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Research Collection School Of Computing and Information Systems

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Articles 2761 - 2790 of 3436

Full-Text Articles in Databases and Information Systems

Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou Jan 2009

Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou

Research Collection School Of Computing and Information Systems

In this chapter, we consider a class of queries that arise in spatial decision making and resource allocation applications. Assume that a company wants to open a number of warehouses in a city. Let P be the set of residential blocks in the city. P represents customer locations to be potentially served by the company. At the same time, P also comprises the candidate warehouse locations because the warehouses themselves must be opened in some residential blocks.

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Efficient Valid Scope Computation For Location-Dependent Spatial Queries In Mobile And Wireless Environments, Ken C. K. Lee, Wang-Chien Lee, Hong Va Leong, Brandon Unger, Baihua Zheng Jan 2009

Efficient Valid Scope Computation For Location-Dependent Spatial Queries In Mobile And Wireless Environments, Ken C. K. Lee, Wang-Chien Lee, Hong Va Leong, Brandon Unger, Baihua Zheng

Research Collection School Of Computing and Information Systems

In mobile and wireless environments, mobile clients can access information with respect to their locations by submitting Location-Dependent Spatial Queries (LDSQs) to Location-Based Service (LBS) servers. Owing to scarce wireless channel bandwidth and limited client battery life, frequent LDSQ submission from clients must be avoided. Observing that LDSQs issued from similar client positions would normally return the same results, we explore the idea of valid scope, that represents a spatial area in which a set of LDSQs will retrieve exactly the same query results. With a valid scope derived and an LDSQ result cached at the client side, a client …

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Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang Jan 2009

Quality-Aware Collaborative Question Answering: Methods And Evaluation, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang

Research Collection School Of Computing and Information Systems

Community Question Answering (QA) portals contain questions and answers contributed by hundreds of millions of users. These databases of questions and answers are of great value if they can be used directly to answer questions from any user. In this research, we address this collaborative QA task by drawing knowledge from the crowds in community QA portals such as Yahoo! Answers. Despite their popularity, it is well known that answers in community QA portals have unequal quality. We therefore propose a quality-aware framework to design methods that select answers from a community QA portal considering answer quality in addition to …

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A Semiotic Analysis Of Unified Modeling Language Graphical Notations, Keng Siau, Yuhong Tian Jan 2009

A Semiotic Analysis Of Unified Modeling Language Graphical Notations, Keng Siau, Yuhong Tian

Research Collection School Of Computing and Information Systems

Unified modeling language (UML) is the standard modeling language for object-oriented system development. Despite its status as a standard, UML has a fuzzy formal specification and a weak theoretical foundation. Semiotics, the study of signs, provides a good theoretical foundation for UML research because graphical notations (or visual signs) of UML are subjected to the principles of signs. In our research, we use semiotics to study the effectiveness of graphical notations in UML. We hypothesized that the use of iconic signs as UML graphical notations leads to representation that is more accurately interpreted and that arouses fewer connotations than the …

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Localized Monitoring Of Knn Queries In Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim Jan 2009

Localized Monitoring Of Knn Queries In Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Wireless sensor networks have been widely used in civilian and military applications. Primarily designed for monitoring purposes, many sensor applications require continuous collection and processing of sensed data. Due to the limited power supply for sensor nodes, energy efficiency is a major performance concern in query processing. In this paper, we focus on continuous kNN query processing in object tracking sensor networks. We propose a localized scheme to monitor nearest neighbors to a query point. The key idea is to establish a monitoring area for each query so that only the updates relevant to the query are collected. The monitoring …

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Partially Materialized Digest Scheme: An Efficient Verification Method For Outsourced Databases, Kyriakos Mouratidis, Dimitris Sacharidis, Hwee Hwa Pang Jan 2009

Partially Materialized Digest Scheme: An Efficient Verification Method For Outsourced Databases, Kyriakos Mouratidis, Dimitris Sacharidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

In the outsourced database model, a data owner publishes her database through a third-party server; i.e., the server hosts the data and answers user queries on behalf of the owner. Since the server may not be trusted, or may be compromised, users need a means to verify that answers received are both authentic and complete, i.e., that the returned data have not been tampered with, and that no qualifying results have been omitted. We propose a result verification approach for one-dimensional queries, called Partially Materialized Digest scheme (PMD), that applies to both static and dynamic databases. PMD uses separate indexes …

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Quc-Tree: Integrating Query Context Information For Efficient Music Retrieval, Jialie Shen, Dacheng Tao, Xuelong Li Jan 2009

