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Articles 5881 - 5910 of 7256
Full-Text Articles in Computer Sciences
The Effects Of Pairing Participants In Facilitated Group Support Systems Sessions, John D. Murphy, Deepak Khazanchi
The Effects Of Pairing Participants In Facilitated Group Support Systems Sessions, John D. Murphy, Deepak Khazanchi
Information Systems and Quantitative Analysis Faculty Proceedings & Presentations
Group Support Systems (GSS) have been used to support facilitated ideation sessions for years and have been studied from a number of different perspectives. Throughout this time the norm for running electronic brainstorming sessions has been for participants to work on their own workstations. A review of applicable literature suggests that pairing participants at GSS workstations could result in higher quality inputs and participant satisfaction. This proposition is examined with a lab experiment to test for differences between paired and unpaired facilitated GSS sessions. The results of the experiment suggest that pairing participants does yield higher quality ideas from facilitated …
Residual-Based Measurement Of Peer And Link Lifetimes In Gnutella Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Residual-Based Measurement Of Peer And Link Lifetimes In Gnutella Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Computer Science Faculty Publications
Existing methods of measuring lifetimes in P2P systems usually rely on the so-called create-based method (CBM), which divides a given observation window into two halves and samples users "created" in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we flrst derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent …
On Node Isolation Under Churn In Unstructured P2p Networks With Heavy-Tailed Lifetimes, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov
On Node Isolation Under Churn In Unstructured P2p Networks With Heavy-Tailed Lifetimes, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov
Computer Science Faculty Publications
Previous analytical studies [12], [18] of unstructured P2P resilience have assumed exponential user lifetimes and only considered age-independent neighbor replacement. In this paper, we overcome these limitations by introducing a general node-isolation model for heavy-tailed user lifetimes and arbitrary neighbor-selection algorithms. Using this model, we analyze two age-biased neighbor-selection strategies and show that they significantly improve the residual lifetimes of chosen users, which dramatically reduces the probability of user isolation and graph partitioning compared to uniform selection of neighbors. In fact, the second strategy based on random walks on age-weighted graphs demonstrates that for lifetimes with infinite variance, the system …
Employing Social Capital By Small & Medium Enterprises To Bear Fruit From Wireless Communications, Abdelnasser Abdelaal, Mehruz Kamal, Peter Wolcott
Employing Social Capital By Small & Medium Enterprises To Bear Fruit From Wireless Communications, Abdelnasser Abdelaal, Mehruz Kamal, Peter Wolcott
Information Systems and Quantitative Analysis Faculty Proceedings & Presentations
Wireless and mobile communications can save Small and Medium Enterprises (SMEs) significant time, money, and effort due to the mobility, flexibility, and ease of use mobile devices provide. SMEs that use such innovations can improve productivity, decrease costs, and enhance the quality of the business process. Lacking technical skills and financial resources, SMEs need special support from local communities and governments in order to survive the severe competition of big chain stores. This paper proposes a model for SMEs to adopt new innovations—those of wireless communications—by employing social capital. We have used a case study approach to show that social …
Cognitive Evaluation Of Information Modeling Methods, Keng Siau, Yuan Wang
Cognitive Evaluation Of Information Modeling Methods, Keng Siau, Yuan Wang
Research Collection School Of Computing and Information Systems
