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Articles 9031 - 9060 of 10474
Full-Text Articles in Entire DC Network
Simulating A Smartboard By Real-Time Gesture Detection In Lecture Videos, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Simulating A Smartboard By Real-Time Gesture Detection In Lecture Videos, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Research Collection School Of Computing and Information Systems
Gesture plays an important role for recognizing lecture activities in video content analysis. In this paper, we propose a real-time gesture detection algorithm by integrating cues from visual, speech and electronic slides. In contrast to the conventional "complete gesture" recognition, we emphasize detection by the prediction from "incomplete gesture". Specifically, intentional gestures are predicted by the modified hidden Markov model (HMM) which can recognize incomplete gestures before the whole gesture paths are observed. The multimodal correspondence between speech and gesture is exploited to increase the accuracy and responsiveness of gesture detection. In lecture presentation, this algorithm enables the on-the-fly editing …
Relationship Preserving Auction For Repeated E-Procurement, Park J., Lee J., Lau H.
Relationship Preserving Auction For Repeated E-Procurement, Park J., Lee J., Lau H.
Research Collection School Of Computing and Information Systems
While e-procurement auction has helped firms to achieve lower procurement costs, auction mechanisms that prevail at present in procurement markets need to address an important issue that concerns the ability to maintain long term relationships with the partners, especially in repeated e-procurement settings. In this paper, we propose a Relationship Preserving Auction (RPA) mechanism that augments the conventional auction mechanism with a bidder relationship scoring model. Our proposed mechanism gives increased chances of winning to the bidders who have bidden at relatively competitive price but had comparatively less wins so far. Keeping these bidders in the auction over time will …
Impacts Of Social Network Structure On Knowledge Sharing In Open Source Software Development Teams, Y. Long, Keng Siau
Impacts Of Social Network Structure On Knowledge Sharing In Open Source Software Development Teams, Y. Long, Keng Siau
Research Collection School Of Computing and Information Systems
The study examines the relationship between social network structure and knowledge sharing in Open Source Software (OSS) development teams. One hundred and fifty projects were selected from SourceForge.net using stratified sampling. Social network structure was measured by two indices: degree of centralization and core/periphery fitness. Knowledge sharing was measured from two aspects: the quality of knowledge sharing that is indicated by the helpfulness of messages and the quantity of knowledge sharing that is indicated by the number of messages. The results show that social network structure significantly affects the quantity of knowledge sharing. However, social network structure does not influence …
Knowledge Transfer Via Multiple Model Local Structure Mapping, Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
Knowledge Transfer Via Multiple Model Local Structure Mapping, Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
Research Collection School Of Computing and Information Systems
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from which test examples are to be drawn. The task can be especially difficult when the training examples are from one or several domains different from the test domain. In this paper, we propose a locally weighted ensemble framework to combine multiple models for transfer learning, where the weights are dynamically assigned according to a model's predictive power on each test example. It can integrate the advantages of various learning algorithms and the labeled information from multiple …
The Pricing Strategy Analysis For The Software-As-A-Service Business Model, Dan Ma, Abraham Seidmann
The Pricing Strategy Analysis For The Software-As-A-Service Business Model, Dan Ma, Abraham Seidmann
Research Collection School Of Computing and Information Systems
The Software-as-a-Service (SaaS) model is a novel way of delivering software applications. In this paper, we present an analytical model to study the competition between the SaaS and the traditional COTS (Commercial off-the-shelf) software. The main research goal is to analyze the pricing strategy of the SaaS in a competitive setting. The model captures the most salient differences between the SaaS and COTS, including their distinct pricing structures, user initial setup costs, system customization levels, and delivery channels. We find that the two could coexist in a competitive market in the long run, and more importantly, we show how the …