Quc-Tree: Integrating Query Context Information For Efficient Music Retrieval, Jialie Shen, Dacheng Tao, Xuelong Li

Research Collection School Of Computing and Information Systems

In this paper, we introduce a novel indexing scheme-query context tree (QUC-tree) to facilitate efficient query sensitive music search under different query contexts. Distinguished from the previous approaches, QUC-tree is a balanced multiway tree structure, where each level represents the data space at different dimensionality. Before the tree structure construction, principle component analysis (PCA) is applied for data analysis and transforming the raw composite features into a new feature space sorted by the importance of acoustic features. The PCA transformed data and reduced dimensions in the upper levels can alleviate suffering from dimensionality curse. To accurately mimic human perception, an …

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Dynamic Web Service Selection For Reliable Web Service Composition, San-Yih Hwang, Ee Peng Lim, Chien-Hsiang Lee, Cheng-Hung Chen Jan 2009

Dynamic Web Service Selection For Reliable Web Service Composition, San-Yih Hwang, Ee Peng Lim, Chien-Hsiang Lee, Cheng-Hung Chen

Research Collection School Of Computing and Information Systems

This paper studies the dynamic web service selection problem in a failure-prone environment, which aims to determine a subset of Web services to be invoked at run-time so as to successfully orchestrate a composite web service. We observe that both the composite and constituent web services often constrain the sequences of invoking their operations and therefore propose to use finite state machine to model the permitted invocation sequences of Web service operations. We assign each state of execution an aggregated reliability to measure the probability that the given state will lead to successful execution in the context where each web …

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A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu Dec 2008

A Fast Pruned‐Extreme Learning Machine For Classification Problem, Hai-Jun Rong, Yew-Soon Ong, Ah-Hwee Tan, Zexuan Zhu

Research Collection School Of Computing and Information Systems

Extreme learning machine (ELM) represents one of the recent successful approaches in machine learning, particularly for performing pattern classification. One key strength of ELM is the significantly low computational time required for training new classifiers since the weights of the hidden and output nodes are randomly chosen and analytically determined, respectively. In this paper, we address the architectural design of the ELM classifier network, since too few/many hidden nodes employed would lead to underfitting/overfitting issues in pattern classification. In particular, we describe the proposed pruned-ELM (P-ELM) algorithm as a systematic and automated approach for designing ELM classifier network. P-ELM uses …

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Text Cube: Computing Ir Measures For Multidimensional Text Database Analysis, Cindy Xinde Lin, Bolin Ding, Jiawei Han, Feida Zhu, Bo Zhao Dec 2008

Text Cube: Computing Ir Measures For Multidimensional Text Database Analysis, Cindy Xinde Lin, Bolin Ding, Jiawei Han, Feida Zhu, Bo Zhao

Research Collection School Of Computing and Information Systems

Since Jim Gray introduced the concept of ”data cube” in 1997, data cube, associated with online analytical processing (OLAP), has become a driving engine in data warehouse industry. Because the boom of Internet has given rise to an ever increasing amount of text data associated with other multidimensional information, it is natural to propose a data cube model that integrates the power of traditional OLAP and IR techniques for text. In this paper, we propose a Text-Cube model on multidimensional text database and study effective OLAP over such data. Two kinds of hierarchies are distinguishable inside: dimensional hierarchy and term …

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Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu Dec 2008

Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual form, which is then solved by some quadratic program solver consequently. In this correspondence, we propose a new formulation for robust regularized kernel regression under the theoretical framework of regularization networks and then tackle the optimization problem directly in the primal. We show that the primal and dual approaches are equivalent to achieving similar regression performance, but the primal formulation is more efficient and easier to be implemented than the dual one. Different from …

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Planning With Ifalcon: Towards A Neural-Network-Based Bdi Agent Architecture, Budhitama Subagdja, Ah-Hwee Tan Dec 2008

Planning With Ifalcon: Towards A Neural-Network-Based Bdi Agent Architecture, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper presents iFALCON, a model of BDI (beliefdesire-intention) agents that is fully realized as a selforganizing neural network architecture. Based on multichannel network model called fusion ART, iFALCON is developed to bridge the gap between a self-organizing neural network that autonomously adapts its knowledge and the BDI agent model that follows explicit descriptions. Novel techniques called gradient encoding are introduced for representing sequences and hierarchical structures to realize plans and the intention structure. This paper shows that a simplified plan representation can be encoded as weighted connections in the neural network through a process of supervised learning. A case …

