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Research Collection School Of Computing and Information Systems

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Articles 5491 - 5520 of 6891

Full-Text Articles in Physical Sciences and Mathematics

Learning Personal Agents With Adaptive Player Modeling In Virtual Worlds, Yilin Kang, Ah-Hwee Tan Aug 2010

Learning Personal Agents With Adaptive Player Modeling In Virtual Worlds, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

There has been growing interest in creating intelligent agents in virtual worlds that do not follow fixed scripts predefined by the developers, but react accordingly based on actions performed by human players during their interaction. In order to achieve this objective, previous approaches have attempted to model the environment and the user’s context directly. However, a critical component for enabling personalized virtual world experience is missing, namely the capability to adapt over time to the habits and eccentricity of a particular player. To address the above issue, this paper presents a cognitive agent with learning player model capability for personalized …

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Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval And Clustering, Steven C. H. Hoi, Wei Liu, Shih-Fu Chang Aug 2010

Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval And Clustering, Steven C. H. Hoi, Wei Liu, Shih-Fu Chang

Research Collection School Of Computing and Information Systems

Learning a good distance metric plays a vital role in many multimedia retrieval and data mining tasks. For example, a typical content-based image retrieval (CBIR) system often relies on an effective distance metric to measure similarity between any two images. Conventional CBIR systems simply adopting Euclidean distance metric often fail to return satisfactory results mainly due to the well-known semantic gap challenge. In this article, we present a novel framework of Semi-Supervised Distance Metric Learning for learning effective distance metrics by exploring the historical relevance feedback log data of a CBIR system and utilizing unlabeled data when log data are …

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On Decision Support For Deliberating With Constraints In Constrained Optimization Models, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, David H. Wood Aug 2010

On Decision Support For Deliberating With Constraints In Constrained Optimization Models, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, David H. Wood

Research Collection School Of Computing and Information Systems

This paper introduces the Deliberation Decision Support System (DDSS). The DDSS obtains heuristically (using a genetic algorithm) solutions of interest for constrained optimization models. This is illustrated, without loss of generality, by generalized assignment problems. The DDSS also provides users with graphical tools that support post-solution deliberation for constrained optimization models. The DDSS and this paper, as befits practical concerns, are focused on deliberation with respect to the constraints of the models being used.

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A Decision Theoretic Approach To Data Leakage Prevention, Janusz Marecki, Mudhakar Srivastava, Pradeep Reddy Varakantham Aug 2010

A Decision Theoretic Approach To Data Leakage Prevention, Janusz Marecki, Mudhakar Srivastava, Pradeep Reddy Varakantham

Research Collection School Of Computing and Information Systems

In both the commercial and defense sectors a compelling need is emerging for rapid, yet secure, dissemination of information. In this paper we address the threat of information leakage that often accompanies such information flows. We focus on domains with one information source (sender) and many information sinks (recipients) where: (i) sharing is mutually beneficial for the sender and the recipients, (ii) leaking a shared information is beneficial to the recipients but undesirable to the sender, and (iii) information sharing decisions of the sender are determined using imperfect monitoring of the (un)intended information leakage by the recipients.We make two key …

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Effect Of Human Biases On Human-Agent Teams, Praveen Paruchuri, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri Aug 2010

Effect Of Human Biases On Human-Agent Teams, Praveen Paruchuri, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri

Research Collection School Of Computing and Information Systems

As human-agent teams get increasingly deployed in the real-world, agent designers need to take into account that humans and agents have different abilities to specify preferences. In this paper, we focus on how human biases in specifying preferences for resources impacts the performance of large, heterogeneous teams. In particular, we model the inclination of humans to simplify their preference functions and to exaggerate their utility for desired resources, and show the effect of these biases on the team performance. We demonstrate this on two different problems, which are representative of many resource allocation problems addressed in literature. In both these …