Authenticating The Query Results Of Text Search Engines, Hwee Hwa Pang, Kyriakos Mouratidis
Authenticating The Query Results Of Text Search Engines, Hwee Hwa Pang, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
The number of successful attacks on the Internet shows that it is very difficult to guarantee the security of online search engines. A breached server that is not detected in time may return incorrect results to the users. To prevent that, we introduce a methodology for generating an integrity proof for each search result. Our solution is targeted at search engines that perform similarity-based document retrieval, and utilize an inverted list implementation (as most search engines do). We formulate the properties that define a correct result, map the task of processing a text search query to adaptations of existing threshold-based …
Regression Asymptotics Using Martingale Convergence Methods, Rustam Ibragimov, Peter C. B. Phillips
Regression Asymptotics Using Martingale Convergence Methods, Rustam Ibragimov, Peter C. B. Phillips
Research Collection School Of Economics
Weak convergence of partial sums and multilinear forms in independent random variables and linear processes and their nonlinear analogues to stochastic integrals now plays a major role in nonstationary time series and has been central to the development of unit root econometrics. The present paper develops a new and conceptually simple method for obtaining such forms of convergence. The method relies on the fact that the econometric quantities of interest involve discrete time martingales or semimartingales and shows how in the limit these quantities become continuous martingales and semimartingales. The limit theory itself uses very general convergence results for semimartingales …
Classification In P2p Networks By Bagging Cascade Rsvms, Hock Hee Ang, Vikvekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng, Anwitaman Datta
Classification In P2p Networks By Bagging Cascade Rsvms, Hock Hee Ang, Vikvekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng, Anwitaman Datta
Research Collection School Of Computing and Information Systems
Data mining tasks in P2P are bound by issues like scalability, peer dynamism, asynchronism, and data privacy preservation. These challenges pose difficulties for deploying conventional machine learning techniques in P2P networks, which may be hard to achieve classification accuracies comparable to regular centralized solutions. We recently investigated the classification problem in P2P networks and proposed a novel P2P classification approach by cascading Reduced Support Vector Machines (RSVM). Although promising results were obtained, the existing solution has some drawback of redundancy in both communication and computation. In this paper, we present a new approach to over the limitation of the previous …
Understanding Factors Influencing Proficient Information Systems Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Understanding Factors Influencing Proficient Information Systems Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Variations exist among information system (IS) users’ abilities to effectively utilize an IS. Some users are able to maximize IS potential, while others are not. This research proposes to understand the attributes of individuals who are most capable of exploiting IS to its fullest potential as well as the management and organizational factors that facilitate the development of highly competent users. The Repertory Grid Technique was utilized to identify user attributes contributing to IS proficiency in Phase One of this research and will be utilized to identify management and organizational factors in Phase Two. The results will provide a comprehensive …
Critical Success Factors In Soa Implementation, J. Erickson, Keng Siau
Critical Success Factors In Soa Implementation, J. Erickson, Keng Siau
Research Collection School Of Computing and Information Systems
Service Oriented Architecture (SOA) has become flavor du jour for many businesses. Seemingly, almost every company has implemented, is in the midst of implementing or is seriously considering a SOA project. A critical question many organizations are facing now is – what are the critical success factors for SOA implementations? This research aims to identify a list of factors relating to SOA implementation success. A Delphi study forms the research method, and inputs regarding SOA critical success factors are requested from a panel of experts.
