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Articles 61 - 90 of 197
Full-Text Articles in Databases and Information Systems
Applications Of Voting Theory To Information Mashups, Alfredo Alba, Varun Bhagwan, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Jan Pieper, Christine Robson, Nachiketa Sahoo
Applications Of Voting Theory To Information Mashups, Alfredo Alba, Varun Bhagwan, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Jan Pieper, Christine Robson, Nachiketa Sahoo
Kno.e.sis Publications
Blogs, discussion forums and social networking sites are an excellent source for people's opinions on a wide range of topics. We examine the application of voting theory to "information mashups" - the combining and summarizing of data from the multitude of often-conflicting sources. This paper presents an information mashup in the music domain: a Top 10 artist chart based on user comments and listening behavior from several Web communities. We consider different voting systems as algorithms to combine opinions from multiple sources and evaluate their effectiveness using social welfare functions. Different voting schemes are found to work better in some …
Classification In P2p Networks By Bagging Cascade Rsvms, Hock Hee Ang, Vikvekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng, Anwitaman Datta
Classification In P2p Networks By Bagging Cascade Rsvms, Hock Hee Ang, Vikvekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng, Anwitaman Datta
Research Collection School Of Computing and Information Systems
Data mining tasks in P2P are bound by issues like scalability, peer dynamism, asynchronism, and data privacy preservation. These challenges pose difficulties for deploying conventional machine learning techniques in P2P networks, which may be hard to achieve classification accuracies comparable to regular centralized solutions. We recently investigated the classification problem in P2P networks and proposed a novel P2P classification approach by cascading Reduced Support Vector Machines (RSVM). Although promising results were obtained, the existing solution has some drawback of redundancy in both communication and computation. In this paper, we present a new approach to over the limitation of the previous …
Impacts Of Social Network Structure On Knowledge Sharing In Open Source Software Development Teams, Y. Long, Keng Siau
Impacts Of Social Network Structure On Knowledge Sharing In Open Source Software Development Teams, Y. Long, Keng Siau
Research Collection School Of Computing and Information Systems
The study examines the relationship between social network structure and knowledge sharing in Open Source Software (OSS) development teams. One hundred and fifty projects were selected from SourceForge.net using stratified sampling. Social network structure was measured by two indices: degree of centralization and core/periphery fitness. Knowledge sharing was measured from two aspects: the quality of knowledge sharing that is indicated by the helpfulness of messages and the quantity of knowledge sharing that is indicated by the number of messages. The results show that social network structure significantly affects the quantity of knowledge sharing. However, social network structure does not influence …
Knowledge Transfer Via Multiple Model Local Structure Mapping, Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
Knowledge Transfer Via Multiple Model Local Structure Mapping, Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
Research Collection School Of Computing and Information Systems
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from which test examples are to be drawn. The task can be especially difficult when the training examples are from one or several domains different from the test domain. In this paper, we propose a locally weighted ensemble framework to combine multiple models for transfer learning, where the weights are dynamically assigned according to a model's predictive power on each test example. It can integrate the advantages of various learning algorithms and the labeled information from multiple …
Authenticating The Query Results Of Text Search Engines, Hwee Hwa Pang, Kyriakos Mouratidis
Authenticating The Query Results Of Text Search Engines, Hwee Hwa Pang, Kyriakos Mouratidis
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 search engines. A breached server that is not detected in time may return incorrect results to the users. To prevent that, we introduce a methodology for generating an integrity proof for each search result. Our solution is targeted at search engines that perform similarity-based document retrieval, and utilize an inverted list implementation (as most search engines do). We formulate the properties that define a correct result, map the task of processing a text search query to adaptations of existing threshold-based …
Critical Success Factors In Soa Implementation, J. Erickson, Keng Siau
Critical Success Factors In Soa Implementation, J. Erickson, Keng Siau
Research Collection School Of Computing and Information Systems
Service Oriented Architecture (SOA) has become flavor du jour for many businesses. Seemingly, almost every company has implemented, is in the midst of implementing or is seriously considering a SOA project. A critical question many organizations are facing now is – what are the critical success factors for SOA implementations? This research aims to identify a list of factors relating to SOA implementation success. A Delphi study forms the research method, and inputs regarding SOA critical success factors are requested from a panel of experts.
