Physical Sciences and Mathematics Commons^™

The D-Tree: An Index Structure For Planar Point Queries Location-Based Wireless Services, Jianliang Xu, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Location-based services (LBSs), considered as a killer application in the wireless data market, provide information based on locations specified in the queries. In this paper, we examine the indexing issue for querying location-dependent data in wireless LBSs; in particular, we focus on an important class of queries, planar point queries. To address the issues of responsiveness, energy consumption, and bandwidth contention in wireless communications, an index has to minimize the search time and maintain a small storage overhead. It is shown that the traditional point-location algorithms and spatial index structures fail to achieve either objective or both. This paper proposes …

Accommodating Instance Heterogeneities In Database Integration, Ee Peng Lim, Roger Hsiang-Li Chiang

Research Collection School Of Computing and Information Systems

A complete data integration solution can be viewed as an iterative process that consists of three phases, namely analysis, derivation and evolution. The entire process is similar to a software development process with the target application being the derivation rules for the integrated databases. In many cases, data integration requires several iterations of refining the local-to-global database mapping rules before a stable set of rules can be obtained. In particular, the mapping rules, as well as the data model and query model for the integrated databases have to cope with poor data quality in local databases, ongoing local database updates …

Spatial Queries In Wireless Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Owing to the advent of wireless networking and personal digital devices, information systems in the era of mobile computing are expected to be able to handle a tremendous amount of traffic and service requests from the users. Wireless data broadcast, thanks to its high scalability, is particularly suitable for meeting such a challenge. Indexing techniques have been developed for wireless data broadcast systems in order to conserve the scarce power resources in mobile clients. However, most of the previous studies do not take into account the impact of location information of users. In this paper, we address the issues of …

On Semantic Caching And Query Scheduling For Mobile Nearest-Neighbor Search, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Location-based services have received increasing attention in recent years. In this paper, we address the performance issues of mobile nearest-neighbor search, in which the mobile user issues a query to retrieve stationary service objects nearest to him/her. An index based on Voronoi Diagram is used in the server to support such a search, while a semantic cache is proposed to enhance the access efficiency of the service. Cache replacement policies tailored for the proposed semantic cache are examined. Moreover, several query scheduling policies are proposed to address the inter-cell roaming issues in multi-cell environments. Simulations are conducted to evaluate the …

Semantic Web Technology In Support Of Bioinformatics For Glycan Expression, Amit P. Sheth, William S. York, Christopher Thomas, Meenakshi Nagarajan, John A. Miller, Krzysztof Kochut, Satya S. Sahoo, Xiaochuan Yi

Kno.e.sis Publications

Due to the complexity of biological systems, interpretation of data obtained by a single experimental approach can often be interpreted only if viewed from a broader context, taking into account the information obtained by many diverse techniques. The vast amount of interpreted experimental data that is now available via the internet opens the possibility of collecting the relevant pieces of information that will enable scientists to form hypotheses based on the integration of this diverse information. However, the sheer volume of data that is available makes it very difficult to select the information necessary to make a coherent model of …

Lsdis: Large Scale Distributed Information Systems Lab, Amit P. Sheth

Kno.e.sis Publications

The LSDIS (Large Scale Distributed Information Systems) lab was established in 1994 with the guidance and direction provided by Dr. Amit P. Sheth with the help of Dr. John A. Miller and Dr. Krzysztof J. Kochut. In 1998 this faculty group was further strengthened by the addition of Dr. Ismailcem B. Arpinar. LSDIS is the largest research group in Computer Science at UGA and one of the strongest in its area. During Fall 2004, it is funding 15 students (majority of them PhD), and has one research staff.

Over the years LSDIS has been actively involved in research projects in …

Clip-Based Similarity Measure For Hierarchical Video Retrieval, Yuxin Peng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a new approach and algorithm for the similarity measure of video clips. The similarity is mainly based on two bipartite graph matching algorithms: maximum matching (MM) and optimal matching (OM). MM is able to rapidly filter irrelevant video clips, while OM is capable of ranking the similarity of clips according to the visual and granularity factors. Based on MM and OM, a hierarchical video retrieval framework is constructed for the approximate matching of video clips. To allow the matching between a query and a long video, an online clip segmentation algorithm is also proposed to rapidly locate …

Improving Transliteration With Precise Alignment Of Phoneme Chunks And Using Contextual Features, Wei Gao, Kam-Fai Wong, Wai Lam

Research Collection School Of Computing and Information Systems

Automatic transliteration of foreign names is basically regarded as a diminutive clone of the machine translation (MT) problem. It thus follows IBM’s conventional MT models under the sourcechannel framework. Nonetheless, some parameters of this model dealing with zero-fertility words in the target sequences, can negatively impact transliteration effectiveness because of the inevitable inverted conditional probability estimation. Instead of source-channel, this paper presents a direct probabilistic transliteration model using contextual features of phonemes with a tailored alignment scheme for phoneme chunks. Experiments demonstrate superior performance over the source-channel for the task of English-Chinese transliteration.

