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Research Collection School Of Computing and Information Systems

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Articles 2881 - 2910 of 3436

Full-Text Articles in Databases and Information Systems

An Examination Of Online Product Comparison Service: Fit Between Product Type And Disposition Style, Fiona Fui-Hoon Nah, W. Hong, L. Chen, H. Lee Jul 2007

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.

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Appraisal - Who Needs It?, M. Thulasidas Jul 2007

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.

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Is Interpersonal Trust A Necessary Condition For Organisational Learning?, Siu Loon Hoe Jul 2007

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 …

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Learning Causal Models For Noisy Biological Data Mining: An Application To Ovarian Cancer Detection, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang Jul 2007

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 …

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Continuous Monitoring Of Top-K Queries Over Sliding Windows, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias Jul 2007

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 …

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Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo Jul 2007

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 …

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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 Jul 2007

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 …

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Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis Jul 2007

Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

In the k-medoid problem, given a dataset P, we are asked to choose kpoints in P as the medoids. The optimal medoid set minimizes the average Euclidean distance between the points in P and their closest medoid. Finding the optimal k medoids is NP hard, and existing algorithms aim at approximate answers, i.e., they compute medoids that achieve a small, yet not minimal, average distance. Similarly in this paper, we also aim at approximate solutions. We consider, however, the continuous version of the problem, where the points in P move and our task is to maintain the medoid set on-the-fly …

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Analyzing Feature Trajectories For Event Detection, Qi He, Kuiyu Chang, Ee Peng Lim Jul 2007

Analyzing Feature Trajectories For Event Detection, Qi He, Kuiyu Chang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

We consider the problem of analyzing word trajectories in both time and frequency domains, with the specific goal of identifying important and less-reported, periodic and aperiodic words. A set of words with identical trends can be grouped together to reconstruct an event in a completely un-supervised manner. The document frequency of each word across time is treated like a time series, where each element is the document frequency - inverse document frequency (DFIDF) score at one time point. In this paper, we 1) first applied spectral analysis to categorize features for different event characteristics: important and less-reported, periodic and aperiodic; …

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Similarity Beyond Distance Measurement, Feng Kang, Rong Jin, Steven C. H. Hoi Jun 2007

Similarity Beyond Distance Measurement, Feng Kang, Rong Jin, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

One of the keys issues to content-based image retrieval is the similarity measurement of images. Images are represented as points in the space of low-level visual features and most similarity measures are based on certain distance measurement between these features. Given a distance metric, two images with shorter distance are deemed to more similar than images that are far away. The well-known problem with these similarity measures is the semantic gap, namely two images separated by large distance could share the same semantic content. In this paper, we propose a novel similarity measure of images that goes beyond the distance …

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A Multi-Scale Tikhonov Regularization Scheme For Implicit Surface Modeling, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu Jun 2007

A Multi-Scale Tikhonov Regularization Scheme For Implicit Surface Modeling, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Kernel machines have recently been considered as a promising solution for implicit surface modelling. A key challenge of machine learning solutions is how to fit implicit shape models from large-scale sets of point cloud samples efficiently. In this paper, we propose a fast solution for approximating implicit surfaces based on a multi-scale Tikhonov regularization scheme. The optimization of our scheme is formulated into a sparse linear equation system, which can be efficiently solved by factorization methods. Different from traditional approaches, our scheme does not employ auxiliary off-surface points, which not only saves the computational cost but also avoids the problem …

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Intelligence Through Interaction: Towards A Unified Theory For Learning, Ah-Hwee Tan, Gail A. Carpenter, Stephen Grossberg Jun 2007

Intelligence Through Interaction: Towards A Unified Theory For Learning, Ah-Hwee Tan, Gail A. Carpenter, Stephen Grossberg

Research Collection School Of Computing and Information Systems

Machine learning, a cornerstone of intelligent systems, has typically been studied in the context of specific tasks, including clustering (unsupervised learning), classification (supervised learning), and control (reinforcement learning). This paper presents a learning architecture within which a universal adaptation mechanism unifies a rich set of traditionally distinct learning paradigms, including learning by matching, learning by association, learning by instruction, and learning by reinforcement. In accordance with the notion of embodied intelligence, such a learning theory provides a computational account of how an autonomous agent may acquire the knowledge of its environment in a real-time, incremental, and continuous manner. Through a …

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The Multi-Agent Data Collection In Hla-Based Simulation System, Heng-Jie Song, Zhi-Qi Shen, Chunyan Miao, Ah-Hwee Tan, Guo-Peng Zhao Jun 2007

