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Secure Mobile Subscription Of Sensor-Encrypted Data, Cheng-Kang Chu, Wen-Tao Zhu, Sherman S. M. Chow, Jianying Zhou, Robert H. Deng Mar 2011

Secure Mobile Subscription Of Sensor-Encrypted Data, Cheng-Kang Chu, Wen-Tao Zhu, Sherman S. M. Chow, Jianying Zhou, Robert H. Deng

Research Collection School Of Computing and Information Systems

In an end-to-end encryption model for a wireless sensor network (WSN), the network control center preloads encryption and decryption keys to the sensor nodes and the subscribers respectively, such that a subscriber can use a mobile device in the deployment field to decrypt the sensed data encrypted by the more resource-constrained sensor nodes. This paper proposes SMS-SED, a provably secure yet practically efficient key assignment system featuring a discrete time-based access control, to better support a business model where the sensors deployer rents the WSN to customers who desires a higher flexibility beyond subscribing to strictly consecutive periods. In SMS-SED, …

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An Energy Efficient Quality Adaptive Multi-Modal Sensor Framework For Context Recognition, Nirmalya Roy, Archan Misra, Christine Julien, Sajal K. Das, Jit Biswas Mar 2011

An Energy Efficient Quality Adaptive Multi-Modal Sensor Framework For Context Recognition, Nirmalya Roy, Archan Misra, Christine Julien, Sajal K. Das, Jit Biswas

Research Collection School Of Computing and Information Systems

Proliferation of mobile applications in unpredictable and changing environments requires applications to sense and act on changing operational contexts. In such environments, understanding the context of an entity is essential for adaptability of the application behavior to changing situations. In our view, context is a high-level representation of a user or entity’s state and can capture activities, relationships, capabilities, etc. Inherently, however, these high-level context measures are difficult to sense directly and instead must be inferred through the combination of many data sources. In pervasive computing environments where this context is of significant importance, a multitude of sensors is already …

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Deckard - A Tree-Based, Scalable, And Accurate Code Clone Detection Tool (Version 1.2.1), Lingxiao Jiang, Ghassan Misherghi, Zhendong Su, Glondu Stephane Feb 2011

Deckard - A Tree-Based, Scalable, And Accurate Code Clone Detection Tool (Version 1.2.1), Lingxiao Jiang, Ghassan Misherghi, Zhendong Su, Glondu Stephane

SMU Research Data

Deckard is a tree-based, scalable, and accurate code clone detection tool. It is also capable of reporting clone-related bugs. For more information, pls refer to readme.txt. The latest version is available from Deckard repository on Github. https://github.com/skyhover/Deckard

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Explosive Behavior In The 1990s Nasdaq: When Did Exuberance Escalate Asset Values?, Peter C. B. Phillips, Yangru Wu, Jun Yu Feb 2011

Explosive Behavior In The 1990s Nasdaq: When Did Exuberance Escalate Asset Values?, Peter C. B. Phillips, Yangru Wu, Jun Yu

Research Collection School Of Economics

A recursive test procedure is suggested that provides a mechanism for testing explosive behavior, date stamping the origination and collapse of economic exuberance, and providing valid confidence intervals for explosive growth rates. The method involves the recursive implementation of a right-side unit root test and a sup test, both of which are easy to use in practical applications, and some new limit theory for mildly explosive processes. The test procedure is shown to have discriminatory power in detecting periodically collapsing bubbles, thereby overcoming a weakness in earlier applications of unit root tests for economic bubbles. An empirical application to the …

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Manipulation In Digital Word-Of-Mouth: A Reality Check For Book Reviews, Nan Hu, Indranil Bose, Yunjun Gao, Ling Liu Feb 2011

Manipulation In Digital Word-Of-Mouth: A Reality Check For Book Reviews, Nan Hu, Indranil Bose, Yunjun Gao, Ling Liu

Research Collection School Of Computing and Information Systems

Built upon the discretionary accrual-based earnings management framework, our paper develops a discretionary manipulation proxy to study the management of online reviews. We reveal that fraudulent review manipulation is a serious problem for 1) non-bestseller books; 2) books whose reviews are classified as not very helpful; 3) books that experience greater variability in the helpfulness of their online reviews; and 4) popular books as well as high-priced books. We also show that review management decreases with the passage of time. Just like fraudulent earnings management, manipulated online reviews reflect inauthentic information from which consumers might derive wrong valuation especially for …

