Databases and Information Systems Commons^™

Self-Organizing Neural Models Integrating Rules And Reinforcement Learning, Teck-Hou Teng, Zhong-Ming Tan, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Traditional approaches to integrating knowledge into neural network are concerned mainly about supervised learning. This paper presents how a family of self-organizing neural models known as fusion architecture for learning, cognition and navigation (FALCON) can incorporate a priori knowledge and perform knowledge refinement and expansion through reinforcement learning. Symbolic rules are formulated based on pre-existing know-how and inserted into FALCON as a priori knowledge. The availability of knowledge enables FALCON to start performing earlier in the initial learning trials. Through a temporal-difference (TD) learning method, the inserted rules can be refined and expanded according to the evaluative feedback signals received …

Defeasible Inference With Circumscriptive Owl Ontologies, Stephan Grimm, Pascal Hitzler

Computer Science and Engineering Faculty Publications

The Web Ontology Language (OWL) adheres to the openworld assumption and can thus not be used for forms of nonmonotonic reasoning or defeasible inference, an acknowledged desirable feature in open Semantic Web environments. We investigate the use of the formalism of circumscriptive description logics (DLs) to realise defeasible inference within the OWL framework. By example, we demonstrate how reasoning with (restricted) circumscribed OWL ontologies facilitates various forms of defeasible inference, also in comparison to alternative approaches. Moreover, we sketch an extension to DL tableaux for handling the circumscriptive case and report on a preliminary implementation.

Empowering Translational Research Using Semantic Web Technologies, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Context Modeling With Evolutionary Fuzzy Cognitive Map In Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen

Research Collection School Of Computing and Information Systems

To generate a believable and dynamic virtual world is a great challenge in interactive storytelling. In this paper, we propose a model, namely evolutionary fuzzy cognitive map (E-FCM), to model the dynamic causal relationships among different context variables. As an extension to conventional FCM, E-FCM models not only the fuzzy causal relationships among the variables, but also the probabilistic property of causal relationships, and asynchronous activity update of the concepts. With this model, the context variables evolve in a dynamic and uncertain manner with the according evolving time. As a result, the virtual world is presented more realistically and dynamically.

Wikinetviz: Visualizing Friends And Adversaries In Implicit Social Networks, Minh-Tam Le, Hoang-Vu Dang, Ee Peng Lim, Anwitaman Datta

Research Collection School Of Computing and Information Systems

When multiple users with diverse backgrounds and beliefs edit Wikipedia together, disputes often arise due to disagreements among the users. In this paper, we introduce a novel visualization tool known as WikiNetViz to visualize and analyze disputes among users in a dispute-induced social network. WikiNetViz is designed to quantify the degree of dispute between a pair of users using the article history. Each user (and article) is also assigned a controversy score by our proposed controversy rank model so as to measure the degree of controversy of a user (and an article) by the amount of disputes between the user …

Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval, Steven Hoi, Wei Liu, Shih-Fu Chang

Research Collection School Of Computing and Information Systems

Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, relevance feedback has been adopted as a promising approach to improve the search performance. In this paper, we propose a novel idea of learning with historical relevance feedback log data, and adopt a new paradigm called “Collaborative Image Retrieval” (CIR). To effectively explore the log data, we propose a novel semi-supervised distance metric learning technique, called “Laplacian Regularized Metric Learning” (LRML), for learning robust distance metrics for CIR. Different from previous methods, the proposed LRML method integrates both …

A Multimodal And Multilevel Ranking Scheme For Large-Scale Video Retrieval, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

A critical issue of large-scale multimedia retrieval is how to develop an effective framework for ranking the search results. This problem is particularly challenging for content-based video retrieval due to some issues such as short text queries, insufficient sample learning, fusion of multimodal contents, and large-scale learning with huge media data. In this paper, we propose a novel multimodal and multilevel (MMML) ranking framework to attack the challenging ranking problem of content-based video retrieval. We represent the video retrieval task by graphs and suggest a graph based semi-supervised ranking (SSR) scheme, which can learn with small samples effectively and integrate …