Mining Patterns And Rules For Software Specification Discovery, David Lo, Siau-Cheng Khoo
Mining Patterns And Rules For Software Specification Discovery, David Lo, Siau-Cheng Khoo
Research Collection School Of Computing and Information Systems
Software specifications are often lacking, incomplete and outdated in the industry. Lack and incomplete specifications cause various software engineering problems. Studies have shown that program comprehension takes up to 45% of software development costs. One of the root causes of the high cost is the lack-of documented specification. Also, outdated and incomplete specification might potentially cause bugs and compatibility issues. In this paper, we describe novel data mining techniques to mine or reverse engineer these specifications from the pool of software engineering data. A large amount of software data is available for analysis. One form of software data is program …
Learning Outcomes For A Business Information Systems Undergraduate Program, Joelle Elmaleh, Steven Miller, Paul S. Goodman
Learning Outcomes For A Business Information Systems Undergraduate Program, Joelle Elmaleh, Steven Miller, Paul S. Goodman
Research Collection School Of Computing and Information Systems
We present a learning outcomes framework for an Information Systems (IS) undergraduate program. This framework includes a supporting software application that goes beyond any other attempt reported to date to integrate learning outcomes into program-wide and course-wide curriculum development, ongoing curriculum redesign, and student learning support. The Learning Outcomes Management System (LOMS) described here is a first-of-a-kind information system created as part of implementing a program-wide learning outcomes framework in a university setting. Our learning outcomes framework is distinct in that 1) it is based on a three-level hierarchically structured definition of learning outcomes that consistently apply to both the …
Being Naive About Naive Diversification: Can Investment Theory Be Consistently Useful?, Jun Tu, Guofu Zhou
Being Naive About Naive Diversification: Can Investment Theory Be Consistently Useful?, Jun Tu, Guofu Zhou
Research Collection Lee Kong Chian School Of Business
The modern portfolio theory pioneered by Markowitz (1952) is widely used in practice and taught in MBA texts. DeMiguel, Garlappi and Uppal (2007), however, show that, due to estimation errors, existing theory-based portfolio strategies are not as good as we once thought, and the estimation window needed for them to beat the naive $1/N$ strategy (that invests equally across N risky assets) is 'around 3000 months for a portfolio with 25 assets and about 6000 months for a portfolio with 50 assets.' In this paper, we modify the modern portfolio theory to account for estimation errors, so that the theory …
Examining Differential Item Functioning Of The Rosenberg Self-Esteem Scale Across Eight Countries (In Press), Lisa E. Baranik, Adam W. Meade, Chad E. Lakey, Charles E. Lance, Changya Hu, Wei Hua, Alex Michalos
Examining Differential Item Functioning Of The Rosenberg Self-Esteem Scale Across Eight Countries (In Press), Lisa E. Baranik, Adam W. Meade, Chad E. Lakey, Charles E. Lance, Changya Hu, Wei Hua, Alex Michalos
Research Collection Lee Kong Chian School Of Business
We examined the differential item functioning (DIF) of Rosenberg's (1965) Self-Esteem Scale (RSES) and compared scores from U.S. participants with those from 7 other countries: Canada, Germany, New Zealand, Kenya, South Africa, Singapore, and Taiwan. Results indicate that DIF was present in all comparisons. Moreover, controlling for latent self-esteem, participants from individualistic countries had an easier time reporting high self-esteem on self-competence-related items, whereas participants from communal countries had an easier time reporting high self-esteem on self-liking items (Tafarodi & Milne, 2002). After adjusting for DIF, we found larger mean self-esteem differences between the countries than observed scores initially indicated. …
Smu Names New Institute After The Late Mr Sim Kee Boon, Singapore Management University
Smu Names New Institute After The Late Mr Sim Kee Boon, Singapore Management University
SMU Press Releases and News
No abstract provided.
Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Predicting Trusts Among Users Of Online Communities - An Epinions Case Study, Haifeng Liu, Ee-Peng Lim, Hady Wirawan Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Research Collection School Of Computing and Information Systems
Embedding deals with reducing the high-dimensional representation of data into a low-dimensional representation. Previous work mostly focuses on preserving similarities among objects. Here, not only do we explicitly recognize multiple types of objects, but we also focus on the ordinal relationships across types. Collaborative Ordinal Embedding or COE is based on generative modelling of ordinal triples. Experiments show that COE outperforms the baselines on objective metrics, revealing its capacity for information preservation for ordinal data.
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Research Collection School Of Computing and Information Systems
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is not guaranteed to converge to the global optimum. Instead, it stops at some local optimums, which can be much worse than the global optimum.