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A Probabilistic Approach To Personalized Tag Recommendation, Meiqun Hu, Ee Peng Lim, Jing Jiang Aug 2010

A Probabilistic Approach To Personalized Tag Recommendation, Meiqun Hu, Ee Peng Lim, Jing Jiang

Research Collection School Of Computing and Information Systems

In this work, we study the task of personalized tag recommendation in social tagging systems. To reach out to tags beyond the existing vocabularies of the query resource and of the query user, we examine recommendation methods that are based on personomy translation, and propose a probabilistic framework for incorporating translations by similar users (neighbors). We propose to use distributional divergence to measure the similarity between users in the context of personomy translation, and examine two variations of such similarity measures. We evaluate the proposed framework on a benchmark dataset collected from BibSonomy, and compare with personomy translation methods based …

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Investigating Perceptions Of A Location-Based Annotation System, Huynh Nhu Hop Quach, Khasfariyati Razikin, Dion Hoe-Lian Goh, Thi Nhu Quynh Kim, Tan Phat Pham, Yin-Leng Theng, Ee-Peng Lim Aug 2010

Investigating Perceptions Of A Location-Based Annotation System, Huynh Nhu Hop Quach, Khasfariyati Razikin, Dion Hoe-Lian Goh, Thi Nhu Quynh Kim, Tan Phat Pham, Yin-Leng Theng, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

We introduce MobiTOP, a Web-based system for organizing and retrieving hierarchical location-based annotations. Each annotation contains multimedia content (such as text, images, video) associated with a location, and users are able to annotate existing annotations to an arbitrary depth, in effect creating a hierarchy. An evaluation was conducted on a group of potential users to ascertain their perceptions of the usability of the application. The results were generally positive and the majority of the participants saw MobiTOP as a useful platform to share location-based information. We conclude with implications of our work and opportunities for future research.

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Distributed Route Planning And Scheduling Via Hybrid Conflict Resolution, Ramesh Thangarajoo, Hoong Chuin Lau Aug 2010

Distributed Route Planning And Scheduling Via Hybrid Conflict Resolution, Ramesh Thangarajoo, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we discuss the problem of route planning and scheduling by a group of agents. Each agent is responsible for designing a route plan and schedule over a geographical network, and the goal is to obtain a conflict-free plan/schedule that optimizes a global objective. We present a hybrid conflict resolution method that involves coalition formation and distributed constraint satisfaction depending on the level of coupling between agents. We show how this approach can be effectively applied to solve a distributed convoy movement planning problem.

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The Bi-Objective Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau Aug 2010

The Bi-Objective Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Physician scheduling is the assignment of physicians to perform different duties in the hospital timetable. In this paper, the goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We present a mathematical programming model to represent the problem as a bi-objective optimization problem. Three different methods based on ε–Constraint Method, Weighted-Sum Method and HillClimbing algorithm are proposed. These methods were tested on a real case from the Surgery Department of a large local government hospital, as well as on randomly generated problem instances. The strengths and weaknesses of the …

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Mining Interaction Behaviors For Email Reply Order Prediction, Byung-Won On, Ee Peng Lim, Jing Jiang, Amruta Purandare, Loo Nin Teow Aug 2010

Mining Interaction Behaviors For Email Reply Order Prediction, Byung-Won On, Ee Peng Lim, Jing Jiang, Amruta Purandare, Loo Nin Teow

Research Collection School Of Computing and Information Systems

In email networks, user behaviors affect the way emails are sent and replied. While knowing these user behaviors can help to create more intelligent email services, there has not been much research into mining these behaviors. In this paper, we investigate user engagingness and responsiveness as two interaction behaviors that give us useful insights into how users email one another. Engaging users are those who can effectively solicit responses from other users. Responsive users are those who are willing to respond to other users. By modeling such behaviors, we are able to mine them and to identify engaging or responsive …

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Architectural Strategy For Digital Platforms: Technological And Organizational Perspectives, Jason Woodard, Joel West Aug 2010

