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Articles 1051 - 1080 of 1965
Full-Text Articles in Computer Sciences
Latent Factor Transition For Dynamic Collaborative Filtering, Chengyi Zhang, Ke Wang, Hongkun Yu, Jianling Sun, Ee Peng Lim
Latent Factor Transition For Dynamic Collaborative Filtering, Chengyi Zhang, Ke Wang, Hongkun Yu, Jianling Sun, Ee Peng Lim
Research Collection School Of Computing and Information Systems
No abstract provided.
Automated Mentor Assignment In Blended Learning Environments, Chris Boesch, Kevin Steppe
Automated Mentor Assignment In Blended Learning Environments, Chris Boesch, Kevin Steppe
Research Collection School Of Computing and Information Systems
In this paper we discuss the addition of automatic assignment of mentors during inclass lab work to an existing online platform for programing practice. SingPath is an web based tool for users to practice programming in several software languages. The platform started as a tool to provide students with online feedback on solutions to programming problems and expanded over time to support different of blended learning needs for a variety of classes and classroom settings. The SingPath platform supports traditional self-directed learning mechanisms such as badges and completion metrics as well as features for use in classrooms, such as tournaments. …
Do You Know The Speaker?: An Online Experiment With Authority Messages On Event Websites, Kwan-Hui Lim, Binyan Jiang, Ee Peng Lim, Achananuparp Palakorn
Do You Know The Speaker?: An Online Experiment With Authority Messages On Event Websites, Kwan-Hui Lim, Binyan Jiang, Ee Peng Lim, Achananuparp Palakorn
Research Collection School Of Computing and Information Systems
With the widespread adoption of the Web, many companies and organizations have established websites that provide information and support online transactions (e.g., buying products or viewing content). Unfortunately, users have limited attention to spare for interacting with online sites. Hence, it is of utmost importance to design sites that attract user attention and effectively guide users to the product or content items they like. Thus, we propose a novel and scalable experimentation approach to evaluate the effectiveness of online site designs. Our case study focuses on the effects of an authority message on visitors' browsing behavior on workshop and seminar …
On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo
On Finding The Point Where There Is No Return: Turning Point Mining On Game Data, Wei Gong, Ee Peng Lim, Feida Zhu, Achananuparp Palakorn, David Lo
Research Collection School Of Computing and Information Systems
Gaming expertise is usually accumulated through playing or watching many game instances, and identifying critical moments in these game instances called turning points. Turning point rules (shorten as TPRs) are game patterns that almost always lead to some irreversible outcomes. In this paper, we formulate the notion of irreversible outcome property which can be combined with pattern mining so as to automatically extract TPRs from any given game datasets. We specifically extend the well-known PrefixSpan sequence mining algorithm by incorporating the irreversible outcome property. To show the usefulness of TPRs, we apply them to Tetris, a popular game. We mine …
Online Multi-Modal Distance Metric Learning With Application To Image Retrieval, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Chunyan Miao, Zhi-Yong Liu
Online Multi-Modal Distance Metric Learning With Application To Image Retrieval, Pengcheng Wu, Steven C. H. Hoi, Peilin Zhao, Chunyan Miao, Zhi-Yong Liu
Research Collection School Of Computing and Information Systems
See https://ink.library.smu.edu.sg/sis_research/2924/. Distance metric learning (DML) is an important technique to improve similarity search in content-based image retrieval. Despite being studied extensively, most existing DML approaches typically adopt a single-modal learning framework that learns the distance metric on either a single feature type or a combined feature space where multiple types of features are simply concatenated. Such single-modal DML methods suffer from some critical limitations: (i) some type of features may significantly dominate the others in the DML task due to diverse feature representations; and (ii) learning a distance metric on the combined high-dimensional feature space can be extremely …
Cimloc: A Crowdsourcing Indoor Digital Map Construction System For Localization, Xiuming Zhang, Yunye Jin, Hwee Xian Tan, Wee-Seng Soh
Cimloc: A Crowdsourcing Indoor Digital Map Construction System For Localization, Xiuming Zhang, Yunye Jin, Hwee Xian Tan, Wee-Seng Soh
Research Collection School Of Computing and Information Systems
Indoor maps, as crucial prerequisites for many indoor localization and navigation systems, are sometimes inaccessible. The absence of an indoor map database and the high cost of manually constructing an indoor map produce a need for an inexpensive and efficient way to dynamically construct indoor maps. The ubiquity of sensor-equipped mobile devices enables us to crowdsource user trajectories, out of which indoor digital maps can be automatically constructed at low costs. Similar to other crowdsourced data, the collected user trajectories are often noisy and of low fidelity, which poses a challenge to the accurate map construction. To alleviate this problem, …