In the field of information system engineering, information modeling method is a technique to capture user requirements and to understand system complexity. The importance of information modeling has been recognized by practitioners and researchers, but little has been explored to analyze the available information modeling methods or to evaluate them in terms of their strengths, weaknesses, and effectiveness. This research analyzes six information-modeling methods: use case diagram, rich picture diagram, entity-relationship diagram, Trochim’s concept mapping, repertory grid, and causal mapping. These information-modeling methods are analyzed from a cognitive perspective in order to better understand their nature, the assumptions, and the …
Analysis Of Topological Characteristics Of Huge Online Social Networking Services, Yong-Yeol Ahn, Seungyeop Han, Haewoon Kwak, Sue Moon, Hawoong Jeong
Analysis Of Topological Characteristics Of Huge Online Social Networking Services, Yong-Yeol Ahn, Seungyeop Han, Haewoon Kwak, Sue Moon, Hawoong Jeong
Research Collection School Of Computing and Information Systems
Social networking services are a fast-growing business in the Internet. However, it is unknown if online relationships and their growth patterns are the same as in real-life social networks. In this paper, we compare the structures of three online social networking services: Cyworld, MySpace, and orkut, each with more than 10 million users, respectively. We have access to complete data of Cyworld's ilchon (friend) relationships and analyze its degree distribution, clustering property, degree correlation, and evolution over time. We also use Cyworld data to evaluate the validity of snowball sampling method, which we use to crawl and obtain partial network …
Learning To Classify E-Mail, Irena Koprinska, Josiah Poon, James Clark, Jason Yuk Hin Chan
Learning To Classify E-Mail, Irena Koprinska, Josiah Poon, James Clark, Jason Yuk Hin Chan
Research Collection School Of Computing and Information Systems
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a supervised learning setting, we investigate the use of random forest for automatic e-mail filing into folders and spam e-mail filtering. We show that random forest is a good choice for these tasks as it runs fast on large and high dimensional databases, is easy to tune and is highly accurate, outperforming popular algorithms such as decision trees, support vector machines and naive Bayes. We introduce a new accurate feature selector with linear time complexity. …
Gprune: A Constraint Pushing Framework For Graph Pattern Mining, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
Gprune: A Constraint Pushing Framework For Graph Pattern Mining, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
Research Collection School Of Computing and Information Systems
In graph mining applications, there has been an increasingly strong urge for imposing user-specified constraints on the mining results. However, unlike most traditional itemset constraints, structural constraints, such as density and diameter of a graph, are very hard to be pushed deep into the mining process. In this paper, we give the first comprehensive study on the pruning properties of both traditional and structural constraints aiming to reduce not only the pattern search space but the data search space as well. A new general framework, called gPrune, is proposed to incorporate all the constraints in such a way that they …
Semantic Web Applications In Industry, Government, Health Care And Life Sciences, Amit P. Sheth
Semantic Web Applications In Industry, Government, Health Care And Life Sciences, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Control Of The Electronic Management Of Information, A. Boone, R. Szatmary Jr.
Control Of The Electronic Management Of Information, A. Boone, R. Szatmary Jr.
Publications (YM)
This procedure establishes the responsibilities and provides direction for developing and evaluating the adequacy of process controls on specific uses of electronically stored information. These uses include, but are not limited to, information used in design input, developed as design output, or developed as input to or output from scientific investigation or performance assessment modeling and analysis. This pertains to information that resides in an electronic information management system or on electronic media.
Spatiotemporal And Thematic Semantic Analytics, Matthew Perry
Spatiotemporal And Thematic Semantic Analytics, Matthew Perry
Kno.e.sis Publications
No abstract provided.