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On Visualizing Heterogeneous Semantic Networks From Multiple Data Sources, Maureen Maureen, Aixin Sun, Ee Peng Lim, Anwitaman Datta, Kuiyu Chang Dec 2008

On Visualizing Heterogeneous Semantic Networks From Multiple Data Sources, Maureen Maureen, Aixin Sun, Ee Peng Lim, Anwitaman Datta, Kuiyu Chang

Research Collection School Of Computing and Information Systems

In this paper, we focus on the visualization of heterogeneous semantic networks obtained from multiple data sources. A semantic network comprising a set of entities and relationships is often used for representing knowledge derived from textual data or database records. Although the semantic networks created for the same domain at different data sources may cover a similar set of entities, these networks could also be very different because of naming conventions, coverage, view points, and other reasons. Since digital libraries often contain data from multiple sources, we propose a visualization tool to integrate and analyze the differences among multiple social …

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Innovation In The Programmable Web: Characterizing The Mashup Ecosystem, C. Jason Woodard, Shuli Yu Dec 2008

Innovation In The Programmable Web: Characterizing The Mashup Ecosystem, C. Jason Woodard, Shuli Yu

Research Collection School Of Computing and Information Systems

This paper investigates the structure and dynamics of the Web 2.0 software ecosystem by analyzing empirical data on web service APIs and mashups. Using network analysis tools to visualize the growth of the ecosystem from December 2005 to 2007, we find that the APIs are organized into three tiers, and that mashups are often formed by combining APIs across tiers. Plotting the cumulative distribution of mashups to APIs reveals a power-law relationship, although the tail is short compared to previously reported distributions of book and movie sales. While this finding highlights the dominant role played by the most popular APIs …

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Cognitive Agents Integrating Rules And Reinforcement Learning For Context-Aware Decision Support, Teck-Hou Teng, Ah-Hwee Tan Dec 2008

Cognitive Agents Integrating Rules And Reinforcement Learning For Context-Aware Decision Support, Teck-Hou Teng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

While context-awareness has been found to be effective for decision support in complex domains, most of such decision support systems are hard-coded, incurring significant development efforts. To ease the knowledge acquisition bottleneck, this paper presents a class of cognitive agents based on self-organizing neural model known as TD-FALCON that integrates rules and learning for supporting context-aware decision making. Besides the ability to incorporate a priori knowledge in the form of symbolic propositional rules, TD-FALCON performs reinforcement learning (RL), enabling knowledge refinement and expansion through the interaction with its environment. The efficacy of the developed Context-Aware Decision Support (CaDS) system is …

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Scaling Up Multi-Agent Reinforcement Learning In Complex Domains, Dan Xiao, Ah-Hwee Tan Dec 2008

Scaling Up Multi-Agent Reinforcement Learning In Complex Domains, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (TD) methods for real-time reinforcement learning. In this paper, we present two strategies, i.e. policy sharing and neighboring-agent mechanism, to further improve the learning efficiency of TD-FALCON in complex multi-agent domains. Through experiments on a traffic control problem domain and the herding task, we demonstrate that those strategies enable TD-FALCON to remain functional and adaptable in complex multi-agent domains

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Adoption Of 3-D Virtual Worlds For Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah Dec 2008

Adoption Of 3-D Virtual Worlds For Education, X. Chen, Keng Siau, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

As an emerging phenomenon, virtual world education is rarely researched in MIS literature. With stiff competition among institutions using virtual worlds for education, a legitimate research question is: What factors influence students’ intention to adopt 3-D virtual world environment for their education needs? Drawing on existing technology acceptance models and studies in other IS contexts, we developed a model to predict students’ acceptance of a 3-D virtual world education environment and plan to empirically test the model using survey data collected from college students. From the academic research perspective, studies on the use of the new technology for education will …

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Explaining Inferences In Bayesian Networks, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang Dec 2008

Explaining Inferences In Bayesian Networks, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

While Bayesian network (BN) can achieve accurate predictions even with erroneous or incomplete evidence, explaining the inferences remains a challenge. Existing approaches fall short because they do not exploit variable interactions and cannot account for compensations during inferences. This paper proposes the Explaining BN Inferences (EBI) procedure for explaining how variables interact to reach conclusions. EBI explains the value of a target node in terms of the influential nodes in the target's Markov blanket under specific contexts, where the Markov nodes include the target's parents, children, and the children's other parents. Working back from the target node, EBI shows the …