Adoption Of Mobile Information Services: An Empirical Study, S. Gao, J. Krogstie, Keng Siau
Adoption Of Mobile Information Services: An Empirical Study, S. Gao, J. Krogstie, Keng Siau
Research Collection School Of Computing and Information Systems
This study investigates the adoption of mobile information services at a Norwegian university. By expanding the Technology Acceptance Model (TAM), a new research model, known as the mobile services acceptance model (MSAM), is proposed. Based on the research model, seven research hypotheses are presented. The proposed research model and research hypotheses were empirically tested using data collected from a survey of users of a mobile service, extended Mobile Student Information Systems (eMSIS), at a Norwegian university. The findings indicate that the fitness of the research model is good. Support was also found for the seven research hypotheses. Among the factors, …
The Application Of Graph Theory To Access Control Systems, Eric Brown
The Application Of Graph Theory To Access Control Systems, Eric Brown
Student Work
Computer systems contain vital information that must be protected. One of the crucial aspects of protection is access control. A review of some of the research into ways in which access to the information in computers can be controlled focuses on a question about safety. The safety question asks, “Can a user ever gain access to a resource for which he is not authorized?” This question cannot be answered in general because of the unbounded, unrestricted nature of a general-purpose access control system. It can be answered only for systems that are specifically designed to restrict the actions that can …
Automated Oracle Generation Via Denotational Semantics, Liang Cao
Automated Oracle Generation Via Denotational Semantics, Liang Cao
Student Work
Software failure detection is typically done by comparing the running behaviors from a software under test (SUT) against its expected behaviors, called test oracles. In this paper, we present a formal approach to specifying test oracles in denotational semantics for systems with structured inputs. The approach introduces formal semantic evaluation rules, based on the denotational semantics methodology, defined on each productive grammar rule. We extend our grammar-based test generator, GENA, with automated test oracle generation. We provide three case studies of software testing: (i) a benchmark of Java programs on arithmetic calculations, (ii) an open source software on license identification, …
Test-Driven Learning In High School Computer Science, Ryan Stejskal
Test-Driven Learning In High School Computer Science, Ryan Stejskal
Student Work
Test-driven development is a style of software development that emphasizes writing tests first and running them frequently with the aid of automated testing tools. This development style is widely used in the software development industry to improve the rate of development while reducing software defects. Some computer science educators are adopting the test-driven development approach to help improve student understanding and performance on programming projects. Several studies have examined the benefits of teaching test-driven programming techniques to undergraduate student programmers, with generally positive results. However, the usage of test-driven learning at the high school level has not been studied to …
A Hybrid Scheme For Authenticating Scalable Video Codestreams, Zhuo Wei, Yongdong Wu, Robert H. Deng, Xuhua Ding
A Hybrid Scheme For Authenticating Scalable Video Codestreams, Zhuo Wei, Yongdong Wu, Robert H. Deng, Xuhua Ding
Research Collection School Of Computing and Information Systems
A scalable video coding (SVC) codestream consists of one base layer and possibly several enhancement layers. The base layer, which contains the lowest quality and resolution images, is the foundation of the SVC codestream and must be delivered to recipients, whereas enhancement layers contain richer contour/texture of images in order to supplement the base layer in resolution, quality, and temporal scalabilities. This paper presents a novel hybrid authentication (HAU) scheme. The HAU employs both cryptographic authentication and content-based authentication techniques to ensure integrity and authenticity of the SVC codestreams. Our analysis and experimental results indicate that the HAU is able …
Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang
Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang
Research Collection School Of Computing and Information Systems
Due to the fast development of social media on the Web, Twitter has become one of the major platforms for people to express themselves. Because of the wide adoption of Twitter, events like breaking news and release of popular videos can easily catch people’s attention and spread rapidly on Twitter, and the number of relevant tweets approximately reflects the impact of an event. Event identification and analysis on Twitter has thus become an important task. Recently the Recurrent Chinese Restaurant Process (RCRP) has been successfully used for event identification from news streams and news-centric social media streams. However, these models …
Where Am I? : Studying Users’ Indoor Navigation Location Needs, Kartik Muralidharan, Archan Misra, Rajesh Krishna Balan