On Profiling Blogs With Representative Entries, Jinfeng Zhuang, Steven C. H. Hoi, Aixin Sun
On Profiling Blogs With Representative Entries, Jinfeng Zhuang, Steven C. H. Hoi, Aixin Sun
Research Collection School Of Computing and Information Systems
With an explosive growth of blogs, information seeking in blogosphere becomes more and more challenging. One example task is to find the most relevant topical blogs against a given query or an existing blog. Such a task requires concise representation of blogs for effective and efficient searching and matching. In this paper, we investigate a new problem of profiling a blog by choosing a set of m most representative entries from the blog, where m is a predefined number that is application-dependent. With the set of selected representative entries, applications on blogs avoid handling hundreds or even thousands of entries …
Bag-Of-Visual-Words Expansion Using Visual Relatedness For Video Indexing, Yu-Gang Jiang, Chong-Wah Ngo
Bag-Of-Visual-Words Expansion Using Visual Relatedness For Video Indexing, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Bag-of-visual-words (BoW) has been popular for visual classification in recent years. In this paper, we propose a novel BoW expansion method to alleviate the effect of visual word correlation problem. We achieve this by diffusing the weights of visual words in BoW based on visual word relatedness, which is rigorously defined within a visual ontology. The proposed method is tested in video indexing experiment on TRECVID-2006 video retrieval benchmark, and an improvement of 7% over the traditional BoW is reported.
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper presents a self-organizing network model for the fusion of multimedia information. By synchronizing the encoding of information across multiple media channels, the neural model known as fusion Adaptive Resonance Theory (fusion ART) generates clusters that encode the associative mappings across multimedia information in a real-time and continuous manner. In addition, by incorporating a semantic category channel, fusion ART further enables multimedia information to be fused into predefined themes or semantic categories. We illustrate the fusion ART’s functionalities through experiments on two multimedia data sets in the terrorist domain and show the viability of the proposed approach.
Revenue Management In Business Services, Brenda Dietrich, Giuseppe A. Paleologo, Laura Wynter
Revenue Management In Business Services, Brenda Dietrich, Giuseppe A. Paleologo, Laura Wynter
Research Collection School Of Computing and Information Systems
A significant portion of the services industry is focused on providing services (medical, legal, financial, personal, and travel) to individuals. However, studies have shown that a less visible but rapidly growing segment of the service sector comprises firms that provide business functions to other businesses. The sector covers tasks such as payroll processing, procurement, and information systems management, as well as business consulting, technical support, call center operations, and software development. Firms may choose to purchase, rather than perform, these business functions to reduce costs, to mitigate risk, or simply to focus on their processes that provide marketplace differentiation. Transferring …
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Comments left by readers on Web documents contain valuable information that can be utilized in different information retrieval tasks including document search, visualization, and summarization. In this paper, we study the problem of comments-oriented document summarization and aim to summarize a Web document (e.g., a blog post) by considering not only its content, but also the comments left by its readers. We identify three relations (namely, topic, quotation, and mention) by which comments can be linked to one another, and model the relations in three graphs. The importance of each comment is then scored by: (i) graph-based method, where the …
Searching Correlated Objects In A Long Sequence, Ken C. K. Lee, Wang-Chien Lee, Donna Peuquet, Baihua Zheng
Searching Correlated Objects In A Long Sequence, Ken C. K. Lee, Wang-Chien Lee, Donna Peuquet, Baihua Zheng
Research Collection School Of Computing and Information Systems
Sequence, widely appearing in various applications (e.g. event logs, text documents, etc) is an ordered list of objects. Exploring correlated objects in a sequence can provide useful knowledge among the objects, e.g., event causality in event log and word phrases in documents. In this paper, we introduce correlation query that finds correlated pairs of objects often appearing closely to each other in a given sequence. A correlation query is specified by two control parameters, distance bound, the requirement of object closeness, and correlation threshold, the minimum requirement of correlation strength of result pairs. Instead of processing the query by scanning …
Spreadsheet Modeling Of Equipment Acquisition Plan, Thin Yin Leong, Michelle L. F. Cheong
