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Research Collection School Of Computing and Information Systems

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2005

Articles 31 - 47 of 47

Full-Text Articles in Databases and Information Systems

Mining Mobile Group Patterns: A Trajectory-Based Approach, San-Yih Hwang, Ying-Han Liu, Jeng-Kuen Chiu, Ee Peng Lim May 2005

Mining Mobile Group Patterns: A Trajectory-Based Approach, San-Yih Hwang, Ying-Han Liu, Jeng-Kuen Chiu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we present a group pattern mining approach to derive the grouping information of mobile device users based on a trajectory model. Group patterns of users are determined by distance threshold and minimum time duration. A trajectory model of user movement is adopted to save storage space and to cope with untracked or disconnected location data. To discover group patterns, we propose ATGP algorithm and TVG-growth that are derived from the Apriori and VG-growth algorithms respectively.

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Information Dissemination Via Wireless Broadcast, Baihua Zheng, Dik Lun Lee May 2005

Information Dissemination Via Wireless Broadcast, Baihua Zheng, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Unrestricted mobility adds a new dimension to data access methodology--- one that must be addressed before true ubiquity can be realized.

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Secure Human Communications Based On Biometrics Signals, Yongdong Wu, Feng Bao, Robert H. Deng May 2005

Secure Human Communications Based On Biometrics Signals, Yongdong Wu, Feng Bao, Robert H. Deng

Research Collection School Of Computing and Information Systems

User authentication is the first and probably the most challenging step in achieving secure person-to-person communications. Most of the existing authentication schemes require communicating parties either share a secret/password or know each other's public key. In this paper we suggest a novel user authentication scheme that is easy to use and overcomes the requirements of sharing password or public keys. Our scheme allows two human users to perform mutual authentication and have secure communications over an open channel by exchanging biometrics signals (e. g., voice or video signals). In addition to user authentication, our scheme establishes a secret session key …

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Dynamically-Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee-Hwa Pang May 2005

Dynamically-Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee-Hwa Pang

Research Collection School Of Computing and Information Systems

Traditional approaches to recommender systems have not taken into account situational information when making recommendations, and this seriously limits the relevance of the results. This paper advocates context-awareness as a promising approach to enhance the performance of recommenders, and introduces a mechanism to realize this approach. We present a framework that separates the contextual concerns from the actual recommendation module, so that contexts can be readily shared across applications. More importantly, we devise a learning algorithm to dynamically identify the optimal set of contexts for a specific recommendation task and user. An extensive series of experiments has validated that our …

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Event-Driven Document Selection For Terrorism, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Teng-Kwee Ong, Rohan Kumar Gunaratna May 2005

Event-Driven Document Selection For Terrorism, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Teng-Kwee Ong, Rohan Kumar Gunaratna

Research Collection School Of Computing and Information Systems

In this paper, we examine the task of extracting information about terrorism related events hidden in a large document collection. The task assumes that a terrorism related event can be described by a set of entity and relation instances. To reduce the amount of time and efforts in extracting these event related instances, one should ideally perform the task on the relevant documents only. We have therefore proposed some document selection strategies based on information extraction (IE) patterns. Each strategy attempts to select one document at a time such that the gain of event related instance information is maximized. Our …

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Dynamically Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang May 2005

Dynamically Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Traditional approaches to recommender systems have not taken into account situational information when making recommendations, and this seriously limits the relevance of the results. This paper advocates context-awareness as a promising approach to enhance the performance of recommenders, and introduces a mechanism to realize this approach. We present a framework that separates the contextual concerns from the actual recommendation module, so that contexts can be readily shared across applications. More importantly, we devise a learning algorithm to dynamically identify the optimal set of contexts for a specific recommendation task and user. An extensive series of experiments has validated that our …

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Tosa: A Near-Optimal Scheduling Algorithm For Multi-Channel Data Broadcast, Baihua Zheng, Xia Xu, Xing Jin, Dik Lun Lee May 2005