Where Am I? : Studying Users’ Indoor Navigation Location Needs, Kartik Muralidharan, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Location has emerged as the single-most important context whilst building pervasive mobile applications. Several mobile applications have appeared that use location to provide a host of services such as location-specific advertising as well as navigation. As a result, the key challenge of positioning techniques has been to provide the most precise location of the user (device) and much effort has been put in computing this fine grained location in indoor environments. This is under the assumption that highly accurate location is crucial for all indoor services. To understand the location accuracy, that should prove sufficient, for users to navigate to …
Stfu Noob!: Predicting Crowdsourced Decisions On Toxic Behavior In Online Games, Jeremy Blackburn, Haewoon Kwak
Stfu Noob!: Predicting Crowdsourced Decisions On Toxic Behavior In Online Games, Jeremy Blackburn, Haewoon Kwak
Research Collection School Of Computing and Information Systems
One problem facing players of competitive games is negative, or toxic, behavior. League of Legends, the largest eSport game, uses a crowdsourcing platform called the Tribunal to judge whether a reported toxic player should be punished or not. The Tribunal is a two stage system requiring reports from those players that directly observe toxic behavior, and human experts that review aggregated reports. While this system has successfully dealt with the vague nature of toxic behavior by majority rules based on many votes, it naturally requires tremendous cost, time, and human efforts. In this paper, we propose a supervised learning approach …
Laser: A Living Analytics Experimentation System For Large-Scale Online Controlled Experiments, Kwan-Hui Lim, Ee Peng Lim, Achananuparp Palakorn, Adrian Vu, Agus Trisnajaya Kwee, Feida Zhu
Laser: A Living Analytics Experimentation System For Large-Scale Online Controlled Experiments, Kwan-Hui Lim, Ee Peng Lim, Achananuparp Palakorn, Adrian Vu, Agus Trisnajaya Kwee, Feida Zhu
Research Collection School Of Computing and Information Systems
Tracking user browsing data and measuring the effectiveness of website design and web services are important to businesses that want to attract the consumers today who spend much more time online than before. Instead of using randomized controlled experiments, the existing approach simply tracks user browsing behaviors before and after a change is made to website design or web services, and evaluate the differences. To address the effects caused by hidden factors (e.g. promotion activities on the website) and to give fair comparison of different website designs, we propose the LASER system, a unified experimentation platform that enables randomized online …
Hunting For Pirated Software Using Metamorphic Analysis, Hardikkumar Rana
Hunting For Pirated Software Using Metamorphic Analysis, Hardikkumar Rana
Master's Projects
In this paper, we consider the problem of detecting software that has been pirated and modified. We analyze a variety of detection techniques that have been previously studied in the context of malware detection. For each technique, we empirically determine the detection rate as a function of the degree of modification of the original code. We show that the code must be greatly modified before we fail to reliably distinguish it, and we show that our results offer a significant improvement over previous related work. Our approach can be applied retroactively to any existing software and hence, it is both …
Bayesian Classification Using Probabilistic Graphical Models, Mehal Patel
Bayesian Classification Using Probabilistic Graphical Models, Mehal Patel
Master's Projects
Bayesian Classifiers are used to classify unseen observations to one of the probable class category (also called class labels). Classification applications have one or more features and one or more class variables. Naïve Bayes Classifier is one of the simplest classifier used in practice. Though Naïve Bayes Classifier performs well in practice (in terms of its prediction accuracy), it assumes strong independence among features given class variable. Naïve Bayes assumption may reduce prediction accuracy when two or more features are dependent given class variable. In order to improve prediction accuracy, we can relax Naïve Bayes assumption and allow dependencies among …
Big Data Analytics Using Neural Networks, Chetan Sharma
Big Data Analytics Using Neural Networks, Chetan Sharma
Master's Projects
Machine learning is a branch of artificial intelligence in which the system is made to learn from data which can be used to make predictions, real world simulations, pattern recognitions and classifications of the input data. Among the various machine learning approaches in the sub-field of data classification, neural-network methods have been found to be an useful alternatives to the statistical techniques. An artificial neural network is a mathematical model, inspired by biological neural networks, are used for modeling complex relationships between inputs and outputs or to find patterns in data. The goal of the project is to construct a …
A Trust-Aware System For Personalized User Recommendations In Social Networks, Magdalini Eirinaki, Malamati Louta, Iraklis Varlamis