Integrating Lightweight Systems Analysis Into The Unified Process By Using Service Responsibility Tables, X. Tan, S. Alter, Keng Siau
Integrating Lightweight Systems Analysis Into The Unified Process By Using Service Responsibility Tables, X. Tan, S. Alter, Keng Siau
Research Collection School Of Computing and Information Systems
This paper is a step toward establishing direct, but non-automatic links between lightweight (semi-formal) analysis methods for business professionals and heavyweight analysis methods for IT professionals. After noting the importance of user involvement in obtaining accurate and meaningful user requirements, the paper summarizes the Unified Process, a software development methodology that employs Unified Modeling Language (UML). Another section in the paper summarizes previous extensions of the work system method that produced a lightweight analysis tool called Service Responsibility Tables (SRTs). This paper uses a straightforward example to demonstrate a set of heuristics for translating between service responsibility tables produced by …
Understanding Factors Influencing Proficient Information Systems Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Understanding Factors Influencing Proficient Information Systems Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Variations exist among information system (IS) users’ abilities to effectively utilize an IS. Some users are able to maximize IS potential, while others are not. This research proposes to understand the attributes of individuals who are most capable of exploiting IS to its fullest potential as well as the management and organizational factors that facilitate the development of highly competent users. The Repertory Grid Technique was utilized to identify user attributes contributing to IS proficiency in Phase One of this research and will be utilized to identify management and organizational factors in Phase Two. The results will provide a comprehensive …
A Lightweight Buyer-Seller Watermarking Protocol, Yongdong Wu, Hwee Hwa Pang
A Lightweight Buyer-Seller Watermarking Protocol, Yongdong Wu, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
The buyer-seller watermarking protocol enables a seller to successfully identify a traitor from a pirated copy, while preventing the seller from framing an innocent buyer. Based on finite field theory and the homomorphic property of public key cryptosystems such as RSA, several buyer-seller watermarking protocols (N. Memon and P. W. Wong (2001) and C.-L. Lei et al. (2004)) have been proposed previously. However, those protocols require not only large computational power but also substantial network bandwidth. In this paper, we introduce a new buyer-seller protocol that overcomes those weaknesses by managing the watermarks. Compared with the earlier protocols, ours is …
Dependence Of Binary Associations On Co-Occurrence Granularity In News Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni, Mastan Vali Shaik
Dependence Of Binary Associations On Co-Occurrence Granularity In News Documents, Krishnaprasad Thirunarayan, Trivikram Immaneni, Mastan Vali Shaik
Kno.e.sis Publications
We describe and formalize an approach to correlate binary associations (such as between entities and events, between persons and events, etc.) implied by News documents on the co-occurrence granularity (such as document-level, paragraph-level, sentence-level, etc.) of the corresponding text phrases in the documents. Specifically, we present both qualitative and quantitative characterization of searching News documents: former in terms of the nature of the content and the queries, and latter in terms of a metric obtained by adapting the notions of precision and recall. Specifically, the approach tries to reduce the manual effort required to analyze the News documents to compare …
Semantic Web: Promising Technologies, Current Applications & Future Directions, Amit P. Sheth
Semantic Web: Promising Technologies, Current Applications & Future Directions, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Description Logic Rules, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Description Logic Rules, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Computer Science and Engineering Faculty Publications
We introduce description logic (DL) rules as a new rule-based formalism for knowledge representation in DLs. As a fragment of the Semantic Web Rule Language SWRL, DL rules allow for a tight integration with DL knowledge bases. In contrast to SWRL, however, the combination of DL rules with expressive description logics remains decidable, and we show that the DL SROIQ – the basis for the ongoing standardisation of OWL 2 – can completely internalise DL rules. On the other hand, DL rules capture many expressive features of SROIQ that are not available in simpler DLs yet. While reasoning in SROIQ …
Boosting With Incomplete Information, Gholamreza Haffari, Yang Wang, Shaojun Wang, Greg Mori, Feng Jiao
Boosting With Incomplete Information, Gholamreza Haffari, Yang Wang, Shaojun Wang, Greg Mori, Feng Jiao
Kno.e.sis Publications
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we present a boosting approach that integrates features with incomplete information and those with complete information to form a strong classifier. By introducing hidden variables to model missing information, we form loss functions that combine fully labeled data with partially labeled data to effectively learn normalized and unnormalized models. The primal problems of the proposed optimization problems with these loss functions are provided to show their close relationship and the motivations behind them. …
Information Technology’S Influence On Productivity, Jason Smith
Information Technology’S Influence On Productivity, Jason Smith
Student Work
Previous research has had mixed results correlating information technology investments to increases in productivity. This research surveyed the perceptions of information technology managers to determine the impact that information technology, decentralized decision making, and improved business processes have on productivity. It concluded that information technology’s influence on productivity is to magnify the effect of decentralized decision making and improved business processes.
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Research Collection School Of Computing and Information Systems
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is not guaranteed to converge to the global optimum. Instead, it stops at some local optimums, which can be much worse than the global optimum.