A Novel Log-Based Relevance Feedback Technique In Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Relevance feedback has been proposed as an important technique to boost the retrieval performance in content-based image retrieval (CBIR). However, since there exists a semantic gap between low-level features and high-level semantic concepts in CBIR, typical relevance feedback techniques need to perform a lot of rounds of feedback for achieving satisfactory results. These procedures are time-consuming and may make the users bored in the retrieval tasks. For a long-term study purpose in CBIR, we notice that the users' feedback logs can be available and employed for helping the retrieval tasks in CBIR systems. In this paper, we propose a novel …

Blocking Reduction Strategies In Hierarchical Text Classification, Ee Peng Lim, Aixin Sun, Wee-Keong Ng, Jaideep Srivastava

Research Collection School Of Computing and Information Systems

One common approach in hierarchical text classification involves associating classifiers with nodes in the category tree and classifying text documents in a top-down manner. Classification methods using this top-down approach can scale well and cope with changes to the category trees. However, all these methods suffer from blocking which refers to documents wrongly rejected by the classifiers at higher-levels and cannot be passed to the classifiers at lower-levels. We propose a classifier-centric performance measure known as blocking factor to determine the extent of the blocking. Three methods are proposed to address the blocking problem, namely, threshold reduction, restricted voting, and …

Logic Programs, Iterated Function Systems, And Recurrent Radial Basis Function Networks, Sebastian Bader, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Graphs of the single-step operator for first-order logic programs—displayed in the real plane—exhibit self-similar structures known from topological dynamics, i.e., they appear to be fractals, or more precisely, attractors of iterated function systems. We show that this observation can be made mathematically precise. In particular, we give conditions which ensure that those graphs coincide with attractors of suitably chosen iterated function systems, and conditions which allow the approximation of such graphs by iterated function systems or by fractal interpolation. Since iterated function systems can easily be encoded using recurrent radial basis function networks, we eventually obtain connectionist systems which …

Recommender Systems Research: A Connection-Centric Survey, Saverio Perugini, Marcos André Gonçalves, Edward A. Fox

Computer Science Faculty Publications

Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from …

A Spectroscopy Of Texts For Effective Clustering, Wenyuan Li, Wee-Keong Ng, Kok-Leong Ong, Ee Peng Lim

Research Collection School Of Computing and Information Systems

For many clustering algorithms, such as k-means, EM, and CLOPE, there is usually a requirement to set some parameters. Often, these parameters directly or indirectly control the number of clusters to return. In the presence of different data characteristics and analysis contexts, it is often difficult for the user to estimate the number of clusters in the data set. This is especially true in text collections such as Web documents, images or biological data. The fundamental question this paper addresses is: ldquoHow can we effectively estimate the natural number of clusters in a given text collection?rdquo. We propose to use …

Sclope: An Algorithm For Clustering Data Streams Of Categorical Attributes, Kok-Leong Ong, Wenyuan Li, Wee-Keong Ng, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Clustering is a difficult problem especially when we consider the task in the context of a data stream of categorical attributes. In this paper, we propose SCLOPE, a novel algorithm based on CLOPE's intuitive observation about cluster histograms. Unlike CLOPE however, our algorithm is very fast and operates within the constraints of a data stream environment. In particular, we designed SCLOPE according to the recent CluStream framework. Our evaluation of SCLOPE shows very promising results. It consistently outperforms CLOPE in speed and scalability tests on our data sets while maintaining high cluster purity; it also supports cluster analysis that other …

Shared-Storage Auction Ensures Data Availability, Hady W. Lauw, Siu-Cheung Hui, Edmund M. K. Lai

Research Collection School Of Computing and Information Systems

Most current e-auction systems are based on the client-server architecture. Such centralized systems provide a single point of failure and control. In contrast, peer-to-peer systems permit distributed control and minimize individual node and link failures' impact on the system. The shared-storage-based auction model described decentralizes services among peers to share the required processing load and aggregates peers' resources for common use. The model is based on the principles of local computation at each peer, direct inter-peer communication, and a shared storage space.