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Bias And Controversy In Evaluation Systems, Hady Wirawan Lauw, Ee Peng Lim, Ke Wang Nov 2008

Bias And Controversy In Evaluation Systems, Hady Wirawan Lauw, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

Evaluation is prevalent in real life. With the advent of Web 2.0, online evaluation has become an important feature in many applications that involve information (e.g., video, photo, and audio) sharing and social networking (e.g., blogging). In these evaluation settings, a set of reviewers assign scores to a set of objects. As part of the evaluation analysis, we want to obtain fair reviews for all the given objects. However, the reality is that reviewers may deviate in their scores assigned to the same object, due to the potential bias of reviewers or controversy of objects. The statistical approach of averaging …

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A Neural Network Model For A Hierarchical Spatio-Temporal Memory, Kiruthika Ramanathan, Luping Shi, Jianming Li, Kian Guan Lim, Zhi Ping Ang, Chong Chong Tow Nov 2008

A Neural Network Model For A Hierarchical Spatio-Temporal Memory, Kiruthika Ramanathan, Luping Shi, Jianming Li, Kian Guan Lim, Zhi Ping Ang, Chong Chong Tow

Research Collection School Of Computing and Information Systems

The architecture of the human cortex is uniform and hierarchical in nature. In this paper, we build upon works on hierarchical classification systems that model the cortex to develop a neural network representation for a hierarchical spatio-temporal memory (HST-M) system. The system implements spatial and temporal processing using neural network architectures. We have tested the algorithms developed against both the MLP and the Hierarchical Temporal Memory algorithms. Our results show definite improvement over MLP and are comparable to the performance of HTM.

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Virtual World Affordances: Enhancing Brand Value, S. Park, Fiona Fui-Hoon Nah, D. Dewester, B. Eschenbrenner, S. Jeon Nov 2008

Virtual World Affordances: Enhancing Brand Value, S. Park, Fiona Fui-Hoon Nah, D. Dewester, B. Eschenbrenner, S. Jeon

Research Collection School Of Computing and Information Systems

Virtual worlds are three-dimensional, computer-generated worlds that are a natural extension of the existing Internet. Although many businesses are jumping on the bandwagon to maintain a presence in virtual worlds, there is no well-established knowledge or theory to guide businesses in their involvement in these environments. In this paper, we identify affordances in the virtual worlds that can be used to increase the state of flow experienced in a business virtual site, which in turn may enhance brand equity, or the perceived added value of a brand to customers. We present a conceptual model that can be used to guide …

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Beyond Semantic Search: What You Observe May Not Be What You Think, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Wanlei Zhao, Feng Wang, Xiao Wu, Hung-Khoon Tan Nov 2008

Beyond Semantic Search: What You Observe May Not Be What You Think, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Wanlei Zhao, Feng Wang, Xiao Wu, Hung-Khoon Tan

Research Collection School Of Computing and Information Systems

This paper presents our approaches and results of the four TRECVID 2008 tasks we participated in: high-level feature extraction, automatic video search, video copy detection, and rushes summarization

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Modality Mixture Projections For Semantic Video Event Detection, Jialie Shen, Dacheng Tao, Xuelong Li Nov 2008

Modality Mixture Projections For Semantic Video Event Detection, Jialie Shen, Dacheng Tao, Xuelong Li

Research Collection School Of Computing and Information Systems

Event detection is one of the most fundamental components for various kinds of domain applications of video information system. In recent years, it has gained a considerable interest of practitioners and academics from different areas. While detecting video event has been the subject of extensive research efforts recently, much less existing approach has considered multimodal information and related efficiency issues. In this paper, we use a subspace selection technique to achieve fast and accurate video event detection using a subspace selection technique. The approach is capable of discriminating different classes and preserving the intramodal geometry of samples within an identical …

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Using English Information In Non-English Web Search, Wei Gao, Wei Gao, Ming Zhou Oct 2008

Using English Information In Non-English Web Search, Wei Gao, Wei Gao, Ming Zhou

Research Collection School Of Computing and Information Systems

The leading web search engines have spent a decade building highly specialized ranking functions for English web pages. One of the reasons these ranking functions are effective is that they are designed around features such as PageRank, automatic query and domain taxonomies, and click-through information, etc. Unfortunately, many of these features are absent or altered in other languages. In this work, we show how to exploit these English features for a subset of Chinese queries which we call linguistically non-local (LNL). LNL Chinese queries have a minimally ambiguous English translation which also functions as a good English query. We first …

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Near-Duplicate Keyframe Retrieval By Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan Oct 2008

