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Articles 8011 - 8040 of 9003
Full-Text Articles in Computer Sciences
Mapping Better Business Strategies With Gis, Tin Seong Kam
Mapping Better Business Strategies With Gis, Tin Seong Kam
Research Collection School Of Computing and Information Systems
The value of location as a business measure is fast becoming an important consideration for organisations. GIS (Geographical Information Systems), with its capability to manage, display, analyse business information spatially, is emerging as a powerful location intelligence tool. In the US, Starbucks, Blockbuster, Hyundai, and thousands of other businesses use census data and GIS software to help them understand what types of people buy their products and services, and how to better market to these consumers. For example, McDonald’s in Japan uses a GIS system to overlay demographic information on maps to help identify promising new store sites. Singapore Management …
Predicting Coronary Artery Disease With Medical Profile And Gene Polymorphisms Data, Qiongyu Chen, Guoliang Li, Tze-Yun Leong, Chew-Kiat Heng
Predicting Coronary Artery Disease With Medical Profile And Gene Polymorphisms Data, Qiongyu Chen, Guoliang Li, Tze-Yun Leong, Chew-Kiat Heng
Research Collection School Of Computing and Information Systems
Coronary artery disease (CAD) is a main cause of death in the world. Finding cost-effective methods to predict CAD is a major challenge in public health. In this paper, we investigate the combined effects of genetic polymorphisms and non-genetic factors on predicting the risk of CAD by applying well known classification methods, such as Bayesian networks, naïve Bayes, support vector machine, k-nearest neighbor, neural networks and decision trees. Our experiments show that all these classifiers are comparable in terms of accuracy, while Bayesian networks have the additional advantage of being able to provide insights into the relationships among the variables. …
An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair
An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair
Research Collection School Of Computing and Information Systems
Grammar checking and correction comprise of the primary problems in the area of Natural Language Processing (NLP). Traditional approaches fall into two major categories: Rule based and Corpus based. While the former relies heavily on grammar rules the latter approach is statistical in nature. We provide a novel corpus based approach for grammar checking that uses the principles of an Artificial Immune System (AIS).We treat grammatical error as pathogens (in immunological terms) and build antibody detectors capable of detecting grammatical errors while allowing correct constructs to filter through. Our results show that it is possible to detect a range of …
Are You Too Smart For Your Own Good?, M. Thulasidas
Are You Too Smart For Your Own Good?, M. Thulasidas
Research Collection School Of Computing and Information Systems
Knowledge can be a bad thing, if others are taking credit for it. TECHNICAL knowledge is not always a good thing for you in the modern workplace.
Re-Engineering Xid Technologies - From Enterprise To Consumer Markets, Arcot Desai Narasimhalu
Re-Engineering Xid Technologies - From Enterprise To Consumer Markets, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
Several studies have addressed the process of taking ideas to markets but few have shared the experiences of start up companies that have reexamined their product strategies and repositioned their products and services for better revenues and profits. This paper reports the efforts related to repositioning of XID technologies, a start up company, into new markets while continuing to exploit its core technical competencies.
Designing The Value Curve For Your Next Innovation, Arcot Desai Narasimhalu
Designing The Value Curve For Your Next Innovation, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
This paper introduces an additional feature to the strategy canvas and value curve that will make innovation designers more effective. The new feature is to let the innovators carry out the designs of their new innovations taking into account both the cost of improving the quality of a parameter that the users value highly and the savings accrued from the drop in provisioning for parameters that users place less emphasis in an innovation.