Towards Attack-Resilient Geometric Data Perturbation, Keke Chen, Ling Liu
Towards Attack-Resilient Geometric Data Perturbation, Keke Chen, Ling Liu
Kno.e.sis Publications
Data perturbation is a popular technique for privacy-preserving data mining. The major challenge of data perturbation is balancing privacy protection and data quality, which are normally considered as a pair of contradictive factors. We propose that selectively preserving only the task/model specific information in perturbation would improve the balance. Geometric data perturbation, consisting of random rotation perturbation, random translation perturbation, and noise addition, aims at preserving the important geometric properties of a multidimensional dataset, while providing better privacy guarantee for data classification modeling. The preliminary study has shown that random geometric perturbation can well preserve model accuracy for several popular …
Mining Minimal Distinguishing Subsequence Patterns With Gap Constraints, Xiaonan Ji, James Bailey, Guozhu Dong
Mining Minimal Distinguishing Subsequence Patterns With Gap Constraints, Xiaonan Ji, James Bailey, Guozhu Dong
Kno.e.sis Publications
Discovering contrasts between collections of data is an important task in data mining. In this paper, we introduce a new type of contrast pattern, called a Minimal Distinguishing Subsequence (MDS). An MDS is a minimal subsequence that occurs frequently in one class of sequences and infrequently in sequences of another class. It is a natural way of representing strong and succinct contrast information between two sequential datasets and can be useful in applications such as protein comparison, document comparison and building sequential classification models. Mining MDS patterns is a challenging task and is significantly different from mining contrasts between relational/transactional …
Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau
Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau
Research Collection School Of Computing and Information Systems
Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a corel periphery model as the projects …
A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
One critical task in content-based video retrieval is to rank search results with combinations of multimodal resources effectively. This paper proposes a novel multimodal and multilevel ranking framework for content-based video retrieval. The main idea of our approach is to represent videos by graphs and learn harmonic ranking functions through fusing multimodal resources over these graphs smoothly. We further tackle the efficiency issue by a multilevel learning scheme, which makes the semi-supervised ranking method practical for large-scale applications. Our empirical evaluations on TRECVID 2005 dataset show that the proposed multimodal and multilevel ranking framework is effective and promising for content-based …
A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
One critical task in content-based video retrieval is to rank search results with combinations of multimodal resources effectively. This paper proposes a novel multimodal and multilevel ranking framework for content-based video retrieval. The main idea of our approach is to represent videos by graphs and learn harmonic ranking functions through fusing multimodal resources over these graphs smoothly. We further tackle the efficiency issue by a multilevel learning scheme, which makes the semi-supervised ranking method practical for large-scale applications. Our empirical evaluations on TRECVID 2005 dataset show that the proposed multimodal and multilevel ranking framework is effective and promising for content-based …
Mining Colossal Frequent Patterns By Core Pattern Fusion, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, Hong Cheng
Mining Colossal Frequent Patterns By Core Pattern Fusion, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, Hong Cheng
Research Collection School Of Computing and Information Systems
Extensive research for frequent-pattern mining in the past decade has brought forth a number of pattern mining algorithms that are both effective and efficient. However, the existing frequent-pattern mining algorithms encounter challenges at mining rather large patterns, called colossal frequent patterns, in the presence of an explosive number of frequent patterns. Colossal patterns are critical to many applications, especially in domains like bioinformatics. In this study, we investigate a novel mining approach called Pattern-Fusion to efficiently find a good approximation to the colossal patterns. With Pattern-Fusion, a colossal pattern is discovered by fusing its small core patterns in one step, …
Summarizing Review Scores Of "Unequal" Reviewers, Hady W. Lauw, Ee Peng Lim, Ke Wang
Summarizing Review Scores Of "Unequal" Reviewers, Hady W. Lauw, Ee Peng Lim, Ke Wang
Research Collection School Of Computing and Information Systems
A frequently encountered problem in decision making is the following review problem: review a large number of objects and select a small number of the best ones. An example is selecting conference papers from a large number of submissions. This problem involves two sub-problems: assigning reviewers to each object, and summarizing reviewers ’ scores into an overall score that supposedly reflects the quality of an object. In this paper, we address the score summarization sub-problem for the scenario where a small number of reviewers evaluate each object. Simply averaging the scores may not work as even a single reviewer could …
Using Concept Maps To More Efficiently Create Intelligence Information Models, Christopher E. Coryell
Using Concept Maps To More Efficiently Create Intelligence Information Models, Christopher E. Coryell
Theses and Dissertations
Information models are a critical tool that enables intelligence customers to quickly and accurately comprehend U.S. intelligence agency products. The Knowledge Pre-positioning System (KPS) is the standard repository for information models at the National Air and Space Intelligence Center (NASIC). The current approach used by NASIC to build a KPS information model is laborious and costly. Intelligence analysts design an information model using a manual, butcher-paper-based process. The output of their work is then entered into KPS by either a single NASIC KPS "database modeler" or a contractor (at a cost of roughly $100K to the organization). This thesis proposes …
Multi-Dimensional Range Querying Using A Modification Of The Skip Graph, Gregory J. Brault
Multi-Dimensional Range Querying Using A Modification Of The Skip Graph, Gregory J. Brault
Theses and Dissertations
Skip graphs are an application layer-based distributed routing data structure that can be used in a sensor network to facilitate user queries of data collected by the sensor nodes. This research investigates the impact of a proposed modification to the skip graph proposed by Aspnes and Shah. Nodes contained in a standard skip graph are sorted by their key value into successively smaller groups based on random membership vectors computed locally at each node. The proposed modification inverts the node key and membership vector roles, where group membership is computed deterministically and node keys are computed randomly. Both skip graph …
Towards The Development Of A Defensive Cyber Damage And Mission Impact Methodology, Larry W. Fortson Jr.