Tree-Based Partition Querying: A Methodology For Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Tree-Based Partition Querying: A Methodology For Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Research Collection School Of Computing and Information Systems
Besides traditional domains (e.g., resource allocation, data mining applications), algorithms for medoid computation and related problems will play an important role in numerous emerging fields, such as location based services and sensor networks. Since the k-medoid problem is NP hard, all existing work deals with approximate solutions on relatively small datasets. This paper aims at efficient methods for very large spatial databases, motivated by: (i) the high and ever increasing availability of spatial data, and (ii) the need for novel query types and improved services. The proposed solutions exploit the intrinsic grouping properties of a data partition index in order …
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Mobile Interaction Design: Integrating Individual And Organizational Perspectives, Peter Tarasewich, Jun Gong, Fiona Fui-Hoon Nah, David Dewester
Research Collection School Of Computing and Information Systems
While mobile computing provides organizations with many information systems implementation alternatives, it is often difficult to predict the potential benefits, limitations, and problems with mobile applications. Given the inherent portability of mobile devices, many design and use issues can arise which do not exist with desktop systems. While many existing rules of thumb for design of stationary systems apply to mobile systems, many new ones emerge. Issues such as the security and privacy of information take on new dimensions, and potential conflicts can develop when a single mobile device serves both personal and business needs. This paper identifies potential issues …
Semi-Supervised Ensemble Ranking, Steven C. H. Hoi, Rong Jin
Semi-Supervised Ensemble Ranking, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance by combining the outputs from multiple ranking algorithms. Many ensemble ranking approaches employ supervised learning techniques to learn appropriate weights for combining multiple rankers. The main shortcoming with these approaches is that the learned weights for ranking algorithms are query independent. This is suboptimal since a ranking algorithm could perform well for certain queries but poorly for others. In this paper, we propose a novel semi-supervised ensemble ranking (SSER) algorithm that learns query-dependent weights when combining …
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Comments-Oriented Document Summarization: Understanding Documents With Readers' Feedback, Meishan Hu, Aixin Sun, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Comments left by readers on Web documents contain valuable information that can be utilized in different information retrieval tasks including document search, visualization, and summarization. In this paper, we study the problem of comments-oriented document summarization and aim to summarize a Web document (e.g., a blog post) by considering not only its content, but also the comments left by its readers. We identify three relations (namely, topic, quotation, and mention) by which comments can be linked to one another, and model the relations in three graphs. The importance of each comment is then scored by: (i) graph-based method, where the …
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
User Guidance Of Resource-Adaptive Systems, João Pedro Sousa, Rajesh Krishna Balan, Vahe Poladian, David Garlan, Mahadev Satyanarayanan
Research Collection School Of Computing and Information Systems
This paper presents a framework for engineering resource-adaptive software systems targeted at small mobile devices. The proposed framework empowers users to control tradeoffs among a rich set of ervicespecific aspects of quality of service. After motivating the problem, the paper proposes a model for capturing user preferences with respect to quality of service, and illustrates prototype user interfaces to elicit such models. The paper then describes the extensions and integration work made to accommodate the proposed framework on top of an existing software infrastructure for ubiquitous computing. The research question addressed here is the feasibility of coordinating resource allocation and …
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Active Kernel Learning, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A number of kernel learning algorithms have been proposed to learn kernel functions or matrices from side information (e.g., either labeled examples or pairwise constraints). However, most previous studies are limited to “passive” kernel learning in which side information is provided beforehand. In this paper we present a framework of Active Kernel Learning (AKL) that actively identifies the most informative pairwise constraints for kernel learning. The key challenge of active kernel learning is how to measure the informativeness of an example pair given its …
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper presents a self-organizing network model for the fusion of multimedia information. By synchronizing the encoding of information across multiple media channels, the neural model known as fusion Adaptive Resonance Theory (fusion ART) generates clusters that encode the associative mappings across multimedia information in a real-time and continuous manner. In addition, by incorporating a semantic category channel, fusion ART further enables multimedia information to be fused into predefined themes or semantic categories. We illustrate the fusion ART’s functionalities through experiments on two multimedia data sets in the terrorist domain and show the viability of the proposed approach.