Cost-Time Sensitive Decision Tree With Missing Values, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang
Cost-Time Sensitive Decision Tree With Missing Values, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang
Research Collection School Of Computing and Information Systems
Cost-sensitive decision tree learning is very important and popular in machine learning and data mining community. There are many literatures focusing on misclassification cost and test cost at present. In real world application, however, the issue of time-sensitive should be considered in cost-sensitive learning. In this paper, we regard the cost of time-sensitive in cost-sensitive learning as waiting cost (referred to WC), a novelty splitting criterion is proposed for constructing cost-time sensitive (denoted as CTS) decision tree for maximal decrease the intangible cost. And then, a hybrid test strategy that combines the sequential test with the batch test strategies is …
A Genetic Algorithm For Cellular Manufacturing Design And Layout, Xiaodan Wu, Chao-Hsien Chu, Yunfeng Wang, Weili Yan
A Genetic Algorithm For Cellular Manufacturing Design And Layout, Xiaodan Wu, Chao-Hsien Chu, Yunfeng Wang, Weili Yan
Research Collection School Of Computing and Information Systems
Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisions should be addressed simultaneously in order to obtain the best results. However, due to the complexity and NP-complete nature of each decision and the limitations of traditional approaches, most researchers have only addressed these decisions sequentially or independently. In this study, a hierarchical genetic algorithm is developed to simultaneously form manufacturing cells and determine the group …
A Lateral Symmetry Approach To Percentage-Based Hybrid Pattern (Php) Training, Sheng-Uei Guan, Kiruthika Ramanathan
A Lateral Symmetry Approach To Percentage-Based Hybrid Pattern (Php) Training, Sheng-Uei Guan, Kiruthika Ramanathan
Research Collection School Of Computing and Information Systems
In this paper, we investigate the application of lateral symmetry to supervised learning using genetic algorithms. The hypothesis is motivated by the presence of symmetry in the animal brain and by research results showing approximately equal task division between the two hemispheres of the brain. In this paper, each training pattern is considered a task. By applying the concept of lateral symmetry, we use global training (a typically right brained activity) to learn half the tasks and local training (a left brained activity) to learn the rest of the tasks. We verified the use of this Percentage-based Pattern (PHP) training …
Near-Duplicate Keyframe Identification With Interest Point Matching And Pattern Learning, Wan-Lei Zhao, Chong-Wah Ngo, Hung-Khoon Tan, Xiao Wu
Near-Duplicate Keyframe Identification With Interest Point Matching And Pattern Learning, Wan-Lei Zhao, Chong-Wah Ngo, Hung-Khoon Tan, Xiao Wu
Research Collection School Of Computing and Information Systems
This paper proposes a new approach for near-duplicate keyframe (NDK) identification by matching, filtering and learning of local interest points (LIPs) with PCA-SIFT descriptors. The issues in matching reliability, filtering efficiency and learning flexibility are novelly exploited to delve into the potential of LIP-based retrieval and detection. In matching, we propose a one-to-one symmetric matching (OOS) algorithm which is found to be highly reliable for NDK identification, due to its capability in excluding false LIP matches compared with other matching strategies. For rapid filtering, we address two issues: speed efficiency and search effectiveness, to support OOS with a new index …
Measuring Knowledge Sharing In Open Source Software Development Teams, Y. Long, Keng Siau, K. Howell
Measuring Knowledge Sharing In Open Source Software Development Teams, Y. Long, Keng Siau, K. Howell
Research Collection School Of Computing and Information Systems
The study provides an approach to measure the extent of knowledge sharing in Open Source Software (OSS) development in terms of two aspects: the quality of knowledge sharing which is indicated by the helpfulness of the messages, and the quantity of knowledge sharing which is indicated by the volume of the messages. The study developed a computer-aided content analysis program to assess the helpfulness of the messages based on a set of keywords and the length of the messages. The approach was applied to measure the extent of knowledge sharing of 150 OSS projects. The results further confirmed that the …
Design Science Research On Systems Analysis And Design: The Case Of Uml, X. Tan, Keng Siau, J. Erickson
Design Science Research On Systems Analysis And Design: The Case Of Uml, X. Tan, Keng Siau, J. Erickson
Research Collection School Of Computing and Information Systems
Design science in the IS discipline seeks to create artifacts that embody the ideas, practices, technical capabilities, and products required to efficiently accomplish the analysis, design, implementation, and use of information systems (Hevner et al 2006). SA&D research, being close to the design science paradigm, has suffered from a lack of appreciation from the behavioral science paradigm. To provide a paradigmatic foundation, we propose a conceptual framework for SA&D research. The framewor was developed based on several essays that systematically articulate the design science paradigm in the IS field. Using this framework, we reviewed some UML papers that appeared in …