The Multi-Agent Data Collection In Hla-Based Simulation System, Heng-Jie Song, Zhi-Qi Shen, Chunyan Miao, Ah-Hwee Tan, Guo-Peng Zhao

Research Collection School Of Computing and Information Systems

The High Level Architecture (HLA) for distributed simulation was proposed by the Defense Modeling and Simulation Office of the Department of Defense (DOD) in order to support interoperability among simulations as well as reuse of simulation models. One aspect of reusability is to collect and analyze data generated in simulation exercises, including a record of events that occur during the execution, and the states of simulation objects. In order to improve the performance of existing data collection mechanisms in the HLA simulation system, the paper proposes a multi-agent data collection system. The proposed approach adopts the hierarchical data management/organization mechanism …

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Continuous Nearest Neighbor Queries Over Sliding Windows, Kyriakos Mouratidis, Dimitris Papadias Jun 2007

Continuous Nearest Neighbor Queries Over Sliding Windows, Kyriakos Mouratidis, Dimitris Papadias

Research Collection School Of Computing and Information Systems

Recent research has focused on continuous monitoring of nearest neighbors (NN) in highly dynamic scenarios, where the queries and the data objects move frequently and arbitrarily. All existing methods, however, assume the Euclidean distance metric. In this paper we study k-NN monitoring in road networks, where the distance between a query and a data object is determined by the length of the shortest path connecting them. We propose two methods that can handle arbitrary object and query moving patterns, as well as fluctuations of edge weights. The first one maintains the query results by processing only updates that may invalidate …

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Can Uml Be Simplified? Practitioner Use Of Uml In Separate Domains, J. Erickson, Keng Siau Jun 2007

Can Uml Be Simplified? Practitioner Use Of Uml In Separate Domains, J. Erickson, Keng Siau

Research Collection School Of Computing and Information Systems

UML’s complexity is regularly criticized by practitioners and researchers alike, who argue that such complexity is a considerable detriment to the adoption and use of UML in the field. Attempts have been made to assess and/or measure UML’s complexity in a number of ways. Erickson and Siau proposed that a subset (kernel) of UML, composed of the most important constructs, could be equated with the complexity that practitioners face when using the modeling language. This research extends Erickson and Siau’s work by proposing a UML kernel in three application areas, real-time, webbased and enterprise systems. Compared to other modeling methods …

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Learning Nonparametric Kernel Matrices From Pairwise Constraints, Steven C. H. Hoi, Rong Jin, Michael R. Lyu Jun 2007

Learning Nonparametric Kernel Matrices From Pairwise Constraints, Steven C. H. Hoi, Rong Jin, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Many kernel learning methods have to assume parametric forms for the target kernel functions, which significantly limits the capability of kernels in fitting diverse patterns. Some kernel learning methods assume the target kernel matrix to be a linear combination of parametric kernel matrices. This assumption again importantly limits the flexibility of the target kernel matrices. The key challenge with nonparametric kernel learning arises from the difficulty in linking the nonparametric kernels to the input patterns. In this paper, we resolve this problem by introducing the graph Laplacian of the observed data as a regularizer when optimizing the kernel matrix with …

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A Hybrid Of Plot-Based And Character-Based Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen Jun 2007

A Hybrid Of Plot-Based And Character-Based Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen

Research Collection School Of Computing and Information Systems

Interactive storytelling in the virtual environment attracts a lot of research interests in recent years. Story plot and character are two most important elements of a story. Based on these two elements, currently there are two research directions: plot-based and character-based interactive storytelling. However, plot-based approach lacks the refinement of character behaviors as character-based approach. On the other side, character-based approach does not follow a well organized story plot so that the moral of the story might be distorted. Therefore, there is a need to develop an integrated framework to achieve the balance between conveying story moral and enhancing the …

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Assessing Organizational Innovation Capability And Its Effect On E-Commerce Initiatives, Ann L. Fruhling, Keng Siau Jun 2007

Assessing Organizational Innovation Capability And Its Effect On E-Commerce Initiatives, Ann L. Fruhling, Keng Siau

Research Collection School Of Computing and Information Systems

This research uses a qualitative approach to study the innovative capability of two organizations and the effect of innovation on their E-Commerce initiatives, strategies, and outcomes. The Innovation Strategy Model is used in this research to analyze the innovative capability of two organizations. The case study research methodology was selected and two case studies are presented. The research results show that one organization is more innovative than the other in terms of its innovative capability. A post-study follow-up shows that the organization that was high on innovative capability was very successful in their E-Commerce initiative whereas the other organization was …

