Databases and Information Systems Commons^™

Semantic Interoperability Of Web Services - Challenges And Experiences, Meenakshi Nagarajan, Kunal Verma, Amit P. Sheth, John A. Miller, Jonathan Lathem

Kno.e.sis Publications

With the rising popularity of Web services, both academia and industry have invested considerably in Web service description standards, discovery, and composition techniques. The standards based approach utilized by Web services has supported interoperability at the syntax level. However, issues of structural and semantic heterogeneity between messages exchanged by Web services are far more complex and crucial to interoperability. It is for these reasons that we recognize the value that schema/data mappings bring to Web service descriptions. In this paper, we examine challenges to interoperability; classify the types of heterogeneities that can occur between interacting services and present a possible …

Optimal Adaptation In Web Processes With Coordination Constraints, Kunal Verma, Prashant Doshi, Karthik Gomadam, John A. Miller, Amit P. Sheth

Kno.e.sis Publications

We present methods for optimally adapting Web processes to exogenous events while preserving inter-service constraints that necessitate coordination. For example, in a supply chain process, orders placed by a manufacturer may get delayed in arriving. In response to this event, the manufacturer has the choice of either waiting out the delay or changing the supplier. Additionally, there may be compatibility constraints between the different orders, thereby introducing the problem of coordination between them if the manufacturer chooses to change the suppliers. We focus on formulating the decision making models of the managers, who must adapt to external events while satisfying …

Flexible Querying Of Xml Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni

Kno.e.sis Publications

Text search engines are inadequate for indexing and searching XML documents because they ignore metadata and aggregation structure implicit in the XML documents. On the other hand, the query languages supported by specialized XML search engines are very complex. In this paper, we present a simple yet flexible query language, and develop its semantics to enable intuitively appealing extraction of relevant fragments of information while simultaneously falling back on retrieval through plain text search if necessary. We also present a simple yet robust relevance ranking for heterogeneous document-centric XML.

Continuous Nearest Neighbor Monitoring In Road Networks, Kyriakos Mouratidis, Man Lung Yiu, Dimitris Papadias, Nikos Mamoulis

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 °uctuations of edge weights. The ¯rst one maintains the query results by processing only updates that may invalidate …

Three Architectures For Trusted Data Dissemination In Edge Computing, Shen-Tat Goh, Hwee Hwa Pang, Robert H. Deng, Feng Bao

Research Collection School Of Computing and Information Systems

Edge computing pushes application logic and the underlying data to the edge of the network, with the aim of improving availability and scalability. As the edge servers are not necessarily secure, there must be provisions for users to validate the results—that values in the result tuples are not tampered with, that no qualifying data are left out, that no spurious tuples are introduced, and that a query result is not actually the output from a different query. This paper aims to address the challenges of ensuring data integrity in edge computing. We study three schemes that enable users to check …

Cuhk At Imageclef 2005: Cross-Language And Cross Media Image Retrieval, Steven Hoi, Jianke Zhu, Michael R. Lyu

Research Collection School Of Computing and Information Systems

In this paper, we describe our studies of cross-language and cross-media image retrieval at the ImageCLEF 2005. This is the first participation of our CUHK (The Chinese University of Hong Kong) group at ImageCLEF. The task in which we participated is the “bilingual ad hoc retrieval” task. There are three major focuses and contributions in our participation. The first is the empirical evaluation of language models and smoothing strategies for cross-language image retrieval. The second is the evaluation of cross-media image retrieval, i.e., combining text and visual contents for image retrieval. The last is the evaluation of bilingual image retrieval …

Multi-Learner Based Recursive Supervised Training, Laxmi R. Iyer, Kiruthika Ramanathan, Sheng-Uei Guan

Research Collection School Of Computing and Information Systems

In this paper, we propose the multi-learner based recursive supervised training (MLRT) algorithm, which uses the existing framework of recursive task decomposition, by training the entire dataset, picking out the best learnt patterns, and then repeating the process with the remaining patterns. Instead of having a single learner to classify all datasets during each recursion, an appropriate learner is chosen from a set of three learners, based on the subset of data being trained, thereby avoiding the time overhead associated with the genetic algorithm learner utilized in previous approaches. In this way MLRT seeks to identify the inherent characteristics of …

Wireless Indoor Positioning System With Enhanced Nearest Neighbors In Signal Space Algorithm, Quang Tran, Juki Wirawan Tantra, Ah-Hwee Tan, Ah-Hwee Tan, Kin-Choong Yow, Dongyu Qiu