An Augmented Approach To Support Collaborative Distance Learning Of Unified Modeling Language, Keng Siau, Fiona Fui-Hoon Nah, Brenda Eschenbrenner, Ashu Guru
An Augmented Approach To Support Collaborative Distance Learning Of Unified Modeling Language, Keng Siau, Fiona Fui-Hoon Nah, Brenda Eschenbrenner, Ashu Guru
Research Collection School Of Computing and Information Systems
Teaching in the classroom faces many challenges of providing a collaborative, interactive environment that effectively facilitates students’ learning. The challenges increase when the physical classroom converts into a virtual classroom. This difficulty is further exacerbated when the course is diagramming intensive, practice-oriented, and hands-on in nature. Technology has been sought after to help with these challenges. Web Conferencing software, when compared to Web Broadcasting software, can facilitate real-time interaction and collaboration in a distance learning context. For courses that are diagramming intensive and practice-oriented, Tablet PCs, when compared to desktop PCs, can support drawing and diagramming because of the ability …
Theoretical And Practical Complexity Of Modeling Methods, John Erickson, Keng Siau
Theoretical And Practical Complexity Of Modeling Methods, John Erickson, Keng Siau
Research Collection School Of Computing and Information Systems
The estimation of theoretical and practical complexity of a system development method is discussed. Executable model capability allow developers to transform models developed during the Systems Analysis and Design portion of the systems development process into working applications. Systems are becoming more complex mostly because of influencing factors such as required and enhanced functionality, interoperability, and security. Other trends that impact the complexity of applications include systems such as enterprise resource planning, supply chain management, and customer relationship management. These types of systems are very large and complex and require close internal cooperation for the implementing organizations individually and also …
Century: Automated Aspects Of Patient Care, Marion Blount, John Davis, Maria Ebling, Ji Hyun Kim, Kyun Hyun Kim, Kang Yoon Lee, Archan Misra, Se Hun Park, Daby Sow, Young Ju Tak, Min Wang, Karen Witting
Century: Automated Aspects Of Patient Care, Marion Blount, John Davis, Maria Ebling, Ji Hyun Kim, Kyun Hyun Kim, Kang Yoon Lee, Archan Misra, Se Hun Park, Daby Sow, Young Ju Tak, Min Wang, Karen Witting
Research Collection School Of Computing and Information Systems
Remote health monitoring affords the possibility of improving the quality of health care by enabling relatively inexpensive out-patient care. However, remote health monitoring raises new a problem: the potential for data explosion in health care systems. To address this problem, the remote health monitoring systems must be integrated with analysis tools that provide automated trend analysis and event detection in real time. In this paper, we propose an overview of Century, an extensible framework for analysis of large numbers of remote sensor-based medical data streams.
On Searching Continuous Nearest Neighbors In Wireless Data Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee
On Searching Continuous Nearest Neighbors In Wireless Data Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee
Research Collection School Of Computing and Information Systems
A continuous nearest neighbor (CNN) search, which retrieves the nearest neighbors corresponding to every point in a given query line segment, is important for location-based services such as vehicular navigation and tourist guides. It is infeasible to answer a CNN search by issuing a traditional nearest neighbor query at every point of the line segment due to the large number of queries generated and the overhead on bandwidth. Algorithms have been proposed recently to support CNN search in the traditional client-server systems but not in the environment of wireless data broadcast, where uplink communication channels from mobile devices to the …
An Empirical Study On Large-Scale Content-Based Image Retrieval, Yuk Man Wong, Steven C. H. Hoi, Michael R. Lyu
An Empirical Study On Large-Scale Content-Based Image Retrieval, Yuk Man Wong, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
One key challenge in content-based image retrieval (CBIR) is to develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems. In this paper, we propose a scalable content-based image retrieval scheme using locality-sensitive hashing (LSH), and conduct extensive evaluations on a large image testbed of a half million images. To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building Web-scale …
Discovering And Exploiting Causal Dependencies For Robust Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Discovering And Exploiting Causal Dependencies For Robust Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Acquisition of context poses unique challenges to mobile context-aware recommender systems. The limited resources in these systems make minimizing their context acquisition a practical need, and the uncertainty in the mobile environment makes missing and erroneous context inputs a major concern. In this paper, we propose an approach based on Bayesian networks (BNs) for building recommender systems that minimize context acquisition. Our learning approach iteratively trims the BN-based context model until it contains only the minimal set of context parameters that are important to a user. In addition, we show that a two-tiered context model can effectively capture the causal …