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Instance Weighting For Domain Adaptation In Nlp, Jing Jiang, Chengxiang Zhai Jun 2007

Instance Weighting For Domain Adaptation In Nlp, Jing Jiang, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

Domain adaptation is an important problem in natural language processing (NLP) due to the lack of labeled data in novel domains. In this paper, we study the domain adaptation problem from the instance weighting per- spective. We formally analyze and charac- terize the domain adaptation problem from a distributional view, and show that there are two distinct needs for adaptation, cor- responding to the different distributions of instances and classification functions in the source and the target domains. We then propose a general instance weighting frame- work for domain adaptation. Our empir- ical results on three NLP tasks show that …

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Mobile G-Portal Supporting Collaborative Sharing And Learning In Geography Fieldwork: An Empirical Study, Yin-Leng Theng, Kuah-Li Tan, Ee Peng Lim, Jun Zhang, Dion Hoe-Lian Goh, Kalyani Chatterjea, Chew-Hung Chang, Aixin Sun, Han Yu, Nam Hai Dang, Yuanyuan Li, Minh Chanh Vo Jun 2007

Mobile G-Portal Supporting Collaborative Sharing And Learning In Geography Fieldwork: An Empirical Study, Yin-Leng Theng, Kuah-Li Tan, Ee Peng Lim, Jun Zhang, Dion Hoe-Lian Goh, Kalyani Chatterjea, Chew-Hung Chang, Aixin Sun, Han Yu, Nam Hai Dang, Yuanyuan Li, Minh Chanh Vo

Research Collection School Of Computing and Information Systems

Integrated with G-Portal, a Web-based geospatial digital library of geography resources, this paper describes the implementation of Mobile G-Portal, a group of mobile devices as learning assistant tools supporting collaborative sharing and learning for geography fieldwork. Based on a modified Technology Acceptance Model and a Task-Technology Fit model, an initial study with Mobile G-Portal was conducted involving 39 students in a local secondary school. The findings suggested positive indication of acceptance of Mobile G-Portal for geography fieldwork. The paper concludes with a discussion on technological challenges, recommendations for refinement of Mobile G-Portal, and design implications in general for digital libraries …

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Gprune: A Constraint Pushing Framework For Graph Pattern Mining, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu May 2007

Gprune: A Constraint Pushing Framework For Graph Pattern Mining, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu

Research Collection School Of Computing and Information Systems

In graph mining applications, there has been an increasingly strong urge for imposing user-specified constraints on the mining results. However, unlike most traditional itemset constraints, structural constraints, such as density and diameter of a graph, are very hard to be pushed deep into the mining process. In this paper, we give the first comprehensive study on the pruning properties of both traditional and structural constraints aiming to reduce not only the pattern search space but the data search space as well. A new general framework, called gPrune, is proposed to incorporate all the constraints in such a way that they …

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Analysis Of Topological Characteristics Of Huge Online Social Networking Services, Yong-Yeol Ahn, Seungyeop Han, Haewoon Kwak, Sue Moon, Hawoong Jeong May 2007

Analysis Of Topological Characteristics Of Huge Online Social Networking Services, Yong-Yeol Ahn, Seungyeop Han, Haewoon Kwak, Sue Moon, Hawoong Jeong

Research Collection School Of Computing and Information Systems

Social networking services are a fast-growing business in the Internet. However, it is unknown if online relationships and their growth patterns are the same as in real-life social networks. In this paper, we compare the structures of three online social networking services: Cyworld, MySpace, and orkut, each with more than 10 million users, respectively. We have access to complete data of Cyworld's ilchon (friend) relationships and analyze its degree distribution, clustering property, degree correlation, and evolution over time. We also use Cyworld data to evaluate the validity of snowball sampling method, which we use to crawl and obtain partial network …

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Cognitive Evaluation Of Information Modeling Methods, Keng Siau, Yuan Wang May 2007

Cognitive Evaluation Of Information Modeling Methods, Keng Siau, Yuan Wang

Research Collection School Of Computing and Information Systems

In the field of information system engineering, information modeling method is a technique to capture user requirements and to understand system complexity. The importance of information modeling has been recognized by practitioners and researchers, but little has been explored to analyze the available information modeling methods or to evaluate them in terms of their strengths, weaknesses, and effectiveness. This research analyzes six information-modeling methods: use case diagram, rich picture diagram, entity-relationship diagram, Trochim’s concept mapping, repertory grid, and causal mapping. These information-modeling methods are analyzed from a cognitive perspective in order to better understand their nature, the assumptions, and the …