Predicting Trusts Among Users Of Online Communities: An Epinions Case Study, Haifeng Liu, Ee Peng Lim, Hady W. Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim

Research Collection School Of Computing and Information Systems

Trust between a pair of users is an important piece of information for users in an online community (such as electronic commerce websites and product review websites) where users may rely on trust information to make decisions. In this paper, we address the problem of predicting whether a user trusts another user. Most prior work infers unknown trust ratings from known trust ratings. The effectiveness of this approach depends on the connectivity of the known web of trust and can be quite poor when the connectivity is very sparse which is often the case in an online community. In this …

Use Of Cognitive Mapping Techniques In Information Systems Development, Keng Siau, X. Tan

Research Collection School Of Computing and Information Systems

Cognitive mapping techniques as a communication tool can be used in various information systems (IS) development and implementation activities. The three major cognitive mapping techniques include causal mapping, semantic mapping, and concept mapping. A causal map represents a set of causal relationships among constructs within a belief system. Semantic mapping, also known as idea mapping, is used to explore an idea without the constraints of a superimposed structure. The result of concept mapping is a graphical representation in which nodes represent concepts and links represent the relationships between concepts. Cognitive mapping techniques have been proposed to be applied in requirements …

Semi-Supervised Svm Batch Mode Active Learning For Image Retrieval, Steven Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learning is popular for its application to relevance feedback in CBIR. However, the regular SVM active learning has two main drawbacks when used for relevance feedback. First, SVM often suffers from learning with a small number of labeled examples, which is the case in relevance feedback. Second, SVM active learning usually does not take into account the redundancy among examples, and therefore could select multiple examples in relevance feedback that are similar (or even identical) to …

Visual Analytics For Supporting Entity Relationship Discovery On Text Data, Hanbo Dai, Ee Peng Lim, Hady W. Lauw, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

To conduct content analysis over text data, one may look out for important named objects and entities that refer to real world instances, synthesizing them into knowledge relevant to a given information seeking task. In this paper, we introduce a visual analytics tool called ER-Explorer to support such an analysis task. ER-Explorer consists of a data model known as TUBE and a set of data manipulation operations specially designed for examining entities and relationships in text. As part of TUBE, a set of interestingness measures is defined to help exploring entities and their relationships. We illustrate the use of ER-Explorer …

Capacity Constrained Assignment In Spatial Databases, Hou U Leong, Man Lung Yiu, Kyriakos Mouratidis, Nikos Mamoulis

Research Collection School Of Computing and Information Systems

Given a point set P of customers (e.g., WiFi receivers) and a point set Q of service providers (e.g., wireless access points), where each q 2 Q has a capacity q.k, the capacity constrained assignment (CCA) is a matching M Q × P such that (i) each point q 2 Q (p 2 P) appears at most k times (at most nce) in M, (ii) the size of M is maximized (i.e., it comprises min{|P|,P q2Q q.k} pairs), and (iii) the total assignment cost (i.e., the sum of Euclidean distances within all pairs) is minimized. Thus, the CCA problem is …

An Office Survival Guide, M. Thulasidas

Research Collection School Of Computing and Information Systems

In the unforgiving, dog-eat-dog corporate jungle, when you find yourself in a new corporate setting, you need to be sure of the welcome. More importantly, you need to prove yourself worthy of it.

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

Research Collection School Of Computing and Information Systems

Ubiquitous commerce (u-commerce) represents “anytime, anywhere” commerce. U-commerce can provide a high level of personalization, which can bring significant benefits to customers. However, privacy is a major concern to customers and an obstacle to the adoption of u-commerce. This research examines how personalization and context can impact customers’ privacy concerns as well as intention to adopt u-commerce applications. As u-commerce is new and emerging, we used the scenario-based approach to operationalize personalization and context in an experimental study. The experimental results show that the effects of personalization on customers’ privacy concerns and adoption intention are situation dependent.