Research Collection School Of Computing and Information Systems

With the rapid development and wide deployment of wireless Local Area Networks (WLANs), WLAN-based positioning system employing signal-strength-based technique has become an attractive solution for location estimation in indoor environment. In recent years, a number of such systems has been presented, and most of the systems use the common Nearest Neighbor in Signal Space (NNSS) algorithm. In this paper, we propose an enhancement to the NNSS algorithm. We analyze the enhancement to show its effectiveness. The performance of the enhanced NNSS algorithm is evaluated with different values of the parameters. Based on the performance evaluation and analysis, we recommend some …

Discovering Image-Text Associations For Cross-Media Web Information Fusion, Tao Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

The diverse and distributed nature of the information published on the World Wide Web has made it difficult to collate and track information related to specific topics. Whereas most existing work on web information fusion has focused on multiple document summarization, this paper presents a novel approach for discovering associations between images and text segments, which subsequently can be used to support cross-media web content summarization. Specifically, we employ a similarity-based multilingual retrieval model and adopt a vague transformation technique for measuring the information similarity between visual features and textual features. The experimental results on a terrorist domain document set …

Human-Computer Interaction Research In The Management Information Systems Discipline, Fiona Fui-Hoon Nah, Ping Zhang, Scott Mccoy, Munyong Yi

Research Collection School Of Computing and Information Systems

No abstract provided.

Masking Page Reference Patterns In Encryption Databases On Untrusted Storage, Xi Ma, Hwee Hwa Pang, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

To support ubiquitous computing, the underlying data have to be persistent and available anywhere-anytime. The data thus have to migrate from devices that are local to individual computers, to shared storage volumes that are accessible over open network. This potentially exposes the data to heightened security risks. In particular, the activity on a database exhibits regular page reference patterns that could help attackers learn logical links among physical pages and then launch additional attacks. We propose two countermeasures to mitigate the risk of attacks initiated through analyzing the shared storage server’s activity for those page patterns. The first countermeasure relocates …

An Event-Driven Approach To Computerizing Clinical Guidelines Using Xml, Bing Wu, Essam Mansour, Kudakwashe Dube, Jianxin Li

Conference Papers

Clinical events form the basis of patient care practice. Their computerization is an important aid to the work of clinicians. Clinical guidelines or protocols direct clinicians and patients on when and how to handle clinical problems. Thus, clinical guidelines are an encapsulation of clinical events. Hence, an event-driven approach to computerizing the management of clinical guidelines is worthy of investigation. In our framework, called SpEM, the main clinical guideline management dimensions are specification, execution, and manipulation. This paper presents an event-driven approach, within the context of the SpEM framework, to manage clinical guidelines. The event-driven approach is based on the …

The Viability Of Is Enhanced Knowledge Sharing In Mission-Critical Command And Control Centers, Sameh A. Sabet

Dissertations

Engineering processes such as the maintenance of mission-critical infrastructures are highly unpredictable processes that are vital for everyday life, as well as for national security goals. These processes are categorized as Emergent Knowledge Processes (EKP), organizational processes that are characterized by a changing set of actors, distributed knowledge bases, and emergent knowledge sharing activities where the process itself has no predetermined structure. The research described here utilizes the telecommunications network fault diagnosis process as a specific example of an EKP. The field site chosen for this research is a global undersea telecommunication network where nodes are staffed by trained personnel …

Geoexpert - An Expert System Based Framework For Data Quality In Spatial Databases, Aditya Kumar

Masters Theses & Specialist Projects

Usage of very large sets of historical spatial data in knowledge discovery process became a common trend, and in order to obtain better results from this knowledge discovery process the data should be of high quality. In this thesis we proposed a framework 'GeoExpert' for data quality assessment and cleansing tool for spatial data that integrates the spatial data visualization and analysis capabilities of the ARCGIS, the reason and inference capability of an expert system. In this thesis we implemented the proposed framework both stand-alone and web versions using ArcGIS Engine and ArcGIS Server, respectively. We used JESS expert system …

Information Availability And Security Policy, Andrew P. Martin, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Information availability is a key element of information security. However, information availability has not been addressed with the same enthusiasm as confidentiality and integrity because availability is impacted by many variables which cannot easily be controlled. The principal goal of this research is to characterize information availability in detail and investigate how effective enterprise security policy can ensure availability.