Towards The Development Of A Defensive Cyber Damage And Mission Impact Methodology, Larry W. Fortson Jr.
Theses and Dissertations
The purpose of this research is to establish a conceptual methodological framework that will facilitate effective cyber damage and mission impact assessment and reporting following a cyber-based information incidents. Joint and service guidance requires mission impact reporting, but current efforts to implement such reporting have proven ineffective. This research seeks to understand the impediments existing in the current implementation and to propose an improved methodology. The research employed a hybrid historical analysis and case study methodology for data collection through extensive literature review, examination of existing case study research and interviews with Air Force members and civilian personnel employed as …
Tube (Text-Cube) For Discovering Documentary Evidence Of Associations Among Entities, Hady Lauw, Ee Peng Lim, Hwee Hwa Pang
Tube (Text-Cube) For Discovering Documentary Evidence Of Associations Among Entities, Hady Lauw, Ee Peng Lim, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
User-driven discovery of associations among entities, and documents that provide evidence for these associations, is an important search task conducted by researchers and do-main information specialists. Entities here refer to real or abstract objects such as people, organizations, ideologies, etc. Associations are the inter-relationships among entities. Most current works in query-driven document retrieval and finding representative subgraphs are ill-suited for the task as they lack an awareness of entity types as well as an intuitive representation of associations. We propose the TUBE model, a text cube approach for discovering associations and documentary evidence of these associations. The model consists of …
Valuing Information Technology Infrastructures: A Growth Options Approach, Qizhi Dai, Robert J. Kauffman, Salvatore T. March
Valuing Information Technology Infrastructures: A Growth Options Approach, Qizhi Dai, Robert J. Kauffman, Salvatore T. March
Research Collection School Of Computing and Information Systems
Decisions to invest in information technology (IT) infrastructure are often made based on an assessment of its immediate value to the organization. However, an important source of value comes from the fact that such technologies have the potential to be leveraged in the development of future applications. From a real options perspective, IT infrastructure investments create growth options that can be exercised if and when an organization decides to develop systems to provide new or enhanced IT capabilities. We present an analytical model based on real options that shows the process by which this potential is converted into business value, …
Automatic Composition Of Semantic Web Services Using Process And Data Mediation, Zixin Wu, Ajith H. Ranabahu, Karthik Gomadam, Amit P. Sheth, John A. Miller
Automatic Composition Of Semantic Web Services Using Process And Data Mediation, Zixin Wu, Ajith H. Ranabahu, Karthik Gomadam, Amit P. Sheth, John A. Miller
Kno.e.sis Publications
Web service composition has quickly become a key area of research in the services oriented architecture community. One of the challenges in composition is the existence of heterogeneities across independently created and autonomously managed Web service requesters and Web service providers. Previous work in this area either involved significant human effort or in cases of the efforts seeking to provide largely automated approaches, overlooked the problem of data heterogeneities, resulting in partial solutions that would not support executable workflow for real-world problems. In this paper, we present a planning-based approach to solve both the process heterogeneity and data heterogeneity problems. …
Engineering Mathematics Education At Wright State University: Uncorking The First Year Bottleneck, Nathan W. Klingbeil, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds, Richard Mercer
Engineering Mathematics Education At Wright State University: Uncorking The First Year Bottleneck, Nathan W. Klingbeil, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds, Richard Mercer
Kno.e.sis Publications
No abstract provided.