Appropriation Of Privacy Management Within Social Networking Sites, Catherine Dwyer

Dissertations

Social networking sites have emerged as one of the most widely used types of interactive systems, with memberships numbering in the hundreds of millions around the globe. By providing tools for their members to manage an ever-changing set of relationships, social networking sites push a constant expansion of social boundaries. These sites place less emphasis on tools that limit social boundaries to enable privacy.

The rapid expansion of online social boundaries has caused privacy shockwaves. Privacy offline is enabled by constraints of time and space. Online, powerful search engines and long term digital storage means private data have no expiration …

Dynamics Of Online Chat, Mihai Moldovan

Dissertations

Millions of people use online synchronous chat networks on a daily basis for work, play and education. Despite their widespread use, little is known about their user dynamics. For example, one does not know how many users are typically co-present and actively engaged in public interaction in the individual chat rooms of any of the numerous public Internet Relay Chat (IRC) networks found on the Internet; or what are the factors that constrain the boundaries of user activity inside those chat rooms. Failure to collect and present such data means there is a lack of a good understanding of the …

Perception Gaps And The Adoption Of Information Technology In The Clinical Healthcare Environment, Karen Hare

Dissertations

Implementation of information systems has lagged in many areas of clinical healthcare for a variety of reasons. Economics, data complexity and resistance are among the often quoted roadblocks. Research suggests that physicians play a major part in the adoption, use and diffusion of information technology (IT) in clinical settings. There are also other healthcare professionals, clinical and non-clinical, who play important roles in making decisions about the acquisition of information technology. In addition to these groups there are information technology professionals providing the services required within the healthcare field. Finally within this group are those IT professionals who have sufficient …

The Impact Of Cultural Differences In Temporal Perception On Global Software Development Teams, Richard William Egan

Dissertations

This dissertation investigated the impact of cultural differences in temporal perception on globally dispersed software development teams. Literature and anecdotal evidence suggest that these temporal differences affect individual communication quality, which in turn will affect individual satisfaction and trust within global teams. Additionally, the temporal dispersion of the team was expected to affect an individual's sense of temporal disruption which, in turn, was expected to affect individual satisfaction and trust. Differences in temporal perception were expected to moderate this impact on perceived temporal disruption. A Fortune 100 Company that carried out software testing in Ireland, the United States, China and …

Sa-Rest: Using Semantics To Empower Restful Services And Smashups With Better Interoperability And Mediation, Karthik Gomadam, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Dynamic And Agile Soa Using Sawsdl, Karthik Gomadam, Kunal Verma, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

A Framework To Support Spatial, Temporal And Thematic Analytics Over Semantic Web Data, Matthew Perry, Amit P. Sheth

Kno.e.sis Publications

Spatial and temporal data are critical components in many applications. This is especially true in analytical applications ranging from scientific discovery to national security and criminal investigation. The analytical process often requires uncovering and analyzing complex thematic relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful for this purpose. However, these analysis mechanisms are primarily intended for thematic relationships. In this paper, we describe a framework built around the RDF data model for analysis of thematic, spatial and temporal relationships between …

Location-Based Hashing For Querying And Searching, Felix Ching

Computer Science and Computer Engineering Undergraduate Honors Theses

The rapidly growing information technology in modern days demands an efficient searching scheme to search for desired data. Locality Sensitive Hashing (LSH) is a method for searching similar data in a database. LSH achieves high accuracy and precision for locating desired data, but consumes a significant amount of memory and time. Based on LSH, this thesis presents two novel schemes for efficient and accurate data searching: Locality Sensitive Hashing-SmithWaterman (LSH-SmithWaterman) and Secure Min-wise Locality Sensitive Hashing (SMLSH). Both methods dramatically reduce the memory and time consumption and exhibit high accuracy in data searching. Simulation results demonstrate the efficiency of the …

Guidelines For Evaluating Patterns In The Is Domain, Deepak Khazanchi, John D. Murphy, Stacie Clarke Petter