Architectural Strategy For Digital Platforms: Technological And Organizational Perspectives, Jason Woodard, Joel West

Research Collection School Of Computing and Information Systems

different spatial queries such as kNN query, range query and CNN query. A comprehensive experimental study has been conducted to

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A New Hardware-Assisted Pir With O(N) Shuffle Cost, Xuhua Ding, Yanjiang Yang, Robert H. Deng, Shuhong Wang Aug 2010

A New Hardware-Assisted Pir With O(N) Shuffle Cost, Xuhua Ding, Yanjiang Yang, Robert H. Deng, Shuhong Wang

Research Collection School Of Computing and Information Systems

Since the concept of private information retrieval (PIR) was first formalized by Chor et al., various constructions have been proposed with a common goal of reducing communication complexity. Unfortunately, none of them is suitable for practical settings mainly due to the prohibitively high cost for either communications or computations. The booming of the Internet and its applications, especially, the recent trend in outsourcing databases, fuels the research on practical PIR schemes. In this paper, we propose a hardware-assisted PIR scheme with a novel shuffle algorithm. Our PIR construction entails O(n) offline computation cost, and constant online operations and O(log n) …

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Messaging Behavior Modeling In Mobile Social Networks, Byung-Won On, Ee Peng Lim, Jing Jiang, Freddy Tat Chua Chua, Viet-An Nguyen, Loo Nin Teow Aug 2010

Messaging Behavior Modeling In Mobile Social Networks, Byung-Won On, Ee Peng Lim, Jing Jiang, Freddy Tat Chua Chua, Viet-An Nguyen, Loo Nin Teow

Research Collection School Of Computing and Information Systems

Mobile social networks are gaining popularity with the pervasive use of mobile phones and other handheld devices. In these networks, users maintain friendship links, exchange short messages and share content with one another. In this paper, we study the user behaviors in mobile messaging and friendship linking using the data collected from a large mobile social network service known as myGamma (m.mygamma.com). We distinguish two types of user behaviors: soliciting active responses for an initiated message and responding to an incoming message. We propose various models for the two behaviors also known as engagingness and responsiveness. Our experiments show that …

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A Hubel Wiesel Model For Hierarchical Representation Of Concepts In Textual Documents, Kiruthika Ramanathan, Luping Shi, Chong Chong Tow Aug 2010

A Hubel Wiesel Model For Hierarchical Representation Of Concepts In Textual Documents, Kiruthika Ramanathan, Luping Shi, Chong Chong Tow

Research Collection School Of Computing and Information Systems

Hubel Weisel models of the cortex describe visual processing as a hierarchy of increasingly sophisticated representations. While several models exist for image processing, little work has been done with Hubel Weisel models out of the domain of object recognition. In this paper, we describe how such models can be extended to the representation of concepts, resulting in a model that shares several properties with the PDP model of semantic cognition. The model that we propose is also capable of incremental learning, in which the knowledge is stored in the strength of the neuron connections. Degradation of old knowledge occurs as …

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Cloud Services From A Consumer Perspective, Philip Koehler, Arun Anandasivam, Dan Ma Aug 2010

Cloud Services From A Consumer Perspective, Philip Koehler, Arun Anandasivam, Dan Ma

Research Collection School Of Computing and Information Systems

Although there is an increased attention on Cloud Computing in the academic literature in the recent years, most research work focus on technical aspects of cloud computing. Research on consumers’ preferences for cloud services is limited to studies from consulting and industry companies. This paper fills the gap by empirically identifying consumer preferences for cloud service attributes. Using conjoint methods we reveal the relative importance of different attributes of cloud services. The results help both practitioners and academic researchers to better understand the prerequisites of a successful market introduction of cloud services and to design appropriate services. Moreover, the derived …

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On The Annotation Of Web Videos By Efficient Near-Duplicate Search, Wan-Lei Zhao, Xiao Wu, Chong-Wah Ngo Aug 2010