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Fraud Detection In Online Consumer Reviews, Nan Hu, Ling Liu, Vallbh Sambamurthy Feb 2011

Fraud Detection In Online Consumer Reviews, Nan Hu, Ling Liu, Vallbh Sambamurthy

Research Collection School Of Computing and Information Systems

Increasingly, consumers depend on social information channels, such as user-posted online reviews, to make purchase decisions. These reviews are assumed to be unbiased reflections of other consumers' experiences with the products or services. While extensively assumed, the literature has not tested the existence or non-existence of review manipulation. By using data from Amazon and Barnes & Noble, our study investigates if vendors, publishers, and writers consistently manipulate online consumer reviews. We document the existence of online review manipulation and show that the manipulation strategy of firms seems to be a monotonically decreasing function of the product's true quality or the …

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A Two-View Learning Approach For Image Tag Ranking, Jinfeng Zhuang, Steven C. H. Hoi Feb 2011

A Two-View Learning Approach For Image Tag Ranking, Jinfeng Zhuang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Tags of social images play a central role for text-based social image retrieval and browsing tasks. However, the original tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In this paper, we aim to overcome the challenge of social tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the …

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Adnext: A Visit-Pattern-Aware Mobile Advertising System For Urban Commercial Complexes, Byoungjip Kim, Jin-Young Ha, Sangjeong Lee, Seungwoo Kang, Youngki Lee, Yunseok Rhee, Lama Nachman, Junehwa Song Feb 2011

Adnext: A Visit-Pattern-Aware Mobile Advertising System For Urban Commercial Complexes, Byoungjip Kim, Jin-Young Ha, Sangjeong Lee, Seungwoo Kang, Youngki Lee, Yunseok Rhee, Lama Nachman, Junehwa Song

Research Collection School Of Computing and Information Systems

As smartphones have become prevalent, mobile advertising is getting significant attention as being not only a killer application in future mobile commerce, but also as an important business model of emerging mobile applications to monetize them. In this paper, we present AdNext, a visit-pattern-aware mobile advertising system for urban commercial complexes. AdNext can provide highly relevant ads to users by predicting places that the users will next visit. AdNext predicts the next visit place by learning the sequential visit patterns of commercial complex users in a collective manner. As one of the key enabling techniques for AdNext, we develop a …

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Evolution Of Developer Collaboration On The Jazz Platform: A Study Of A Large Scale Agile Project, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta Feb 2011

Evolution Of Developer Collaboration On The Jazz Platform: A Study Of A Large Scale Agile Project, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta

Research Collection School Of Computing and Information Systems

Collaboration is a key aspect of the agile philosophy of software development. As a software system matures over iterations, trends of developer collaboration can offer valuable insights into project dynamics. In this paper, we study evolution of developer collaboration for a large scale agile project on the Jazz platform. We construct networks of collaboration based on developer affiliations across comments on work items and file changes; and then compare parameters of such networks with established results from networks of scientific collaborations. The comparisons illuminate interesting facets of developer collaboration on the Jazz platform. Such perception helps deeper understanding of the …

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Distance Metric Learning From Uncertain Side Information For Automated Photo Tagging, Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu Feb 2011

Distance Metric Learning From Uncertain Side Information For Automated Photo Tagging, Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu

Research Collection School Of Computing and Information Systems

Automated photo tagging is an important technique for many intelligent multimedia information systems, for example, smart photo management system and intelligent digital media library. To attack the challenge, several machine learning techniques have been developed and applied for automated photo tagging. For example, supervised learning techniques have been applied to automated photo tagging by training statistical classifiers from a collection of manually labeled examples. Although the existing approaches work well for small testbeds with relatively small number of annotation words, due to the long-standing challenge of object recognition, they often perform poorly in large-scale problems. Another limitation of the existing …

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Database Access Pattern Protection Without Full-Shuffles, Xuhua Ding, Yanjiang Yang, Robert H. Deng Feb 2011

Database Access Pattern Protection Without Full-Shuffles, Xuhua Ding, Yanjiang Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Privacy protection is one of the fundamental security requirements for database outsourcing. A major threat is information leakage from database access patterns generated by query executions. The standard private information retrieval (PIR) schemes, which are widely regarded as theoretical solutions, entail O(n) computational overhead per query for a database with items. Recent works propose to protect access patterns by introducing a trusted component with constant storage size. The resulting privacy assurance is as strong as PIR, though with O(1) online computation cost, they still have O(n) amortized cost per query due to periodically full database shuffles. In this paper, we …