Efficient Near-Duplicate Keyframe Retrieval With Visual Language Models, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Efficient Near-Duplicate Keyframe Retrieval With Visual Language Models, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Near-duplicate keyframe retrieval is a critical task for video similarity measure, video threading and tracking. In this paper, instead of using expensive point-to-point matching on keypoints, we investigate the visual language models built on visual keywords to speed up the near-duplicate keyframe retrieval. The main idea is to estimate a visual language model on visual keywords for each keyframe and compare keyframes by the likelihood of their visual language models. Experiments on a subset of TRECVID-2004 video corpus show that visual language models built on visual keywords demonstrate promising performance for near-duplicate keyframe retrieval, which greatly speed up the retrieval …
An Examination Of Online Product Comparison Service: Fit Between Product Type And Disposition Style, Fiona Fui-Hoon Nah, W. Hong, L. Chen, H. Lee
An Examination Of Online Product Comparison Service: Fit Between Product Type And Disposition Style, Fiona Fui-Hoon Nah, W. Hong, L. Chen, H. Lee
Research Collection School Of Computing and Information Systems
Horizontal and vertical disposition styles are two main formats used in product comparison service on e-commerce websites. In this research, we hypothesize that there is a fit between product type (‘think’ vs. ‘feel’ product) and disposition style (horizontal vs. vertical style), where horizontal disposition style is more appropriate for ‘feel’ products and vertical disposition style is a better fit for ‘think’ products. An experiment will be carried out to test the hypotheses.
Appraisal - Who Needs It?, M. Thulasidas
Appraisal - Who Needs It?, M. Thulasidas
Research Collection School Of Computing and Information Systems
WE GO through this ordeal every year when our boss- es appraise our performance. Our career progression, bonus and salary depend on it. So, we spend sleepless nights agonising over it.
Improving Memory-Based Collaborative Filtering Using A Factor-Based Approach, Zhenxue Zhang, Dongsong Zhang, Zhiling Guo
Improving Memory-Based Collaborative Filtering Using A Factor-Based Approach, Zhenxue Zhang, Dongsong Zhang, Zhiling Guo
Research Collection School Of Computing and Information Systems
Collaborative Filtering (CF) systems generate recommendations for a user by aggregating item ratings of other like-minded users. The memory-based approach is a common technique used in CF. This approach first uses statistical methods such as Pearson’s Correlation Coefficient to measure user similarities based on their previous ratings on different items. Users will then be grouped into different neighborhood depending on the calculated similarities. Finally, the system will generate predictions on how a user would rate a specific item by aggregating ratings on the item cast by the identified neighbors of his/her. However, current memory-based CF method only measures user similarities …
Is Interpersonal Trust A Necessary Condition For Organisational Learning?, Siu Loon Hoe
Is Interpersonal Trust A Necessary Condition For Organisational Learning?, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
The organisational behaviour and management literature has devoted a lot attention on various factors affecting organisational learning. While there has been much work done to examine trust in promoting organisational learning, there is a lack of consensus on the specific type of trust involved. The purpose of this paper is to highlight the importance of interpersonal trust in promoting organisational learning and propose a research agenda to test the extent of interpersonal trust on organisational learning. This paper contributes to the existing organisational learning literature by specifying a specific form of trust, interpersonal trust, which promotes organisational learning and proposing …
Learning Causal Models For Noisy Biological Data Mining: An Application To Ovarian Cancer Detection, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Learning Causal Models For Noisy Biological Data Mining: An Application To Ovarian Cancer Detection, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Undetected errors in the expression measurements from highthroughput DNA microarrays and protein spectroscopy could seriously affect the diagnostic reliability in disease detection. In addition to a high resilience against such errors, diagnostic models need to be more comprehensible so that a deeper understanding of the causal interactions among biological entities like genes and proteins may be possible. In this paper, we introduce a robust knowledge discovery approach that addresses these challenges. First, the causal interactions among the genes and proteins in the noisy expression data are discovered automatically through Bayesian network learning. Then, the diagnosis of a disease based on …
Generating Job Schedules For Vessel Operations In A Container Terminal, Thin Yin Leong, Hoong Chuin Lau
Generating Job Schedules For Vessel Operations In A Container Terminal, Thin Yin Leong, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
No abstract provided.