On The Annotation Of Web Videos By Efficient Near-Duplicate Search, Wan-Lei Zhao, Xiao Wu, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

With the proliferation of Web 2.0 applications, usersupplied social tags are commonly available in social media as a means to bridge the semantic gap. On the other hand, the explosive expansion of social web makes an overwhelming number of web videos available, among which there exists a large number of near-duplicate videos. In this paper, we investigate techniques which allow effective annotation of web videos from a data-driven perspective. A novel classifier-free video annotation framework is proposed by first retrieving visual duplicates and then suggesting representative tags. The significance of this paper lies in the addressing of two timely issues …

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Decentralized Resource Allocation And Scheduling Via Walrasian Auctions With Negotiable Agents, Huaxing Chen, Hoong Chuin Lau Aug 2010

Decentralized Resource Allocation And Scheduling Via Walrasian Auctions With Negotiable Agents, Huaxing Chen, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper is concerned with solving decentralized resource allocation and scheduling problems via auctions with negotiable agents by allowing agents to switch their bid generation strategies within the auction process, such that a better system wide performance is achieved on average as compared to the conventional walrasian auction running with agents of fixed bid generation strategy. We propose a negotiation mechanism embedded in auctioneer to solicit bidders’ change of strategies in the process of auction. Finally we benchmark our approach against conventional auctions subject to the real-time large-scale dynamic resource coordination problem to demonstrate the effectiveness of our approach.

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Hoare Logic For Graph Programs, Christopher M. Poskitt, Detlef Plump Aug 2010

Hoare Logic For Graph Programs, Christopher M. Poskitt, Detlef Plump

Research Collection School Of Computing and Information Systems

We present a new approach for verifying programs written in GP (for Graph Programs), an experimental programming language for performing computations on graphs at a high level of abstraction. Taking a labelled graph as input, a graph program nondeterministically applies to it a number of graph transformation rules, directed by simple control constructs such as sequential composition and as-long-as-possible iteration. We adapt classical Hoare logic to the domain of graphs, and describe a system of sound proof rules for showing the partial correctness of graph programs.

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New Constructions For Identity-Based Unidirectional Proxy Re-Encryption, Junzuo Lai, Wen Tao Zhu, Robert H. Deng, Shengli Liu, Weidong Kou Jul 2010

New Constructions For Identity-Based Unidirectional Proxy Re-Encryption, Junzuo Lai, Wen Tao Zhu, Robert H. Deng, Shengli Liu, Weidong Kou

Research Collection School Of Computing and Information Systems

We address the cryptographic topic of proxy re-encryption (PRE), which is a special public-key cryptosystem. A PRE scheme allows a special entity, known as the proxy, to transform a message encrypted with the public key of a delegator (say Alice), into a new ciphertext that is protected under the public key of a delegatee (say Bob), and thus the same message can then be recovered with Bob’s private key. In this paper, in the identity-based setting, we first investigate the relationship between so called mediated encryption and unidirectional PRE. We provide a general framework which converts any secure identity-based unidirectional …

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Self-Organizing Agents For Reinforcement Learning In Virtual Worlds, Yilin Kang, Ah-Hwee Tan Jul 2010

Self-Organizing Agents For Reinforcement Learning In Virtual Worlds, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

We present a self-organizing neural model for creating intelligent learning agents in virtual worlds. As agents in a virtual world roam, interact and socialize with users and other agents as in real world without explicit goals and teachers, learning in virtual world presents many challenges not found in typical machine learning benchmarks. In this paper, we highlight the unique issues and challenges of building learning agents in virtual world using reinforcement learning. Specifically, a self-organizing neural model, named TD-FALCON (Temporal Difference - Fusion Architecture for Learning and Cognition), is deployed, which enables an autonomous agent to adapt and function in …