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Mining Social Images With Distance Metric Learning For Automated Image Tagging, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Ying He Feb 2011

Mining Social Images With Distance Metric Learning For Automated Image Tagging, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Ying He

Research Collection School Of Computing and Information Systems

With the popularity of various social media applications, massive social images associated with high quality tags have been made available in many social media web sites nowadays. Mining social images on the web has become an emerging important research topic in web search and data mining. In this paper, we propose a machine learning framework for mining social images and investigate its application to automated image tagging. To effectively discover knowledge from social images that are often associated with multimodal contents (including visual images and textual tags), we propose a novel Unified Distance Metric Learning (UDML) scheme, which not only …

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Pgtp: Power Aware Game Transport Protocol For Multi-Player Mobile Games, Bhojan Anand, Jeena Sebastian, Soh Yu Ming, Akhihebbal L. Ananda, Mun Choon Chan, Rajesh Krishna Balan Feb 2011

Pgtp: Power Aware Game Transport Protocol For Multi-Player Mobile Games, Bhojan Anand, Jeena Sebastian, Soh Yu Ming, Akhihebbal L. Ananda, Mun Choon Chan, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Applications on the smartphones are able to capitalize on the increasingly advanced hardware to provide a user experience reasonably impressive. However, the advancement of these applications are hindered battery lifetime of the smartphones. The battery technologies have a relatively low growth rate. Applications like mobile multiplayer games are especially power hungry as they maximize the use of the network, display and CPU resources. The PGTP, presented in this paper is aware of both the transport requirement of these multiplayer mobile games and the limitation posed by battery resource. PGTP dynamically controls the transport based on the criticality of game state …

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Fraud Detection In Online Consumer Reviews, Nan Hu, Ling Liu, Vallabh Sambamurthy Feb 2011

Fraud Detection In Online Consumer Reviews, Nan Hu, Ling Liu, Vallabh Sambamurthy

Research Collection School Of Computing and Information Systems

Increasingly, consumers depend on social information channels, such as user-posted online reviews, to make purchase decisions. These reviews are assumed to be unbiased reflections of other consumers' experiences with the products or services. While extensively assumed, the literature has not tested the existence or non-existence of review manipulation. By using data from Amazon and Barnes & Noble, our study investigates if vendors, publishers, and writers consistently manipulate online consumer reviews. We document the existence of online review manipulation and show that the manipulation strategy of firms seems to be a monotonically decreasing function of the product's true quality or the …

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Artificial Cognitive Memory - Changing From Density Driven To Functionality Driven, Luping Shi, Kaijun Yi, Kiruthika Ramanathan, Rong Zhao, Ning Ning, Ding Ding, Tow Chong Chong Feb 2011

Artificial Cognitive Memory - Changing From Density Driven To Functionality Driven, Luping Shi, Kaijun Yi, Kiruthika Ramanathan, Rong Zhao, Ning Ning, Ding Ding, Tow Chong Chong

Research Collection School Of Computing and Information Systems

Increasing density based on bit size reduction is currently a main driving force for the development of data storage technologies. However, it is expected that all of the current available storage technologies might approach their physical limits in around 15 to 20 years due to miniaturization. To further advance the storage technologies, it is required to explore a new development trend that is different from density driven. One possible direction is to derive insights from biological counterparts. Unlike physical memories that have a single function of data storage, human memory is versatile. It contributes to functions of data storage, information …

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Cryptanalysis Of A Certificateless Signcryption Scheme In The Standard Model, Jian Weng, Guoxiang Yao, Robert H. Deng, Min-Rong Chen, Xianxue Li Feb 2011

Cryptanalysis Of A Certificateless Signcryption Scheme In The Standard Model, Jian Weng, Guoxiang Yao, Robert H. Deng, Min-Rong Chen, Xianxue Li

Research Collection School Of Computing and Information Systems

Certificateless signcryption is a useful primitive which simultaneously provides the functionalities of certificateless encryption and certificateless signature. Recently, Liu et al. [15] proposed a new certificateless signcryption scheme, and claimed that their scheme is provably secure without random oracles in a strengthened security model, where the malicious-but-passive KGC attack is considered. Unfortunately, by giving concrete attacks, we indicate that Liu et al. certificateless signcryption scheme is not secure in this strengthened security model.