A Trust-Aware System For Personalized User Recommendations In Social Networks, Magdalini Eirinaki, Malamati Louta, Iraklis Varlamis
Faculty Publications
Social network analysis has recently gained a lot of interest because of the advent and the increasing popularity of social media, such as blogs, social networking applications, microblogging, or customer review sites. In this environment, trust is becoming an essential quality among user interactions and the recommendation for useful content and trustful users is crucial for all the members of the network. In this paper, we introduce a framework for handling trust in social networks, which is based on a reputation mechanism that captures the implicit and explicit connections between the network members, analyzes the semantics and dynamics of these …
Document Classification In Support Of Automated Metadata Extraction Form Heterogeneous Collections, Paul K. Flynn
Document Classification In Support Of Automated Metadata Extraction Form Heterogeneous Collections, Paul K. Flynn
Computer Science Theses & Dissertations
A number of federal agencies, universities, laboratories, and companies are placing their documents online and making them searchable via metadata fields such as author, title, and publishing organization. To enable this, every document in the collection must be catalogued using the metadata fields. Though time consuming, the task of identifying metadata fields by inspecting the document is easy for a human. The visual cues in the formatting of the document along with accumulated knowledge and intelligence make it easy for a human to identify various metadata fields. Even with the best possible automated procedures, numerous sources of error exist, including …
Assessing The Impact Of Electronic Health Record Systems Implementation On Hospital Patient Perceptions Of Care, Katherine Sofia Palacio Salgar
Assessing The Impact Of Electronic Health Record Systems Implementation On Hospital Patient Perceptions Of Care, Katherine Sofia Palacio Salgar
Engineering Management & Systems Engineering Theses & Dissertations
The delivery of health care services has been impacted by advances in Knowledge Management Information Systems (KMIS) and Information Technology (IT). The literature reveals that Electronic Health Records Systems (EHRs) are a comprehensive KMIS. There is a wide recognition in the body of knowledge that demonstrates the potential of EHRs to transform all aspects of health care services and, in consequence, the performance of Health Care Delivery Organizations (HCDO). Authors of published research also agree that there is a need for more empirical contributions that demonstrate the impact of EHRs upon HCDO. It is argued that in most cases, studies …
Modeling Contextual Agreement In Preferences, Ha Loc Do, Hady Wirawan Lauw
Modeling Contextual Agreement In Preferences, Ha Loc Do, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Personalization, or customizing the experience of each individual user, is seen as a useful way to navigate the huge variety of choices on the Web today. A key tenet of personalization is the capacity to model user preferences. The paradigm has shifted from that of individual preferences, whereby we look at a user's past activities alone, to that of shared preferences, whereby we model the similarities in preferences between pairs of users (e.g., friends, people with similar interests). However, shared preferences are still too granular, because it assumes that a pair of users would share preferences across all items. We …
Are Timed Automata Bad For A Specification Language? Language Inclusion Checking For Timed Automata, Ting Wang, Jun Sun, Yang Liu, Xinyu Wang, Shanping Li
Are Timed Automata Bad For A Specification Language? Language Inclusion Checking For Timed Automata, Ting Wang, Jun Sun, Yang Liu, Xinyu Wang, Shanping Li
Research Collection School Of Computing and Information Systems
Given a timed automaton P modeling an implementation and a timed automaton S as a specification, language inclusion checking is to decide whether the language of P is a subset of that of S. It is known that this problem is undecidable and “this result is an obstacle in using timed automata as a specification language” [2]. This undecidability result, however, does not imply that all timed automata are bad for specification. In this work, we propose a zone-based semi-algorithm for language inclusion checking, which implements simulation reduction based on Anti-Chain and LU-simulation. Though it is not guaranteed to terminate, …
Just-For-Me: An Adaptive Personalization System For Location-Aware Social Music Recommendation, Zhiyong Cheng, Jialie Shen
Just-For-Me: An Adaptive Personalization System For Location-Aware Social Music Recommendation, Zhiyong Cheng, Jialie Shen
Research Collection School Of Computing and Information Systems
The fast growth of online communities and increasing popularity of internet-accessing smart devices have significantly changed the way people consume and share music. As an emerging technology to facilitate effective music retrieval on the move, intelligent recommendation has been recently received great attentions in recent years. While a large amount of efforts have been invested in the field, the technology is still in its infancy. One of the major reasons for this stagnation is due to inability of the existing approaches to comprehensively take multiple kinds of contextual information into account. In the paper, we present a novel recommender system …