Robust Classification Of Event-Related Potential For Brain-Computer Interface, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

We report the implementation of a text input application (speller) based on the P300 event related potential. We obtain high accuracies by using an SVM classifier and a novel feature. These techniques enable us to maintain fast performance without sacrificing the accuracy, thus making the speller usable in an online mode. In order to further improve the usability, we perform various studies on the data with a view to minimizing the training time required. We present data collected from nine healthy subjects, along with the high accuracies (of the order of 95% or more) measured online. We show that the …

Towards Personalised Web Intelligence, Ah-Hwee Tan, Hwee-Leng Ong, Hong Pan, Jamie Ng, Qiu-Xiang Li

Research Collection School Of Computing and Information Systems

The Flexible Organizer for Competitive Intelligence (FOCI) is a personalised web intelligence system that provides an integrated platform for gathering, organising, tracking, and disseminating competitive information on the web. FOCI builds personalised information portfolios through a novel method called User-Configurable Clustering, which allows a user to personalise his/her portfolios in terms of the content as well as the organisational structure. This paper outlines the key challenges we face in personalised information management and gives a detailed account of FOCI’s underlying personalisation mechanism. For a quantitative evaluation of the system’s performance, we propose a set of performance indices based on information …

Modeling Usage Of An Online Research Community, Yi Zhang

Dissertations

Although online communities have been thought of as a new way for collaboration across geographic boundaries in the scientific world, they have a problem attracting people to keep visiting. The main purpose of this study is to understand how people behave in such communities, and to build and evaluate tools to stimulate engagement in a research community. These tools were designed based on a research framework of factors that influence online participation and relationship development.

There are two main objectives for people to join an online community, information sharing and interpersonal relationship development, such as friends or colleagues. The tools …

Sb9: The Ninth Catalogue Of Spectroscopic Binary Orbits, Dimitri Pourbaix, Andrei A. Tokovinin, Alan H. Batten, Francis C. Fekel, William I. Hartkopf, Hugo Levato, Nidia I. Morrell, Guillermo Torres, Stephane Udry

Information Systems and Engineering Management Research Publications

The Ninth Catalogue of Spectroscopic Binary Orbits (http://sb9.astro.ulb.ac.be) continues the series of compilations of spectroscopic orbits carried out over the past 35 years by Batten and collaborators. As of 2004 May 1st, the new Catalogue holds orbits for 2386 systems. Some essential differences between this catalogue and its predecessors are outlined and three straightforward applications are presented: (1) completeness assessment: period distribution of SB1s and SB2s; (2) shortest periods across the H-R diagram; (3) period-eccentricity relation.

Group-Based Relevance Feedback With Support Vector Machine Ensembles, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Support vector machines (SVMs) have become one of the most promising techniques for relevance feedback in content-based image retrieval (CBIR). Typical SVM-based relevance feedback techniquessimply apply the strict binary classifications: positive (relevant) class and negative (irrelevant) class. However, in a real-world relevance feedback task, it is more reasonable and practical to assume the data come from multiple positive classes and one negative class. In order to formulate an effective relevance feedback algorithm, we propose a novel group-based relevance feedback scheme constructed with the SVM ensembles technique. Experiments are conducted to evaluate the performance of our proposed scheme and the traditional …

High Accuracy Classification Of Eeg Signal, Wenjie Xu, Cuitai Guan, Chng Eng Siong, S. Ranganatha, Manoj Thulasidas, Jiankang Wu

Research Collection School Of Computing and Information Systems

Improving classification accuracy is a key issue to advancing brain computer interface (BCI) research from laboratory to real world applications. This article presents a high accuracy EEC signal classification method using single trial EEC signal to detect left and right finger movement. We apply an optimal temporal filter to remove irrelevant signal and subsequently extract key features from spatial patterns of EEG signal to perform classification. Specifically, the proposed method transforms the original EEG signal into a spatial pattern and applies the RBF feature selection method to generate robust feature. Classification is performed by the SVM and our experimental result …

Ltam: A Location-Temporal Authorization Model, Hai Yu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

This paper describes an authorization model for specifying access privileges of users who make requests to access a set of locations in a building or more generally a physical or virtual infrastructure. In the model, primitive locations can be grouped into composite locations and the connectivities among locations are represented in a multilevel location graph. Authorizations are defined with temporal constraints on the time to enter and leave a location and constraints on the number of times users can access a location. Access control enforcement is conducted by monitoring user movement and checking access requests against an authorization database. The …

Gesture Tracking And Recognition For Lecture Video Editing, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong

Research Collection School Of Computing and Information Systems

This paper presents a gesture based driven approach for video editing. Given a lecture video, we adopt novel approaches to automatically detect and synchronize its content with electronic slides. The gestures in each synchronized topic (or shot) are then tracked and recognized continuously. By registering shots and slides and recovering their transformation, the regions where the gestures take place can be known. Based on the recognized gestures and their registered positions, the information in slides can be seamlessly extracted, not only to assist video editing, but also to enhance the quality of original lecture video.