A Hybrid Architecture Combining Reactive Plan Execution And Reactive Learning, Samin Karim, Liz Sonenberg, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Developing software agents has been complicated by the problem of how knowledge should be represented and used. Many researchers have identified that agents need not require the use of complex representations, but in many cases suffice to use “the world” as their representation. However, the problem of introspection, both by the agents themselves and by (human) domain experts, requires a knowledge representation with a higher level of abstraction that is more ‘understandable’. Learning and adaptation in agents has traditionally required knowledge to be represented at an arbitrary, low-level of abstraction. We seek to create an agent that has the capability …

Use Of A Classroom Response System To Enhance Classroom Interactivity, Keng Siau, H. Sheng, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Classroom interactivity is a critical component of teaching and learning. This paper reports on the use of a classroom response system to enhance classroom interactivity in a systems analysis and design course. The success of the project was assessed using both quantitative and qualitative data. A pretest/posttest design was used to examine the effects of a classroom respons system on interactivity. The results show that a classroom response system can significantly improve classroom interactivity. Qualitative data was also collected to identify the strengths and weaknesses of using a classroom response system to enhance classroom interaction. Based on the quantitative and …

Collaborative Image Retrieval Via Regularized Metric Learning, Luo Si, Rong Jin, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

In content-based image retrieval (CBIR), relevant images are identified based on their similarities to query images. Most CBIR algorithms are hindered by the semantic gap between the low-level image features used for computing image similarity and the high-level semantic concepts conveyed in images. One way to reduce the semantic gap is to utilize the log data of users' feedback that has been collected by CBIR systems in history, which is also called “collaborative image retrieval.” In this paper, we present a novel metric learning approach, named “regularized metric learning,” for collaborative image retrieval, which learns a distance metric by exploring …

Learning The Unified Kernel Machines For Classification, Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang

Research Collection School Of Computing and Information Systems

Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel Machines (UKM) from both labeled and unlabeled data. Our proposed framework integrates supervised learning, semi-supervised kernel learning, and active learning in a unified solution. In the suggested framework, we particularly focus our attention on designing a new semi-supervised kernel learning method, i.e., Spectral Kernel Learning (SKL), which is built on the principles of kernel target alignment and unsupervised kernel design. Our algorithm is related to an equivalent quadratic programming problem that can be efficiently …

Social Network Dynamics For Open Source Software Projects, Y. Long, Keng Siau

Research Collection School Of Computing and Information Systems

Drawing on social network theories and previous studies, this research is an initial effort to explore the dynamics of the social network structure in Open Source Software (OSS) teams. Three projects were selected from SourceForge.net in term of their similarities as well as their differences. Monthly data were extracted from the bug tracking system in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of network structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a …

An Energy-Efficient And Access Latency Optimized Indexing Scheme For Wireless Data Broadcast, Yuxia Yao, Xueyan Tang, Ee Peng Lim, Aixin Sun

Research Collection School Of Computing and Information Systems

Data broadcast is an attractive data dissemination method in mobile environments. To improve energy efficiency, existing air indexing schemes for data broadcast have focused on reducing tuning time only, i.e., the duration that a mobile client stays active in data accesses. On the other hand, existing broadcast scheduling schemes have aimed at reducing access latency through nonflat data broadcast to improve responsiveness only. Not much work has addressed the energy efficiency and responsiveness issues concurrently. This paper proposes an energy-efficient indexing scheme called MHash that optimizes tuning time and access latency in an integrated fashion. MHash reduces tuning time by …

Using Mobile Technology In Education: Perspectives Of Students And Instructors, H. Sheng, F. Nah, Keng Siau

Research Collection School Of Computing and Information Systems

Mobile technology has the tremendous potential in supporting and improving education and its delivery. As a new phenomenon that is gaining popularity, the values of mobile technology in education need to be better researched and understood. In this research, we used the Value-Focused Thinking approach to interview students and instructors to identify the values of education that are enabled by mobile technology. These values are represented in the form of a means-ends objective network that not only captures the values of education facilitated by mobile technology but also depicts the relationships between these values. The values of education enabled by …

An Experimental Study On U-Commerce Adoption: The Impact Of Personalization And Privacy Concerns, H. Sheng, Fiona Fui-Hoon Nah, Keng Siau

Research Collection School Of Computing and Information Systems

U-commerce represents “anytime, anywhere” commerce, which is believed to be the ultimate form of commerce. Ucommerce can provide a high level of personalization, which can bring additional benefits and values to customers. However, despite these promises and potential benefits, customers’ privacy is a major concern and obstacle to the adoption of ucommerce. As customers’ intention to adopt u-commerce is based on the aggregate effect of perceived benefits and risk exposure (e.g., privacy concerns), this research examines how personalization and context can impact on customers’ perceived benefits and privacy concerns, and how this aggregated effect in turn affects u-commerce adoption intention. …

Understanding Intrinsic Factors Influencing Benefit Maximization Of Is Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

This research uses the Repertory Grid technique to understand intrinsic factors influencing benefit maximization of IS usage. The results show that domain-relevant skills, task motivation, cognitive/work style attributes, individual characteristics (identified as creativity traits) and personal characteristics (identified as innovativeness traits) influence benefit maximization of IS usage. The findings not only provide insights on ways to increase quality of IS usage in organizations but are also helpful for identifying approaches that foster attributes leading to increased benefit realization from IS usage.