Continuous Monitoring Of Top-K Queries Over Sliding Windows, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias
Continuous Monitoring Of Top-K Queries Over Sliding Windows, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias
Research Collection School Of Computing and Information Systems
Given a dataset P and a preference function f, a top-k query retrieves the k tuples in P with the highest scores according to f. Even though the problem is well-studied in conventional databases, the existing methods are inapplicable to highly dynamic environments involving numerous long-running queries. This paper studies continuous monitoring of top-k queries over a fixed-size window W of the most recent data. The window size can be expressed either in terms of the number of active tuples or time units. We propose a general methodology for top-k monitoring that restricts processing to the sub-domains of the workspace …
The Business Model Of "Software-As-A-Service", Dan Ma
The Business Model Of "Software-As-A-Service", Dan Ma
Research Collection School Of Computing and Information Systems
The emergence of the software-as-a-service (SaaS) business model has attracted great attentions from both researchers and practitioners. SaaS vendors deliver on-demand information processing services to users, and thus offer computing utility rather than the standalone software itself. In this work, the author propose an analytical model to study the competition between the SaaS and the traditional COTS (commercial off-the-shelf) solutions for software applications. The author show that when software applications become open, modulated, and standardized, the SaaS business model will take a significant market share. In addition, under certain market conditions, offering users an easy exit option through the software …
Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Near-duplicate keyframes (NDK) play a unique role in large-scale video search, news topic detection and tracking. In this paper, we propose a novel NDK retrieval approach by exploring both visual and textual cues from the visual vocabulary and semantic context respectively. The vocabulary, which provides entries for visual keywords, is formed by the clustering of local keypoints. The semantic context is inferred from the speech transcript surrounding a keyframe. We experiment the usefulness of visual keywords and semantic context, separately and jointly, using cosine similarity and language models. By linearly fusing both modalities, performance improvement is reported compared with the …
Towards Optimal Bag-Of-Features For Object Categorization And Semantic Video Retrieval, Yu-Gang Jiang, Chong-Wah Ngo, Jun Yang
Towards Optimal Bag-Of-Features For Object Categorization And Semantic Video Retrieval, Yu-Gang Jiang, Chong-Wah Ngo, Jun Yang
Research Collection School Of Computing and Information Systems
Bag-of-features (BoF) deriving from local keypoints has recently appeared promising for object and scene classification. Whether BoF can naturally survive the challenges such as reliability and scalability of visual classification, nevertheless, remains uncertain due to various implementation choices. In this paper, we evaluate various factors which govern the performance of BoF. The factors include the choices of detector, kernel, vocabulary size and weighting scheme. We offer some practical insights in how to optimize the performance by choosing good keypoint detector and kernel. For the weighting scheme, we propose a novel soft-weighting method to assess the significance of a visual word …
Cross-Lingual Query Suggestion Using Query Logs Of Different Languages, Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Jian Hu, Kam-Fai Wong, Hsiao-Wuen Hon
Cross-Lingual Query Suggestion Using Query Logs Of Different Languages, Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Jian Hu, Kam-Fai Wong, Hsiao-Wuen Hon
Research Collection School Of Computing and Information Systems
Query suggestion aims to suggest relevant queries for a given query, which help users better specify their information needs. Previously, the suggested terms are mostly in the same language of the input query. In this paper, we extend it to cross-lingual query suggestion (CLQS): for a query in one language, we suggest similar or relevant queries in other languages. This is very important to scenarios of cross-language information retrieval (CLIR) and cross-lingual keyword bidding for search engine advertisement. Instead of relying on existing query translation technologies for CLQS, we present an effective means to map the input query of one …