Agribusiness Sheep Updates - 2004 Part 3, Ken Hart, Keith Croker, Rob Davidson, Mario D'Antuono, Evan Burt, Tanya Kilminster, Diana Fedorenko, Darryl Mcclements, Robert Beard, Sandy Turton, Martin Atwell, Robert Beard

Sheep Updates

Posters Can Merino Ewes be Teased to Synchronise Oestrus for a Summer/Autumn Mating? Ken Hart, Keith Croker, Department of Agriculture Western Australia, Rob Davidson, School of Animal Biology, University of Western Australia. Mario D'Antuono, Department of Agriculture Western Australia Damara Sheep: Now Looking Domestic Evan Burt and Tanya Kilminster, Department of Agriculture Western Australia Production and Water Use of Lucerne and French Serradella Under Three Sowing Rates Diana Fedorenko1,4, Darryl McClements1,4 , Robert Beard3,4 1Department of Agriculture, 3 Farmer, Meckering, 4CRC for Plant-based Management of Dryland Salinity. E-SHEEP - Individual Animal Management is here Sandy Turton & Martin Atwell, Department …

Enhancing Web Services Description And Discovery To Facilitate Composition, Preeda Rajasekaran, John A. Miller, Kunal Verma, Amit P. Sheth

Kno.e.sis Publications

Web services are in the midst of making the transition from being a promising technology to being widely used in the industry. However, most efforts to use Web services have been manual, thus slowing down the ever changing and dynamic businesses of today. In this paper, we contend that more expressive descriptions of Web services will lead to greater automation and thus provide more agility to businesses. We present the METEOR-S front-end tools for source code annotation and semantic Web service description generation. We also present WSDL-S, a language created for incorporating semantic descriptions in the industry wide accepted WSDL, …

Learning Mixture Models With The Regularized Latent Maximum Entropy Principle, Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

Kno.e.sis Publications

This paper presents a new approach to estimating mixture models based on a recent inference principle we have proposed: the latent maximum entropy principle (LME). LME is different from Jaynes' maximum entropy principle, standard maximum likelihood, and maximum a posteriori probability estimation. We demonstrate the LME principle by deriving new algorithms for mixture model estimation, and show how robust new variants of the expectation maximization (EM) algorithm can be developed. We show that a regularized version of LME (RLME), is effective at estimating mixture models. It generally yields better results than plain LME, which in turn is often better than …

Workflow Management Systems And Erp Systems: Differences, Commonalities, And Applications, Jorge Cardoso, Robert P. Bostrom, Amit P. Sheth

Kno.e.sis Publications

Two important classes of information systems, Workflow Management Systems(WfMSs) and Enterprise Resource Planning (ERP) systems, have been used to support e-business process redesign, integration, and management. While both technologies can help with business process automation, data transfer, and information sharing, the technological approach and features of solutions provided by WfMS and ERP are different. Currently, there is a lack of understanding of these two classes of information systems in the industry and academia, thus hindering their effective applications. In this paper, we present a comprehensive comparison between these two classes of systems. We discuss how the two types of systems …

Discovery Of Web Services In A Federated Registry Environment, Kaarthik Sivashanmugam, Kunal Verma, Amit P. Sheth

Kno.e.sis Publications

The potential of a large scale growth of private and semi-private registries is creating the need for an infrastructure which can support discovery and publication over a group of autonomous registries. Recent versions of UDDI have made changes to accommodate interactions between distributed registries. In this paper, we discuss METEOR-S Web service Discovery Infrastructure, which provides an ontology-based infrastructure to access a group of registries that are divided based on business domains and grouped into federations. We also discuss how Web service discovery is carried out within a federation.

An Interactive Learning Environment For A Dynamic Educational Digital Library, Ee Peng Lim, Dion Hoe-Lian Goh, Yin-Leng Theng, Eng-Kai Suen

Research Collection School Of Computing and Information Systems

GeogDL is a digital library of geography examination resources designed to assist students in preparing for a national geography examination in Singapore. We describe an interactive learning environment built into GeogDL that consists of four major components. The practice and review module allows students to attempt individual examination questions, the mock exam provides a simulation of the actual geography examination, the trends analysis tool provides an overview of the types of questions asked in previous examinations, while the contributions module allows students and teachers to create and share knowledge within the digital library.

A Support-Ordered Trie For Fast Frequent Itemset Discovery, Ee Peng Lim, Yew-Kwong Woon, Wee-Keong Ng

Research Collection School Of Computing and Information Systems

The importance of data mining is apparent with the advent of powerful data collection and storage tools; raw data is so abundant that manual analysis is no longer possible. Unfortunately, data mining problems are difficult to solve and this prompted the introduction of several novel data structures to improve mining efficiency. Here, we critically examine existing preprocessing data structures used in association rule mining for enhancing performance in an attempt to understand their strengths and weaknesses. Our analyses culminate in a practical structure called the SOTrielT (support-ordered trie itemset) and two synergistic algorithms to accompany it for the fast discovery …