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Patterns were originally developed in the field of architecture as a mechanism for communicating good solutions to recurring classes of problems. Since then researchers have created patterns to provide guidance and solutions associated with virtual project management, software development and engineering, human computer interaction, and design science research. However, there has been limited emphasis on developing guidelines for evaluating the validity of patterns. In this paper, we propose an evaluation framework for patterns that draws upon the literature associated with patterns, philosophy of science and research methods. The evaluation framework can be used to validate patterns in a more consistent …

Measuring Soa Success, J. Erickson, Keng Siau

Research Collection School Of Computing and Information Systems

Service-oriented architecture (SOA), web services, and service-oriented computing (SOC) have become prominent topics in the business world. Many companies are either implementing, considering, or have already implemented SOA projects, web services initiatives, or SOC adoption. A critical question for organizations is how to measure SOA success. Is return on investment (ROI) a suitable metric for evaluating SOA projects? What about intangible factors such as comparative advantage or competitive necessity? Additionally, considerations like agility, nimbleness, and responsiveness play a significant role. This research investigates various factors for measuring project success and employs a Delphi study to gather insights from a panel …

Verifying Completeness Of Relational Query Answers From Online Servers, Hwee Hwa Pang, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

The number of successful attacks on the Internet shows that it is very difficult to guarantee the security of online servers over extended periods of time. A breached server that is not detected in time may return incorrect query answers to users. In this article, we introduce authentication schemes for users to verify that their query answers from an online server are complete (i.e., no qualifying tuples are omitted) and authentic (i.e., all the result values are legitimate). We introduce a scheme that supports range selection, projection as well as primary key-foreign key join queries on relational databases. We also …

Stress Test, M. Thulasidas

Research Collection School Of Computing and Information Systems

Ultimately, the risk factors that create stress in professional life do not generate any reward

Ws3: International Workshop On Context-Enabled Source And Service Selection, Integration And Adaptation, Quan Z. Sheng, Ullas Nambiar, Amit P. Sheth, Biplav Srivastava, Zakaria Maamr, Said Elnaffar

Kno.e.sis Publications

This write-up provides a summary of the International Workshop on Context enabled Source and Service Selection, Integration and Adaptation (CSSSIA 2008), organized in conjunction with WWW2008, at Beijing, China on April 22nd 2008. We outline the motivation for organizing the work-shop, briefly describe the organizational details and program of the workshop, and summarize each of the papers accepted by the workshop. More information about the workshop can be found at http://www.cs.adelaide.edu.au/∼csssia08/.

Rdb2rdf: Incorporating Domain Semantics In Structured Data, Satya S. Sahoo

Kno.e.sis Publications

No abstract provided.

Getting Started With Prpl, Qingfeng Guan

School of Natural Resources: Faculty Publications

pRPL is an open-source1 general-purpose parallel Raster Processing programming Library developed by Qingfeng Guan, in the Department of Geography, University of California, Santa Barbara. pRPL encapsulates complex parallel computing utilities and routines specifically for raster processing (e.g., raster data decomposition, distribution and gathering among multiple processors, inter-processor communication and data exchange), and provides an easy-to-use interface for users to parallelize almost any raster processing algorithm with any arbitrary neighborhood (or moving window) configuration. pRPL enables the implementation of parallel raster-processing algorithms without requiring a deep understanding of parallel computing and programming, thus it greatly reduces the development complexity. Moreover, even …

Mobile Communication And Data Gathering Software For Autistic Children And Their Caregivers, Gondy Leroy, Gianluca De Leo

CGU Faculty Publications and Research

Positive design leads to positive change in our society. In most cases, discussions focus on those who receive the design. However, positive design may also have a positive, but often over-looked, effect on the designers themselves. Learning about difficulties others face and developing solutions is a benefit that can contribute to individual designers’ education and general sense of well-being. Having a broader understanding of alternative views and lifestyles makes one a better person. In addition, positive design may benefit the entire field of information science by improving its ability to renew itself and attract new, young talent.