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Mining Iterative Generators And Representative Rules For Software Specification Discovery, David Lo, Jinyan Li, Limsoon Wong, Siau-Cheng Khoo Feb 2011

Mining Iterative Generators And Representative Rules For Software Specification Discovery, David Lo, Jinyan Li, Limsoon Wong, Siau-Cheng Khoo

Research Collection School Of Computing and Information Systems

Billions of dollars are spent annually on software-related cost. It is estimated that up to 45 percent of software cost is due to the difficulty in understanding existing systems when performing maintenance tasks (i.e., adding features, removing bugs, etc.). One of the root causes is that software products often come with poor, incomplete, or even without any documented specifications. In an effort to improve program understanding, Lo et al. have proposed iterative pattern mining which outputs patterns that are repeated frequently within a program trace, or across multiple traces, or both. Frequent iterative patterns reflect frequent program behaviors that likely …

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Searching Patterns For Relation Extraction Over The Web: Rediscovering The Pattern-Relation Duality, Yuan Fang, Kevin Chen-Chuan Chang Feb 2011

Searching Patterns For Relation Extraction Over The Web: Rediscovering The Pattern-Relation Duality, Yuan Fang, Kevin Chen-Chuan Chang

Research Collection School Of Computing and Information Systems

While tuple extraction for a given relation has been an active research area, its dual problem of pattern search- to find and rank patterns in a principled way- has not been studied explicitly. In this paper, we propose and address the problem of pattern search, in addition to tuple extraction. As our objectives, we stress reusability for pattern search and scalability of tuple extraction, such that our approach can be applied to very large corpora like the Web. As the key foundation, we propose a conceptual model PRDualRank to capture the notion of precision and recall for both tuples and …

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The New Way Of The Future: Small, Local, Open And Connected, Ezio Manzini Jan 2011

The New Way Of The Future: Small, Local, Open And Connected, Ezio Manzini

Social Space

Beset with a global financial crisis and deepening ecological woes, it’s clear that we need alternative models of development. But as Ezio Manzinipoints out, these models are already with us.

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Towards Rio 2012 And Collaborative Governance For Sustainable Development, Jem Bendell Jan 2011

Towards Rio 2012 And Collaborative Governance For Sustainable Development, Jem Bendell

Social Space

Since the global Earth Summit in 1992, non-governmental organisations and businesses have made some strides towards sustainable development, but as Jem Bendell explains, governments need to join them.

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Of Spatial And Mindset Change: An Interview With Tay Kheng Soon, Lien Centre For Social Innovation Jan 2011

Of Spatial And Mindset Change: An Interview With Tay Kheng Soon, Lien Centre For Social Innovation

Social Space

Amidst the gloom of the growing environmental crisis and unmet social needs, one man refuses to admit defeat. After 50 years advocating in civil society and the architectural space, Tay Kheng Soon has come up with yet another ground-breaking idea—Rubanisation—which re-imagines the city and countryside as a single organic whole. Social Space catches up with the social space maverick in his eco-office in the tranquil setting of a wooded area off Dairy Farm Road.

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Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung Jan 2011

Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung

Research Collection School Of Economics

We propose an asymptotic likelihood-based LASSO approach for model selection in regression analysis when data are subject to validation sampling. The method makes use of an initial estimator of the regression coefficients and their asymptotic covariance matrix to form an asymptotic likelihood. This ``working'' objective function facilitates the formulation of the LASSO and the implementation of a fast algorithm. Our method circumvents the need to use a likelihood set-up that requires full distributional assumptions about the data. We show that the resulting estimator is consistent in model selection and that the method has lower prediction errors than a model that …

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Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah Jan 2011

Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah

Research Collection School Of Economics

We propose a semiparametric conditional covariance (SCC) estimator that combines the first-stage parametric conditional covariance (PCC) estimator with the second-stage nonparametric correction estimator in a multiplicative way. We prove the asymptotic normality of our SCC estimator, propose a nonparametric test for the correct specification of PCC models, and study its asymptotic properties. We evaluate the finite sample performance of our test and SCC estimator and compare the latter with that of PCC estimator, purely nonparametric estimator, and Hafner, Dijk, and Franses’s (2006) estimator in terms of mean squared error and Value-at-Risk losses via simulations and real data analyses.

