makes it difficult to detect using traditional signature-based malware detectors. Thus, researchers have proposed various behavior-based malware detection techniques to mitigate this problem. However, there are still serious shortcomings, related to scalability and computational complexity, in existing malware behavior modeling techniques. This raises questions about the practical applicability of these techniques. This paper proposes and evaluates a bounded feature space behavior modeling (BOFM) framework for scalable malware detection. BOFM models the interactions between software (which can be malware or benign) and security-critical …

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Electroweak Measurements In Electron-Positron Collisions At W-Boson-Pair Energies At Lep, S. Schael, Manoj Thulasidas Nov 2013

Electroweak Measurements In Electron-Positron Collisions At W-Boson-Pair Energies At Lep, S. Schael, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

Electroweak measurements performed with data taken at the electron–positron collider LEP at CERN from 1995 to 2000 are reported. The combined data set considered in this report corresponds to a total luminosity of about 3 fb −1 collected by the four LEP experiments ALEPH, DELPHI, L3 and OPAL, at centre-of-mass energies ranging from 130 GeV to 209 GeV. Combining the published results of the four LEP experiments, the measurements include total and differential cross-sections in photon-pair, fermion-pair and four-fermion production, the latter resulting from both double-resonant WW and ZZ production as well as singly resonant production. Total and differential cross-sections …

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Optimization Approaches For Solving Chance Constrained Stochastic Orienteering Problems, Pradeep Varakantham, Akshat Kumar Nov 2013

Optimization Approaches For Solving Chance Constrained Stochastic Orienteering Problems, Pradeep Varakantham, Akshat Kumar

Research Collection School Of Computing and Information Systems

Orienteering problems (OPs) are typically used to model routing and trip planning problems. OP is a variant of the well known traveling salesman problem where the goal is to compute the highest reward path that includes a subset of nodes and has an overall travel time less than the specified deadline. Stochastic orienteering problems (SOPs) extend OPs to account for uncertain travel times and are significantly harder to solve than deterministic OPs. In this paper, we contribute a scalable mixed integer LP formulation for solving risk aware SOPs, which is a principled approximation of the underlying stochastic optimization problem. Empirically, …

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Predicting User's Political Party Using Ideological Stances, Swapna Gottopati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang Nov 2013

Predicting User's Political Party Using Ideological Stances, Swapna Gottopati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang

Research Collection School Of Computing and Information Systems

Predicting users political party in social media has important impacts on many real world applications such as targeted advertising, recommendation and personalization. Several political research studies on it indicate that political parties’ ideological beliefs on sociopolitical issues may influence the users political leaning. In our work, we exploit users’ ideological stances on controversial issues to predict political party of online users. We propose a collaborative filtering approach to solve the data sparsity problem of users stances on ideological topics and apply clustering method to group the users with the same party. We evaluated several state-of-the-art methods for party prediction task …

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A Link-Bridged Topic Model For Cross-Domain Document Classification, Pei Yang, Wei Gao, Qi Tan, Kam-Fai Wong Nov 2013

A Link-Bridged Topic Model For Cross-Domain Document Classification, Pei Yang, Wei Gao, Qi Tan, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Transfer learning utilizes labeled data available from some related domain (source domain) for achieving effective knowledge transformation to the target domain. However, most state-of-the-art cross-domain classification methods treat documents as plain text and ignore the hyperlink (or citation) relationship existing among the documents. In this paper, we propose a novel cross-domain document classification approach called Link-Bridged Topic model (LBT). LBT consists of two key steps. Firstly, LBT utilizes an auxiliary link network to discover the direct or indirect co-citation relationship among documents by embedding the background knowledge into a graph kernel. The mined co-citation relationship is leveraged to bridge the …

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Mining Fraudulent Patterns In Online Advertising, Richard J. Oentaryo, Ee-Peng Lim Nov 2013

Mining Fraudulent Patterns In Online Advertising, Richard J. Oentaryo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Advances in web technologies have rendered onlineadvertising as an effective means for small and large businesses to target different market segments on the fly. Online advertising is a huge industry. According to Gartner Inc., worldwide online advertising revenue is projected tohit $11.4 billion in 2013, up from $9.6 billion in 2012. Global revenue will also reach $24.5 billion in 2016, with online advertising creating opportunities for app developers, advertising networks, and service providersin various regions. An online advertising ecosystem is typically coordinated by an advertising commissioner, acting as a broker between advertisers and content publishers. An advertiser plans a budget, …

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Vireo/Ecnu @ Trecvid 2013: A Video Dance Of Detection, Recounting And Search With Motion Relativity And Concept Learning From Wild, Chong-Wah Ngo, Feng Wang, Wei Zhang, Chun-Chet Tan, Zhanhu Sun, Shi-Ai Zhu, Ting Yao Nov 2013

Vireo/Ecnu @ Trecvid 2013: A Video Dance Of Detection, Recounting And Search With Motion Relativity And Concept Learning From Wild, Chong-Wah Ngo, Feng Wang, Wei Zhang, Chun-Chet Tan, Zhanhu Sun, Shi-Ai Zhu, Ting Yao

Research Collection School Of Computing and Information Systems

The VIREO group participated in four tasks: instance search, multimedia event recounting, multimedia event detection, and semantic indexing. In this paper, we will present our approaches and discuss the evaluation results

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Multimedia Modeling, Chong-Wah Ngo, Klaus Schoeffmann, Yiannis Andreopoulos, Christian Breiteneder Nov 2013

Multimedia Modeling, Chong-Wah Ngo, Klaus Schoeffmann, Yiannis Andreopoulos, Christian Breiteneder

Research Collection School Of Computing and Information Systems

Multimedia modeling aims to study computational models for addressing real-world multimedia problems from various perspectives, including information fusion, perceptual understanding, performance evaluation and social media. The topic becomes increasingly important with the massive amount of data available over the Internet, representing different pieces of information in heterogeneous forms that need to be consolidated before being used for multimedia problems. On the other hand, the advancement in technologies such as mobile and sensing devices drive the needs for revisiting the existing models for not only dealing with audio-visual cues but also incorporating various sensory modalities that have potential in providing cheaper …

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A Social Network-Empowered Research Analytics Framework For Project Selection, Thushari Silva, Zhiling Guo, Jian Ma, Hongbing Jiang, Huaping Chen Nov 2013

A Social Network-Empowered Research Analytics Framework For Project Selection, Thushari Silva, Zhiling Guo, Jian Ma, Hongbing Jiang, Huaping Chen

Research Collection School Of Computing and Information Systems

Traditional approaches for research project selection by government funding agencies mainly focus on the matching of research relevance by keywords or disciplines. Other research relevant information such as social connections (e.g., collaboration and co-authorship) and productivity (e.g., quality, quantity, and citations of published journal articles) of researchers is largely ignored. To overcome these limitations, this paper proposes a social network-empowered research analytics framework (RAF) for research project selections. Scholarmate.com, a professional research social network with easy access to research relevant information, serves as a platform to build researcher profiles from three dimensions, i.e., relevance, productivity and connectivity. Building upon profiles …

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