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Research Collection School Of Computing and Information Systems
Given a set of data points P and a query point q in a multidimensional space, Reverse Nearest Neighbor (RNN) query finds data points in P whose nearest neighbors are q. Reverse k-Nearest Neighbor (RkNN) query (where k ≥ 1) generalizes RNN query to find data points whose kNNs include q. For RkNN query semantics, q is said to have influence to all those answer data points. The degree of q's influence on a data point p (∈ P) is denoted by κp where q is the κp-th NN of p. We introduce a new variant of RNN query, namely, …
Improving The Availability Of Manufacturability Information Through Decentralization Of Process Planning, Eliab Opiyo
Improving The Availability Of Manufacturability Information Through Decentralization Of Process Planning, Eliab Opiyo
Tanzania Journal of Engineering and Technology (TJET)
Process planning is part of the general product development and production process that usually follows design and precedes manufacturing. Manufacturability and process planning information in general play central role in many product development and production activities, including paradoxically, conceptual and detail design - the activities that take place before process planning. The need of conducting some of the process planning activities formally before or during design is thus rather obvious. One of the main research issues is therefore the identification of the process planning activities that can be performed before the traditional process planning phase and handling of the process …
Open Source Software In Health Information Systems: Opportunities And Challenges, Hashim Twaakyondo
Open Source Software In Health Information Systems: Opportunities And Challenges, Hashim Twaakyondo
Tanzania Journal of Engineering and Technology (TJET)
The paper presents results of a study seeking to identify constraining and motivating factors associated with the adoption and use of Free Open Source Software to computerise health Information Systems in a developing country. The study approach is interpretive research to case study with a triangulation of several qualitative data collection methods such as interviews, group discussions and document analysis. The findings indicate that using open source software has advantages and disadvantages. The advantages are low entry cost to adopting software, possibilities of software localization, avoiding being hostage of proprietary software and foster knowledge acquisition among software developers. The disadvantages …
A Framework For Trust And Distrust Networks, Krishnaprasad Thirunarayan
A Framework For Trust And Distrust Networks, Krishnaprasad Thirunarayan
Kno.e.sis Publications
In this age of internet and electronic commerce it is becoming increasingly important to have and to manipulate information about the trustworthiness of the content or service providers in order to make informed decisions. This paper explores realistic models of trust and distrust based on partially ordered discrete values and proposes a framework, which is sensitive to local, relative ordering of values rather than their magnitudes. The framework distinguishes between direct and inferred trust, preferring direct information over possibly conflicting inferred information. It also represents ambiguity or inconsistency explicitly. The framework is capable of handling general trust and belief networks …
A Forgetting-Based Approach For Reasoning With Inconsistent Distributed Ontologies, Guilin Qi, Yimin Wang, Peter Haase, Pascal Hitzler
A Forgetting-Based Approach For Reasoning With Inconsistent Distributed Ontologies, Guilin Qi, Yimin Wang, Peter Haase, Pascal Hitzler
Computer Science and Engineering Faculty Publications
In the context of multiple distributed ontologies, we are often confronted with the problem of dealing with inconsistency. In this paper, we propose an approach for reasoning with inconsistent distributed ontologies based on concept forgetting. We firstly define concept forgetting in description logics. We then adapt the notions of recoveries and preferred recoveries in propositional logic to description logics. Two consequence relations are then defined based on the preferred recoveries.
The Motivators And Benefits Of Sharing Knowledge To A Kms Repository In An Omani Organization, Kamla Al-Busaidi '05, Lorne Olfman, Terry Ryan, Gondy Leroy
The Motivators And Benefits Of Sharing Knowledge To A Kms Repository In An Omani Organization, Kamla Al-Busaidi '05, Lorne Olfman, Terry Ryan, Gondy Leroy
CGU Faculty Publications and Research
Knowledge is a powerful resource that enables individuals and organizations to achieve several benefits such as improved learning and decisionmaking. Repository knowledge management system (KMS) assists organizations to efficiently capture their knowledge for later reuse. However, the breadth and depth of a knowledge management system depends on the magnitude of knowledge contributed to the system. This paper aimed to empirically investigate the motivators of knowledge sharing behavior and the individual benefits of such behavior in a culture where knowledge is perceived as power and private. Based on 104 employees in a major private petroleum organization in Oman and the partial …
Smartphones To Facilitate Communication And Improve Social Skills Of Children With Severe Autism Spectrum Disorder: Special Education Teachers As Proxies, Gondy Leroy, Gianluca De Leo
Smartphones To Facilitate Communication And Improve Social Skills Of Children With Severe Autism Spectrum Disorder: Special Education Teachers As Proxies, Gondy Leroy, Gianluca De Leo
CGU Faculty Publications and Research
We present an overview of the approach we used and the challenges we encountered while designing software for smartphones to facilitate communication and improve social skills of children with severe autism spectrum disorder (ASD). We employed participatory design, using special education teachers of children with ASD as proxies for our target population.
Graph Summaries For Subgraph Frequency Estimation, Angela Maduko, Kemafor Anyanwu, Amit P. Sheth, Paul Schliekelman
Graph Summaries For Subgraph Frequency Estimation, Angela Maduko, Kemafor Anyanwu, Amit P. Sheth, Paul Schliekelman
Kno.e.sis Publications
A fundamental problem related to graph structured databases is searching for substructures. One issue with respect to optimizing such searches is the ability to estimate the frequency of substructures within a query graph. In this work, we present and evaluate two techniques for estimating the frequency of subgraphs from a summary of the data graph. In the first technique, we assume that edge occurrences on edge sequences are position independent and summarize only the most informative dependencies. In the second technique, we prune small subgraphs using a valuation scheme that blends information about their importance and estimation power. In both …