Spreadsheet Modeling Of Equipment Acquisition Plan, Thin Yin Leong, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Excel spreadsheets have been used in many classrooms to teach modeling and analysis of real business problems. This can be done with relative ease but often the modeling approach may be inappropriate and the analysis results not easily implemented. In this article, we illustrate these difficulties with the modeling of the number of equipment required in future years, given demand (historical and projected) and the amount of equipment held. We show how the desired output can be, and needs to be related to the given input. For this purpose, we apply the TREND function to predict data into future years. …
Searching Blogs And News: A Study On Popular Queries, Aixin Sun, Meishan Hu, Ee Peng Lim
Searching Blogs And News: A Study On Popular Queries, Aixin Sun, Meishan Hu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Blog/news search engines are very important channels to reach information about the real-time happenings. In this paper, we study the popular queries collected over one year period and compare their search results returned by a blog search engine (i.e., Technorati) and a news search engine (i.e., Google News). We observed that the numbers of hits returned by the two search engines for the same set of queries were highly correlated, suggesting that blogs often provide commentary to current events reported in news. As many popular queries are related to some events, we further observed a high cohesiveness among the returned …
Tree-Based Partition Querying: A Methodology For Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Tree-Based Partition Querying: A Methodology For Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Research Collection School Of Computing and Information Systems
Besides traditional domains (e.g., resource allocation, data mining applications), algorithms for medoid computation and related problems will play an important role in numerous emerging fields, such as location based services and sensor networks. Since the k-medoid problem is NP hard, all existing work deals with approximate solutions on relatively small datasets. This paper aims at efficient methods for very large spatial databases, motivated by: (i) the high and ever increasing availability of spatial data, and (ii) the need for novel query types and improved services. The proposed solutions exploit the intrinsic grouping properties of a data partition index in order …
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
Research Collection School Of Computing and Information Systems
This paper presents a framework for engineering resource-adaptive software systems targeted at small mobile devices. The proposed framework empowers users to control tradeoffs among a rich set of ervicespecific aspects of quality of service. After motivating the problem, the paper proposes a model for capturing user preferences with respect to quality of service, and illustrates prototype user interfaces to elicit such models. The paper then describes the extensions and integration work made to accommodate the proposed framework on top of an existing software infrastructure for ubiquitous computing. The research question addressed here is the feasibility of coordinating resource allocation and …
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A number of kernel learning algorithms have been proposed to learn kernel functions or matrices from side information (e.g., either labeled examples or pairwise constraints). However, most previous studies are limited to “passive” kernel learning in which side information is provided beforehand. In this paper we present a framework of Active Kernel Learning (AKL) that actively identifies the most informative pairwise constraints for kernel learning. The key challenge of active kernel learning is how to measure the informativeness of an example pair given its …
Bounded Model Checking Of Compositional Processes, Jun Sun, Yang Liu, Jin Song Dong, Jing Sun
Bounded Model Checking Of Compositional Processes, Jun Sun, Yang Liu, Jin Song Dong, Jing Sun
Research Collection School Of Computing and Information Systems
Verification techniques like SAT-based bounded model checking have been successfully applied to a variety of system models. Applying bounded model checking to compositional process algebras is, however, not a trivial task. One challenge is that the number of system states for process algebra models is not statically known, whereas exploring the full state space is computationally expensive. This paper presents a compositional encoding of hierarchical processes as SAT problems and then applies state-of-the-art SAT solvers for bounded model checking. The encoding avoids exploring the full state space for complex systems so as to deal with state space explosion. We developed …
Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Research Collection School Of Computing and Information Systems
Even today, software projects still suffer from delays and budget overspending. The causes for this problem are compounded when the project team is distributed across different locations and generally attributed to the decreasing ability to communicate well (due to cultural, linguistic, and physical distance). Many projects, especially those with off-shoring component, consist of small iterations with changes, deletions and additions, yet there is no formal model of the flow of iterations available. A number of commercially available project prediction tools for projects as a whole exist, but the model adaptation process by iteration, if it exists, is unclear. Furthermore, no …