Bias And Controversy: Beyond The Statistical Deviation, Hady W. Lauw, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

In this paper, we investigate how deviation in evaluation activities may reveal bias on the part of reviewers and controversy on the part of evaluated objects. We focus on a 'data-centric approach' where the evaluation data is assumed to represent the ground truth'. The standard statistical approaches take evaluation and deviation at face value. We argue that attention should be paid to the subjectivity of evaluation, judging the evaluation score not just on 'what is being said' (deviation), but also on 'who says it' (reviewer) as well as on 'whom it is said about' (object). Furthermore, we observe that bias …

Optimal Adaptation Of Web Processes With Inter-Service Dependencies, Kunal Verma, Prashant Doshi, Karthik Gomadam, John A. Miller, Amit P. Sheth

Kno.e.sis Publications

We present methods for optimally adapting Web processes to exogenous events while preserving inter-service dependencies. For example, in a supply chain process, orders placed by the manufacturer may get delayed in arriving. In response to this event, the manufacturer has the choice of either waiting out the delay or changing the supplier. Additionally, there may be compatibility constraints between the different orders, thereby introducing the problem of coordination between them if the manufacturer chooses to change the suppliers. We present our methods within the framework of autonomic Web processes. This framework seeks to add properties of self-configuration, adaptation, and self-optimization …

Gaussian Mixture Models And Neural Networks For Automatic Speaker Identification, Usha Gayatri Chalkapally

Electrical & Computer Engineering Theses & Dissertations

Automatic Speaker Recognition is the process of automatically recognizing who is speaking on the basis of individual information contained in speech signals. This technique of Automatic Speaker Recognition makes it possible to use the speaker's voice to verify their identity and control access to services such as voice dialing, banking by telephone, telephone shopping, database access services, information services, voice mail, security control for confidential information areas, and remote access to computers.

In this thesis, the techniques of Gaussian Mixture Models and Neural Networks for Automatic Speaker Identification are presented. Algorithms for Speaker Identification using Gaussian Mixture Models were developed, …

Querying Formal Contexts With Answer Set Programs, Pascal Hitzler, Markus Krotzsch

Computer Science and Engineering Faculty Publications

Recent studies showed how a seamless integration of formal concept analysis (FCA), logic of domains, and answer set programming (ASP) can be achieved. Based on these results for combining hierarchical knowledge with classical rule-based formalisms, we introduce an expressive common-sense query language for formal contexts. Although this approach is conceptually based on order-theoretic paradigms, we show how it can be implemented on top of standard ASP systems. Advanced features, such as default negation and disjunctive rules, thus become practically available for processing contextual data.

Geospatial Ontology Development And Semantic Analytics, I. Budak Arpinar, Cartic Ramakrishnan, Molly Azami, Amit P. Sheth, E. Lynn Usery, Mei-Po Kwan

Kno.e.sis Publications

Geospatial ontology development and semantic knowledge discovery addresses the need for modeling, analyzing and visualizing multimodal information, and is unique in offering integrated analytics that encompasses spatial, temporal and thematic dimensions of information and knowledge. The comprehensive ability to provide integrated analysis from multiple forms of information and use of explicit knowledge make this approach unique. This also involves specification of spatiotemporal thematic ontologies and populating such ontologies with high quality knowledge. Such ontologies form the basis for defining the meaning of important relations terms, such as near or surrounded by, and enable computation of spatiotemporal thematic proximity measures we …

Hierarchical Hidden Markov Model For Rushes Structuring And Indexing, Chong-Wah Ngo, Zailiang Pan, Xiaoyong Wei

Research Collection School Of Computing and Information Systems

Rushes footage are considered as cheap gold mine with the potential for reuse in broadcasting and filmmaking industries. However, it is difficult to mine the "gold" from the rushes since usually only minimum metadata is available. This paper focuses on the structuring and indexing of the rushes to facilitate mining and retrieval of "gold". We present a new approach for rushes structuring and indexing based on motion feature. We model the problem by a two-level Hierarchical Hidden Markov Model (HHMM). The HHMM, on one hand, represents the semantic concepts in its higher level to provide simultaneous structuring and indexing, on …