Tosa: A Near-Optimal Scheduling Algorithm For Multi-Channel Data Broadcast, Baihua Zheng, Xia Xu, Xing Jin, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Wireless broadcast is very suitable for delivering information to a large user population. In this paper, we concentrate on data allocation methods for multiple broadcast channels. To the best of our knowledge, this is the first allocation model that takes into the consideration of items' access frequencies, items' lengths. and bandwidth of different channels. We first derive the optimal average expected delay for multiple channels for the general case where data access frequencies, data sizes, and channel bandwidths can all be non-uniform. Second, we develop TOSA, a multi-channel allocation method that does not assume a uniform broadcast schedule for data …

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Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin Apr 2005

Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin

Research Collection School Of Computing and Information Systems

Relevance feedback has been shown as an important tool to boost the retrieval performance in content-based image retrieval. In the past decade, various algorithms have been proposed to formulate relevance feedback in contentbased image retrieval. Traditional relevance feedback techniques mainly carry out the learning tasks by focusing lowlevel visual features of image content with little consideration on log information of user feedback. However, from a long-term learning perspective, the user feedback log is one of the most important resources to bridge the semantic gap problem in image retrieval. In this paper we propose a novel technique to integrate the log …

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Predictive Neural Networks For Gene Expression Data Analysis, Ah-Hwee Tan, Hong Pan Apr 2005

Predictive Neural Networks For Gene Expression Data Analysis, Ah-Hwee Tan, Hong Pan

Research Collection School Of Computing and Information Systems

Gene expression data generated by DNA microarray experiments have provided a vast resource for medical diagnosis and disease understanding. Most prior work in analyzing gene expression data, however, focuses on predictive performance but not so much on deriving human understandable knowledge. This paper presents a systematic approach for learning and extracting rule-based knowledge from gene expression data. A class of predictive self-organizing networks known as Adaptive Resonance Associative Map (ARAM) is used for modelling gene expression data, whose learned knowledge can be transformed into a set of symbolic IF-THEN rules for interpretation. For dimensionality reduction, we illustrate how the system …

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Mining Social Network From Spatio-Temporal Events, Hady Wirawan Lauw, Ee Peng Lim, Teck Tim Tan, Hwee Hwa Pang Apr 2005

Mining Social Network From Spatio-Temporal Events, Hady Wirawan Lauw, Ee Peng Lim, Teck Tim Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Knowing patterns of relationship in a social network is very useful for law enforcement agencies to investigate collaborations among criminals, for businesses to exploit relationships to sell products, or for individuals who wish to network with others. After all, it is not just what you know, but also whom you know, that matters. However, finding out who is related to whom on a large scale is a complex problem. Asking every single individual would be impractical, given the huge number of individuals and the changing dynamics of relationships. Recent advancement in technology has allowed more data about activities of individuals …

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Proactive Caching For Spatial Queries In Mobile Environments, Haibo Hu, Jianliang Xu, Wing Sing Wong, Baihua Zheng, Dik Lun Lee, Wang-Chien Lee Apr 2005

Proactive Caching For Spatial Queries In Mobile Environments, Haibo Hu, Jianliang Xu, Wing Sing Wong, Baihua Zheng, Dik Lun Lee, Wang-Chien Lee

Research Collection School Of Computing and Information Systems

Semantic caching enables mobile clients to answer spatial queries locally by storing the query descriptions together with the results. However, it supports only a limited number of query types, and sharing results among these types is difficult. To address these issues, we propose a proactive caching model which caches the result objects as well as the index that supports these objects as the results. The cached index enables the objects to be reused for all common types of queries. We also propose an adaptive scheme to cache such an index, which further optimizes the query response time for the best …

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Scheduling Queries To Improve The Freshness Of A Website, Haifeng Liu, Wee-Keong Ng, Ee Peng Lim Mar 2005

Scheduling Queries To Improve The Freshness Of A Website, Haifeng Liu, Wee-Keong Ng, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The World Wide Web is a new advertising medium that corporations use to increase their exposure to consumers. Very large websites whose content is derived from a source database need to maintain a freshness that reflects changes that are made to the base data. This issue is particularly significant for websites that present fast-changing information such as stock-exchange information and product information. In this article, we formally define and study the freshness of a website that is refreshed by a scheduled set of queries that fetch fresh data from the databases. We propose several online-scheduling algorithms and compare the performance …

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Evaluation Of Mpeg-4 Ipmp Extension, Hwee Hwa Pang, Yongdong Wu Mar 2005