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Learning To Classify E-Mail, Irena Koprinska, Josiah Poon, James Clark, Jason Yuk Hin Chan May 2007

Learning To Classify E-Mail, Irena Koprinska, Josiah Poon, James Clark, Jason Yuk Hin Chan

Research Collection School Of Computing and Information Systems

In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a supervised learning setting, we investigate the use of random forest for automatic e-mail filing into folders and spam e-mail filtering. We show that random forest is a good choice for these tasks as it runs fast on large and high dimensional databases, is easy to tune and is highly accurate, outperforming popular algorithms such as decision trees, support vector machines and naive Bayes. We introduce a new accurate feature selector with linear time complexity. …

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Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau Apr 2007

Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau

Research Collection School Of Computing and Information Systems

Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a corel periphery model as the projects …

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A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu Apr 2007

A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

One critical task in content-based video retrieval is to rank search results with combinations of multimodal resources effectively. This paper proposes a novel multimodal and multilevel ranking framework for content-based video retrieval. The main idea of our approach is to represent videos by graphs and learn harmonic ranking functions through fusing multimodal resources over these graphs smoothly. We further tackle the efficiency issue by a multilevel learning scheme, which makes the semi-supervised ranking method practical for large-scale applications. Our empirical evaluations on TRECVID 2005 dataset show that the proposed multimodal and multilevel ranking framework is effective and promising for content-based …

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A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu Apr 2007

A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

One critical task in content-based video retrieval is to rank search results with combinations of multimodal resources effectively. This paper proposes a novel multimodal and multilevel ranking framework for content-based video retrieval. The main idea of our approach is to represent videos by graphs and learn harmonic ranking functions through fusing multimodal resources over these graphs smoothly. We further tackle the efficiency issue by a multilevel learning scheme, which makes the semi-supervised ranking method practical for large-scale applications. Our empirical evaluations on TRECVID 2005 dataset show that the proposed multimodal and multilevel ranking framework is effective and promising for content-based …

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Mining Colossal Frequent Patterns By Core Pattern Fusion, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, Hong Cheng Apr 2007

Mining Colossal Frequent Patterns By Core Pattern Fusion, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, Hong Cheng

Research Collection School Of Computing and Information Systems

Extensive research for frequent-pattern mining in the past decade has brought forth a number of pattern mining algorithms that are both effective and efficient. However, the existing frequent-pattern mining algorithms encounter challenges at mining rather large patterns, called colossal frequent patterns, in the presence of an explosive number of frequent patterns. Colossal patterns are critical to many applications, especially in domains like bioinformatics. In this study, we investigate a novel mining approach called Pattern-Fusion to efficiently find a good approximation to the colossal patterns. With Pattern-Fusion, a colossal pattern is discovered by fusing its small core patterns in one step, …

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Summarizing Review Scores Of "Unequal" Reviewers, Hady W. Lauw, Ee Peng Lim, Ke Wang Apr 2007

Summarizing Review Scores Of "Unequal" Reviewers, Hady W. Lauw, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

A frequently encountered problem in decision making is the following review problem: review a large number of objects and select a small number of the best ones. An example is selecting conference papers from a large number of submissions. This problem involves two sub-problems: assigning reviewers to each object, and summarizing reviewers ’ scores into an overall score that supposedly reflects the quality of an object. In this paper, we address the score summarization sub-problem for the scenario where a small number of reviewers evaluate each object. Simply averaging the scores may not work as even a single reviewer could …

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Valuing Information Technology Infrastructures: A Growth Options Approach, Qizhi Dai, Robert J. Kauffman, Salvatore T. March Mar 2007

Valuing Information Technology Infrastructures: A Growth Options Approach, Qizhi Dai, Robert J. Kauffman, Salvatore T. March

Research Collection School Of Computing and Information Systems

Decisions to invest in information technology (IT) infrastructure are often made based on an assessment of its immediate value to the organization. However, an important source of value comes from the fact that such technologies have the potential to be leveraged in the development of future applications. From a real options perspective, IT infrastructure investments create growth options that can be exercised if and when an organization decides to develop systems to provide new or enhanced IT capabilities. We present an analytical model based on real options that shows the process by which this potential is converted into business value, …

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