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Mental Development And Representation Building Through Motivated Learning, Janusz Starzyk, Pawel Raif, Ah-Hwee Tan Jul 2010

Mental Development And Representation Building Through Motivated Learning, Janusz Starzyk, Pawel Raif, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Motivated learning is a new machine learning approach that extends reinforcement learning idea to dynamically changing, and highly structured environments. In this approach a machine is capable of defining its own objectives and learns to satisfy them though an internal reward system. The machine is forced to explore the environment in response to externally applied negative (pain) signals that it must minimize. In doing so, it discovers relationships between objects observed through its sensory inputs and actions it performs on the observed objects. Observed concepts are not predefined but are emerging as a result of successful operations. For the optimum …

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Auditing The Defense Against Cross Site Scripting In Web Applications, Lwin Khin Shar, Hee Beng Kuan Tan Jul 2010

Auditing The Defense Against Cross Site Scripting In Web Applications, Lwin Khin Shar, Hee Beng Kuan Tan

Research Collection School Of Computing and Information Systems

Majority attacks to web applications today are mainly carried out through input manipulation in order to cause unintended actions of these applications. These attacks exploit the weaknesses of web applications in preventing the manipulation of inputs. Among these attacks, cross site scripting attack -- malicious input is submitted to perform unintended actions on a HTML response page -- is a common type of attacks. This paper proposes an approach for thorough auditing of code to defend against cross site scripting attack. Based on the possible methods of implementing defenses against cross site scripting attack, the approach extracts all such defenses …

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Co-Reranking By Mutual Reinforcement For Image Search, Ting Yao, Tao Mei, Chong-Wah Ngo Jul 2010

Co-Reranking By Mutual Reinforcement For Image Search, Ting Yao, Tao Mei, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Most existing reranking approaches to image search focus solely on mining “visual” cues within the initial search results. However, the visual information cannot always provide enough guidance to the reranking process. For example, different images with similar appearance may not always present the same relevant information to the query. Observing that multi-modality cues carry complementary relevant information, we propose the idea of co-reranking for image search, by jointly exploring the visual and textual information. Co-reranking couples two random walks, while reinforcing the mutual exchange and propagation of information relevancy across different modalities. The mutual reinforcement is iteratively updated to constrain …

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Hybrid Time-Frequency Domain Analysis For Inverter-Fed Induction Motor Fault Detection, T. W. Chua, W. W. Tan, Zhaoxia Wang, C. S. Chang Jul 2010

Hybrid Time-Frequency Domain Analysis For Inverter-Fed Induction Motor Fault Detection, T. W. Chua, W. W. Tan, Zhaoxia Wang, C. S. Chang

Research Collection School Of Computing and Information Systems

The detection of faults in an induction motor is important as a part of preventive maintenance. Stator current is one of the most popular signals used for utility-supplied induction motor fault detection as a current sensor can be installed nonintrusively. In variable speeds operation, the use of an inverter to drive the induction motor introduces noise into the stator current so stator current based fault detection techniques become less reliable. This paper presents a hybrid algorithm, which combines time and frequency domain analysis, for broken rotor bar and bearing fault detection. Cluster information obtained by using Independent Component Analysis (ICA) …

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Semantics-Preserving Bag-Of-Words Models And Applications, Lei Wu, Steven C. H. Hoi, Nenghai Yu Jul 2010

Semantics-Preserving Bag-Of-Words Models And Applications, Lei Wu, Steven C. H. Hoi, Nenghai Yu

Research Collection School Of Computing and Information Systems

The Bag-of-Words (BoW) model is a promising image representation technique for image categorization and annotation tasks. One critical limitation of existing BoW models is that much semantic information is lost during the codebook generation process, an important step of BoW. This is because the codebook generated by BoW is often obtained via building the codebook simply by clustering visual features in Euclidian space. However, visual features related to the same semantics may not distribute in clusters in the Euclidian space, which is primarily due to the semantic gap between low-level features and high-level semantics. In this paper, we propose a …