Evaluation Of Mpeg-4 Ipmp Extension, Hwee Hwa Pang, Yongdong Wu

Research Collection School Of Computing and Information Systems

MPEG-4 IPMPX (intellectual property management and protection extension) is the latest ISO standard which provides a flexible framework for protecting MPEG streams. The message mechanism of IPMPX enables interoperability among IPMPX-compliant devices no matter which protection methods are embedded. This paper highlights several problems in the message syntax of IPMPX: the tool delivery message IPMP_ToolES_AU is vulnerable to network attack, the authentication message IMP_Mutual_Authentication is incapable of defending against forgery attack, and the configuration message IPMP_SelectiveDecrptionInit is ambiguous and redundant. We propose a number of remedies to those problems, which can be incorporated into a corrigenda to improve the present …

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Exploring Bit-Difference For Approximate Knn Search In High-Dimensional Databases, Bin Cui, Heng Tao Shen, Jialie Shen, Kian-Lee Tan Jan 2005

Exploring Bit-Difference For Approximate Knn Search In High-Dimensional Databases, Bin Cui, Heng Tao Shen, Jialie Shen, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

In this paper, we develop a novel index structure to support effcient approximate k-nearest neighbor (KNN) query in high-dimensional databases. In high-dimensional spaces, the computational cost of the distance (e.g., Euclidean distance) between two points contributes a dominant portion of the overall query response time for memory processing. To reduce the distance computation, we first propose a structure (BID) using BIt-Difference to answer approximate KNN query. The BID employs one bit to represent each feature vector of point and the number of bit-difference is used to prune the further points. To facilitate real dataset which is typically skewed, we enhance …

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Linear Correlation Discovery In Databases: A Data Mining Approach, Cecil Chua, Roger Hsiang-Li Chiang, Ee Peng Lim Jan 2005

Linear Correlation Discovery In Databases: A Data Mining Approach, Cecil Chua, Roger Hsiang-Li Chiang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Very little research in knowledge discovery has studied how to incorporate statistical methods to automate linear correlation discovery (LCD). We present an automatic LCD methodology that adopts statistical measurement functions to discover correlations from databases’ attributes. Our methodology automatically pairs attribute groups having potential linear correlations, measures the linear correlation of each pair of attribute groups, and confirms the discovered correlation. The methodology is evaluated in two sets of experiments. The results demonstrate the methodology’s ability to facilitate linear correlation discovery for databases with a large amount of data.

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Applying Scenario-Based Design And Claim Analysis To The Design Of A Digital Library Of Geography Examination Resources, Yin-Leng Theng, Dion Hoe-Lian Goh, Ee Peng Lim, Zehua Liu, Ming Yin, Natalie Lee-San Pang, Patricia Bao-Bao Wong Jan 2005

Applying Scenario-Based Design And Claim Analysis To The Design Of A Digital Library Of Geography Examination Resources, Yin-Leng Theng, Dion Hoe-Lian Goh, Ee Peng Lim, Zehua Liu, Ming Yin, Natalie Lee-San Pang, Patricia Bao-Bao Wong

Research Collection School Of Computing and Information Systems

This paper describes the application of Carroll’s scenario-based design and claims analysis as a means of refinement to the initial design of a digital library of geographical resources (GeogDL) to prepare Singapore students to take a national examination in geography. GeogDL is built on top of G-Portal, a digital library providing services over geospatial and georeferenced Web content. Beyond improving the initial design of GeogDL, a main contribution of the paper is making explicit the use of Carroll’s strong theory-based but undercapitalized scenario-based design and claims analysis that inspired recommendations for the refinement of GeogDL. The paper concludes with an …

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Ontology-Assisted Mining Of Rdf Documents, Tao Jiang, Ah-Hwee Tan Jan 2005

Ontology-Assisted Mining Of Rdf Documents, Tao Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Resource description framework (RDF) is becoming a popular encoding language for describing and interchanging metadata of web resources. In this paper, we propose an Apriori-based algorithm for mining association rules (AR) from RDF documents. We treat relations (RDF statements) as items in traditional AR mining to mine associations among relations. The algorithm further makes use of a domain ontology to provide generalization of relations. To obtain compact rule sets, we present a generalized pruning method for removing uninteresting rules. We illustrate a potential usage of AR mining on RDF documents for detecting patterns of terrorist activities. Experiments conducted based on …

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