Profit-Maximizing Incentive For Participatory Sensing, Tie Luo, Hwee-Pink Tan, Lirong Xia
Profit-Maximizing Incentive For Participatory Sensing, Tie Luo, Hwee-Pink Tan, Lirong Xia
Research Collection School Of Computing and Information Systems
We design an incentive mechanism based on all-pay auctions for participatory sensing. The organizer (principal) aims to attract a high amount of contribution from participating users (agents) while at the same time lowering his payout, which we formulate as a profit-maximization problem. We use a contribution-dependent prize function in an environment that is specifically tailored to participatory sensing, namely incomplete information (with information asymmetry), risk-averse agents, and stochastic population. We derive the optimal prize function that induces the maximum profit for the principal, while satisfying strict individual rationality (i.e., strictly have incentive to participate at equilibrium) for both risk-neutral and …
Machine Learning In Wireless Sensor Networks: Algorithms, Strategies, And Applications, Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan
Machine Learning In Wireless Sensor Networks: Algorithms, Strategies, And Applications, Mohammad Abu Alsheikh, Shaowei Lin, Dusit Niyato, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in WSNs. The advantages and disadvantages of each proposed algorithm are …
Recommending Investors For Crowdfunding Projects, Jisun An, Daniele Quercia, Jon Crowcroft
Recommending Investors For Crowdfunding Projects, Jisun An, Daniele Quercia, Jon Crowcroft
Research Collection School Of Computing and Information Systems
To bring their innovative ideas to market, those embarking in new ventures have to raise money, and, to do so, they have often resorted to banks and venture capitalists. Nowadays, they have an additional option: that of crowdfunding. The name refers to the idea that funds come from a network of people on the Internet who are passionate about supporting others' projects. One of the most popular crowdfunding sites is Kickstarter. In it, creators post descriptions of their projects and advertise them on social media sites (mainly Twitter), while investors look for projects to support. The most common reason for …
A Hamming Embedding Kernel With Informative Bag-Of-Visual Words For Video Semantic Indexing, Feng Wang, Wen-Lei Zhao, Chong-Wah Ngo, Bernard Merialdo
A Hamming Embedding Kernel With Informative Bag-Of-Visual Words For Video Semantic Indexing, Feng Wang, Wen-Lei Zhao, Chong-Wah Ngo, Bernard Merialdo
Research Collection School Of Computing and Information Systems
In this article, we propose a novel Hamming embedding kernel with informative bag-of-visual words to address two main problems existing in traditional BoW approaches for video semantic indexing. First, Hamming embedding is employed to alleviate the information loss caused by SIFT quantization. The Hamming distances between keypoints in the same cell are calculated and integrated into the SVM kernel to better discriminate different image samples. Second, to highlight the concept-specific visual information, we propose to weight the visual words according to their informativeness for detecting specific concepts. We show that our proposed kernels can significantly improve the performance of concept …
Celebrowser: An Example Of Browsing Big Data On Small Device, Song Tan, Chong-Wah Ngo, Jun Xu, Yong Rui
Celebrowser: An Example Of Browsing Big Data On Small Device, Song Tan, Chong-Wah Ngo, Jun Xu, Yong Rui
Research Collection School Of Computing and Information Systems
In this demonstration, we demonstrate a mobile-based celebrity video browsing system called CeleBrowser. Using this system, users can interactively switch among four views: people-centric, timeline-centric, month-centric and topic-centric, for browsing celebrity-related hot videos. A peculiarity of the demonstration is to highlight the advantage of multiperspective information organization and presentation in engaging users for exploratory browsing of large number of Web videos on a device with small screen. Technology-wise the demonstration shows how query logs collected for six months from two vertical search engines are leveraged for mining hot events and videos of celebrities.
Teaching Analysis Of Software Designs Using Dependency Graph, Kevin Steppe
Teaching Analysis Of Software Designs Using Dependency Graph, Kevin Steppe
Research Collection School Of Computing and Information Systems
We present the use of a new type of dependency graph to aid students in analyzing the modifiability of software designs. Though a variety of software design concepts, such as information hiding, separation of concerns and patterns are taught to undergraduate students, they often have difficulty applying these concepts to the analysis of designs and particularly to comparing designs, perhaps due to the subjective nature of these concepts. Our new technique complements design structure matrix and ‘uses’ techniques to handle asymmetric dependency impacts and provide a deterministic approach to comparing alternative designs. A major goal of this technique was for …