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Non-Parametric Kernel Ranking Approach For Social Image Retrieval, Jinfeng Zhuang, Steven C. H. Hoi Jul 2010

Non-Parametric Kernel Ranking Approach For Social Image Retrieval, Jinfeng Zhuang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Social image retrieval has become an emerging research challenge in web rich media search. In this paper, we address the research problem of text-based social image retrieval, which aims to identify and return a set of relevant social images that are related to a text-based query from a corpus of social images. Regular approaches for social image retrieval simply adopt typical text-based image retrieval techniques to search for the relevant social images based on the associated tags, which may suffer from noisy tags. In this paper, we present a novel framework for social image re-ranking based on a non-parametric kernel …

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Evaluation Of Protein Backbone Alphabets: Using Predicted Local Structure For Fold Recognition, Kyong Jin Shim Jul 2010

Evaluation Of Protein Backbone Alphabets: Using Predicted Local Structure For Fold Recognition, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

Optimally combining available information is one of the key challenges in knowledge-driven prediction techniques. In this study, we evaluate six Phi and Psi-based backbone alphabets. We show that the addition of predicted backbone conformations to SVM classifiers can improve fold recognition. Our experimental results show that the inclusion of predicted backbone conformations in our feature representation leads to higher overall accuracy compared to when using amino acid residues alone.

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Show Me The Numbers: Visual Analytics For Insights, Tin Seong Kam Jul 2010

Show Me The Numbers: Visual Analytics For Insights, Tin Seong Kam

Research Collection School Of Computing and Information Systems

In this highly volatile and fast-paced financial market, traders and managers working in banking and financial organizations must struggle to cope with large and complex data from multi-sources, that move throughout the market at increasingly high speed. The cost of making poor business and investment decisions is very high. This places great demands on data analysts, who are responsible for providing process information, to support the activities of traders and managers. Static reports and traditional business intelligence tools simply cannot keep up with a market that is changing on a second-to-second basis. By the time the traders and bankers have …

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Coherent Bag-Of Audio Words Model For Efficient Large-Scale Video Copy Detection, Yang Liu, Wan-Lei Zhao, Chong-Wah Ngo, Chang-Sheng Xu, Han-Qing Lu Jul 2010

Coherent Bag-Of Audio Words Model For Efficient Large-Scale Video Copy Detection, Yang Liu, Wan-Lei Zhao, Chong-Wah Ngo, Chang-Sheng Xu, Han-Qing Lu

Research Collection School Of Computing and Information Systems

Current content-based video copy detection approaches mostly concentrate on the visual cues and neglect the audio information. In this paper, we attempt to tackle the video copy detection task resorting to audio information, which is equivalently important as well as visual information in multimedia processing. Firstly, inspired by bag-of visual words model, a bag-of audio words (BoA) representation is proposed to characterize each audio frame. Different from naive singlebased modeling audio retrieval approaches, BoA is a highlevel model due to its perceptual and semantical property. Within the BoA model, a coherency vocabulary indexing structure is adopted to achieve more efficient …

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Analytics-Modulated Coding Of Surveillance Video, Lai-Tee Cheok, Nikhil Gagvani Jul 2010

Analytics-Modulated Coding Of Surveillance Video, Lai-Tee Cheok, Nikhil Gagvani

Research Collection School Of Computing and Information Systems

Video surveillance systems increasingly use H.264 coding to achieve 24x7 recording and streaming. However, with the proliferation of security cameras, and the need to store several months of video, bandwidth and storage costs can be significant. We propose a new compression technique to significantly improve the coding efficiency of H.264 for surveillance video. Video content is analyzed and video semantics are extracted using video analytics algorithms such as segmentation, classification and tracking. In contrast to existing approaches, our Analytics-Modulated Compression (AMC) scheme does not require coding of object shape information and produces bitstreams that are standards-compliant and not limited to …

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