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Concept-Driven Multi-Modality Fusion For Video Search, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo Jan 2011

Concept-Driven Multi-Modality Fusion For Video Search, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

As it is true for human perception that we gather information from different sources in natural and multi-modality forms, learning from multi-modalities has become an effective scheme for various information retrieval problems. In this paper, we propose a novel multi-modality fusion approach for video search, where the search modalities are derived from a diverse set of knowledge sources, such as text transcript from speech recognition, low-level visual features from video frames, and high-level semantic visual concepts from supervised learning. Since the effectiveness of each search modality greatly depends on specific user queries, prompt determination of the importance of a modality …

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Editorial: Special Issue On Ubiquitous Electronic Commerce Systems, Robert H. Deng, Jari Veijalainen, Shiguo Lian, Dimitris Kanellopoulos Jan 2011

Editorial: Special Issue On Ubiquitous Electronic Commerce Systems, Robert H. Deng, Jari Veijalainen, Shiguo Lian, Dimitris Kanellopoulos

Research Collection School Of Computing and Information Systems

Ubiquitous computing is a post-desktop model of human-computer interaction in which information processing has been thoroughly integrated into everyday objects and activities. Emerging ubiquitous electronic commerce systems (UECS) are expected to be available anytime, anywhere, and using different official or personal computing devices. Systems and services such as digital libraries, on-line business transactions, mobile office and mobile TV are widely deployed. Users will be able to access these services anytime, anywhere, while using any computing device in a pervasive way.

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Improving Service Through Just-In-Time Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu Jan 2011

Improving Service Through Just-In-Time Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu

Research Collection School Of Computing and Information Systems

This paper is concerned with the problem of Just-In-Time (JIT) job scheduling in a dynamic environment under uncertainty to attain timely service. We provide an approach, based on robust scheduling concepts, to analytically evaluate the expected cost of earliness and tardiness for each job and also the project. In addition, we search for a schedule execution policy with the minimum robust cost such that for a given risk level (epsilon), the actual realized schedule has (1 - epsilon) probability of completing with less than or equal to this robust cost. Our method is quite generic, and can be applied to …

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Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati Jan 2011

Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati

Research Collection School Of Computing and Information Systems

Optimizing parameter settings is an important task in algorithm design. Several automated parameter tuning procedures/configurators have been proposed in the literature, most of which work effectively when given a good initial range for the parameter values. In the Design of Experiments (DOE), a good initial range is known to lead to an optimum parameter setting. In this paper, we present a framework based on DOE to find a good initial range of parameter values for automated tuning. We use a factorial experiment design to first screen and rank all the parameters thereby allowing us to then focus on the parameter …

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Near-Duplicate Keyframe Retrieval By Semi-Supervised Learning And Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan Jan 2011

Near-Duplicate Keyframe Retrieval By Semi-Supervised Learning And Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Near-duplicate keyframe (NDK) retrieval techniques are critical to many real-world multimedia applications. Over the last few years, we have witnessed a surge of attention on studying near-duplicate image/keyframe retrieval in multimedia community. To facilitate an effective approach to NDK retrieval on large-scale data, we suggest an effective Multi-Level Ranking (MLR) scheme that effectively retrieves NDKs in a coarse-to-fine manner. One key stage of the MLR ranking scheme is how to learn an effective ranking function with extremely small training examples in a near-duplicate detection task. To attack this challenge, we employ a semi-supervised learning method, semi-supervised support vector machines, which …

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Solving The Teacher Assignment Problem By Two Metaheuristics, Aldy Gunawan, Kien Ming Ng Jan 2011

Solving The Teacher Assignment Problem By Two Metaheuristics, Aldy Gunawan, Kien Ming Ng

Research Collection School Of Computing and Information Systems

The timetabling problem arising from a university in Indonesia is addressed in this paper.It involves the assignment of teachers to the courses and course sections. We formulate theproblem as a mathematical programming model. Two different algorithms, mainly basedon simulated annealing (SA) and tabu search (TS) algorithms, are proposed for solving theproblem. The proposed algorithms consist of two phases. The first phase involves allocatingthe teachers to the courses and determining the number of courses to be assigned to eachteacher. The second phase involves assigning the teachers to the course sections in order tobalance the teachers’ load. The performance of the proposed …

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Solving The Quadratic Assignment Problem By A Hybrid Algorithm, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh Jan 2011

Solving The Quadratic Assignment Problem By A Hybrid Algorithm, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh

Research Collection School Of Computing and Information Systems

This paper presents a hybrid algorithm to solve the Quadratic Assignment Problem (QAP). The proposed algorithminvolves using the Greedy Randomized Adaptive Search Procedure (GRASP) to obtain an initial solution, and then using a combinedSimulated Annealing (SA) and Tabu Search (TS) algorithm to improve the solution. Experimental results indicate that the hybridalgorithm is able to obtain good quality solutions for QAPLIB test problems within reasonable computation time.

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