Mining Generalized Associations Of Semantic Relations From Textual Web Content, Tao Jiang, Ah-Hwee Tan, We Wang
Mining Generalized Associations Of Semantic Relations From Textual Web Content, Tao Jiang, Ah-Hwee Tan, We Wang
Research Collection School Of Computing and Information Systems
Traditional text mining techniques transform free text into flat bags of words representation, which does not preserve sufficient semantics for the purpose of knowledge discovery. In this paper, we present a two-step procedure to mine generalized associations of semantic relations conveyed by the textual content of Web documents. First, RDF (resource description framework) metadata representing semantic relations are extracted from raw text using a myriad of natural language processing techniques. The relation extraction process also creates a term taxonomy in the form of a sense hierarchy inferred from WordNet. Then, a novel generalized association pattern mining algorithm (GP-Close) is applied …
Clustering And Combinatorial Optimization In Recursive Supervised Learning, Kiruthika Ramanathan, Sheng Uei Guan
Clustering And Combinatorial Optimization In Recursive Supervised Learning, Kiruthika Ramanathan, Sheng Uei Guan
Research Collection School Of Computing and Information Systems
The use of combinations of weak learners to learn a dataset has been shown to be better than the use of a single strong learner. In fact, the idea is so successful that boosting, an algorithm combining several weak learners for supervised learning, has been considered to be the best off the shelf classifier. However, some problems still exist, including determining the optimal number of weak learners and the over fitting of data. In an earlier work, we developed the RPHP algorithm which solves both these problems by using a combination of global search, weak learning and pattern distribution. In …
A Collaborative, Hierarchical, Incremental, And Problem Solving Information Systems Development Model, Timothy Joseph Burns
A Collaborative, Hierarchical, Incremental, And Problem Solving Information Systems Development Model, Timothy Joseph Burns
Dissertations
The "software crisis" has been a much discussed and debated topic in Information Systems research. A core cause of the crisis is often identified as the methodologies and approaches used to develop information systems. Thus, over the years a multitude of methodologies have emerged in support of quality software. While many of these methodologies have been effective, research has shown that system development is a highly circumstantial process, and that no one methodology can be optimal in every context of every project. It is also a fact that system development practitioners have employed ad hoc approaches to modify formal methodologies …
Survey Of Current Sensor Network Data Management Frameworks, Cory Henson, Satya S. Sahoo
Survey Of Current Sensor Network Data Management Frameworks, Cory Henson, Satya S. Sahoo
Kno.e.sis Publications
No abstract provided.
Revealing The Antecedents And Benefits Of Kms Use: An Exploratory Study In A Petroleum Company In Oman, Kamla Al-Busaidi '05, Lorne Olfman, Terry Ryan, Gondy Leroy
Revealing The Antecedents And Benefits Of Kms Use: An Exploratory Study In A Petroleum Company In Oman, Kamla Al-Busaidi '05, Lorne Olfman, Terry Ryan, Gondy Leroy
CGU Faculty Publications and Research
This pilot study aimed to explore technical and social antecedents and benefits of KMS use in a petroleum company in Oman. Data was collected through questionnaire given to KMS users. From the technical perspective, results uncovered that both knowledge utilizers and contributors were concerned about the system ease of use, speed and integration. Knowledge utilizers also valued knowledge richness in terms of relevancy and timeliness. From the social perspective, both knowledge utilizers and contributors considered time/availability as the major determinant of their behaviors. The results also suggested that knowledge utillizers valued the technical factors more than the social factors, whereas, …