Near-Duplicate Keyframe Retrieval By Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Near-duplicate image retrieval plays an important role in many real-world multimedia applications. Most previous approaches have some limitations. For example, conventional appearance-based methods may suffer from the illumination variations and occlusion issue, and local feature correspondence-based methods often do not consider local deformations and the spatial coherence between two point sets. In this paper, we propose a novel and effective Nonrigid Image Matching (NIM) approach to tackle the task of near-duplicate keyframe retrieval from real-world video corpora. In contrast to previous approaches, the NIM technique can recover an explicit mapping between two near-duplicate images with a few deformation parameters and …

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Bayesian Tensor Approach For 3-D Face Modeling, Dacheng Tao, Mingli Song, Xuelong Li, Jialie Shen, Jimeng Sun, Xindong Wu, Christos Faloutsos, Stephen J. Maybank Oct 2008

Bayesian Tensor Approach For 3-D Face Modeling, Dacheng Tao, Mingli Song, Xuelong Li, Jialie Shen, Jimeng Sun, Xindong Wu, Christos Faloutsos, Stephen J. Maybank

Research Collection School Of Computing and Information Systems

Effectively modeling a collection of three-dimensional (3-D) faces is an important task in various applications, especially facial expression-driven ones, e.g., expression generation, retargeting, and synthesis. These 3-D faces naturally form a set of second-order tensors-one modality for identity and the other for expression. The number of these second-order tensors is three times of that of the vertices for 3-D face modeling. As for algorithms, Bayesian data modeling, which is a natural data analysis tool, has been widely applied with great success; however, it works only for vector data. Therefore, there is a gap between tensor-based representation and vector-based data analysis …

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Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan Oct 2008

Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

We propose, theorize and implement the Recursive Pattern-based Hybrid Supervised (RPHS) learning algorithm. The algorithm makes use of the concept of pseudo global optimal solutions to evolve a set of neural networks, each of which can solve correctly a subset of patterns. The pattern-based algorithm uses the topology of training and validation data patterns to find a set of pseudo-optima, each learning a subset of patterns. It is therefore well adapted to the pattern set provided. We begin by showing that finding a set of local optimal solutions is theoretically equivalent, and more efficient, to finding a single global optimum …

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Output Regularized Metric Learning With Side Information, Wei Liu, Steven C. H. Hoi, Jianzhuang Liu Oct 2008

Output Regularized Metric Learning With Side Information, Wei Liu, Steven C. H. Hoi, Jianzhuang Liu

Research Collection School Of Computing and Information Systems

Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application of learning distance metrics from historical relevance feedback log data, which leads to a novel scenario called collaborative image retrieval. The log data provide the side information expressed as relevance judgements between image pairs. Exploiting the side information as well as inherent neighborhood structures among examples, we design a convex regularizer upon which a novel distance metric learning approach, named output regularized metric learning, is presented to tackle collaborative image retrieval. Different from previous distance metric …

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Event Detection With Common User Interests, Meishan Hu, Aixin Sun, Ee Peng Lim Oct 2008

Event Detection With Common User Interests, Meishan Hu, Aixin Sun, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we aim at detecting events of common user interests from huge volume of user-generated content. The degree of interest from common users in an event is evidenced by a significant surge of event-related queries issued to search for documents (e.g., news articles, blog posts) relevant to the event. Taking the stream of queries from users and the stream of documents as input, our proposed framework seamlessly integrates the two streams into a single stream of query profiles. A query profile is a set of documents matching a query at a given time. With the single stream of …

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Comparison Of Online Social Relations In Volume Vs Interaction: A Case Study Of Cyworld, Hyunwoo Chun, Haewoon Kwak, Young-Ho Eom, Yong-Yeol Ahn, Sue Moon, Hawoong. Jeong Oct 2008

Comparison Of Online Social Relations In Volume Vs Interaction: A Case Study Of Cyworld, Hyunwoo Chun, Haewoon Kwak, Young-Ho Eom, Yong-Yeol Ahn, Sue Moon, Hawoong. Jeong

Research Collection School Of Computing and Information Systems

Online social networking services are among the most popular Internet services according to Alexa.com and have become a key feature in many Internet services. Users interact through various features of online social networking services: making friend relationships, sharing their photos, and writing comments. These friend relationships are expected to become a key to many other features in web services, such as recommendation engines, security measures, online search, and personalization issues. However, we have very limited knowledge on how much interaction actually takes place over friend relationships declared online. A friend relationship only marks the beginning of online interaction.Does the interaction …

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