
Information and Knowledge Engineering
IKE is an international conference that serves researchers, scholars, professionals, students, and academicians who are looking to both foster working relationships and gain access to the latest research results. It is being held jointly (same location and dates) with a number of other research conferences; namely, The 2014 World Congress in Computer Science, Computer Engineering, and Applied Computing (WORLDCOMP'14). The Congress is among the top five largest annual gathering of researchers in computer science, computer engineering and applied computing. We anticipate to have attendees from about 85 countries/territories. The 2014 Congress will be composed of research presentations, keynote lectures, invited presentations, tutorials, panel discussions, and poster presentations.
31 Slices |
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Session - Information and Knowledge Engineering and Management + Feature Extraction and AI |
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Modeling Shared Drive Utilization Using Stochastic Techniques |
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Int'l Conf. Information and Knowledge Engineering | IKE'14 | 3 Modeling Shared Drive Utilization Using Stochastic Techniques Margret T. Martin, Sarah G. Nurre and Michael R. Grimaila, Senior Member, IEEE Abstract—Information Technology (IT) units provide electronic file shared drives for utilization by personnel in their organization. This shared electronic storage space is used for a wide variety of reasons (e.g., archival, collaboration, backups, dissemination) and is generally focused on providing areas for collaboration, as well as to augment the primary storage disk space located within each user’s computer system. The ways in which shared drives are utilized are highly dependent upon the organizational mission, who can access shared resources, the stability of the user population, end user roles, and the data retention policies enforced by the IT unit. The goal of this research is to understand what happens to information in shared disk storage within an academic institution as a function of time. Academic organizations are unique due to the transitory nature of the user population (e.g., students arrive and depart each year) and by the various roles that exist within the school. By examining the information lifecycle, we can gain insight into the differing perspectives between end users and IT units, the validity of assumptions about information rot and data aging, and develop an understanding how shared storage space is managed. |
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Collaborative Shared Awareness: Human-AI Collaboration |
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10 Int'l Conf. Information and Knowledge Engineering | IKE'14 | Collaborative Shared Awareness: Human-AI Collaboration James A. Crowder, John N. Carbone Raytheon Intelligence, Information, and Services 16800 E. Centretech Parkway, Aurora, Colorado 80011 Abstract - The ability to reason within an autonomous information processing system denotes the ability to infer about information, knowledge, observations and experiences, and affect changes within the system to perform new tasks previously unknown, or to perform tasks already learned more efficiently and effectively [Crowder 1996]. The act of reasoning and inferring allows an autonomous system to construct or modify representations of concepts or knowledge that the system is experiencing and learning. Reasoning allows an Artificially Intelligent System (AIS) to fill in skeletal or incomplete information or specifications about one or more of its domains (selfassessment). The research described here details architectures and algorithms for a cognitive system of |
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Content Management in Digital Libraries |
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Faces Recognition with Image Feature Weights and Least Mean Square Learning Approach |
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Int'l Conf. Information and Knowledge Engineering | IKE'14 | 21 Faces Recognition with Image Feature Weights and Least Mean Square Learning Approach Wei-Li Fang, Ying-Kuei Yang and Jung-Kuei Pan Dept. of Electrical Engineering, National Taiwan Uni. of Sci. & Technology, Taipei, Taiwan Email: yingkyang@yahoo.com Abstract - Most of 2DPCA-enhanced approaches improve face recognition rate while at the expense of computation load. In this paper, an approach is proposed to greatly improve face recognition rate with slightly increased computation load. In this approach, the 2DPCA is applied against a face image to extract important image features for selection. A weight is then assigned to each of selected image features according to the feature’s importance to face recognition. The least mean square (LMS) algorithm is further applied to optimize the feature weights based on the recognition error rate during learning process in order to improve face recognition performance. The experiments have been conducted against |
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A Knowledge Based Selection Framework for Cloud Services |
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26 Int'l Conf. Information and Knowledge Engineering | IKE'14 | A Knowledge Based Selection Framework for Cloud Services Gülfem Isiklar Alptekin1 and S. Emre Alptekin2 Computer Engineering, Galatasaray University, İstanbul, Turkey 2 Industrial Engineering, Galatasaray University, İstanbul, Turkey 1 Abstract - Cloud computing is a scalable services consumption and delivery platform where resources (computational processing power, storage, etc.) are retrieved from the network from anywhere in the world. The inherent complexity and elasticity of the cloud platform products makes their selection a difficult decision for their prospective customers. This paper proposes a multi-criteria based decision support tool which incorporates customer expectations and product attributes and their interrelationships into the decision process. Based on this knowledge the customers are able to rank various alternatives. The proposed knowledge based decision framework is based on quality function deployment and analytic network process. |
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Towards A Knowledge Transfer Measurement for Software Requirements |
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32 Int'l Conf. Information and Knowledge Engineering | IKE'14 | TOWARDS A KNOWLEDGE TRANSFER MEASUREMENT FOR SOFTWARE REQUIREMENTS José Jairo CAMACHO Universidad Nacional de Colombia Bogotá – Colombia jjcamachov@unal.edu.co Jenny Marcela SANCHEZ-TORRES Universidad Nacional de Colombia Bogotá – Colombia jmsanchezt@una.edu.co There has been an increasing interest about knowledge transfer (KT) in software engineering last years, but, less in software requirements (SR) and even less in KT measurement. The purpose of this paper is to make an approach to KT measurement for SR. A mapping from the KT process steps against the software requirements process steps was made, looking for a customized KT process according SR particularities then an approach to metrics were defined for each step. Classic SR metrics are both quantitative and qualitative, none of them related directly with knowledge transfer but with knowledge codification and knowledge sharing. This paper presents the SR process as a KT process obtaining KT oriented FACTORS in one approach to KT measurement in SR. |
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Session - Knowledge and Information Visualization + Imaging Science and Applications |
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Efficient Image Segmentation Algorithm for Mobile Devices |
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Int'l Conf. Information and Knowledge Engineering | IKE'14 | 41 Efficient Image Segmentation Algorithm for Mobile Devices Mark Smith University of Central Arkansas Conway, Arkansas 72035 Abstract An efficient image segmentation algorithm utilized for mobile applications running on the iPhone’s iOS platform is presented. Mobile devices such as the iPhone have limited CPU and memory resources, thus presenting a more challenging task when implementing complex algorithms such as image segmentation. The image segmentation utilized in this work splits the image into real-world objects that are numbered for the user to either select for further processing. First, a color quantization algorithm is applied to the entire image thus simplifying the image to only 16 available colors. Next, a fast texture measurement utilizing the co-occurrence matrix is applied to entire image using a pre-selected neighborhood of interest. Multiple regions are then automatically merged based on a color comparison measurement extracted at each object’s boundary. The resulting regions are then displayed to the user for further analysis or selection. |
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Interactive Visualization of Business Births and Deaths in the U.S. Economy using a Novel Visualization Technique Called HiFi Pie |
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46 Int'l Conf. Information and Knowledge Engineering | IKE'14 | Interactive Visualization of Business Births and Deaths in the U.S. Economy using a Novel Visualization Technique Called HiFi Pie Leonidas Deligiannidis Erik Noyes Professor of Computer Science Wentworth Institute of Technology Boston, MA, USA Associate Professor of Entrepreneurship Babson College Babson Park, MA, USA deligiannidisl@wit.edu enoyes@babson.edu HiFi Pie is a novel technique for interactive information visualization. To illustrate its strength, we explore historic data on new business births and deaths in the U.S. economy. As U.S. Economic Census data continually improves to track the birth and death of new businesses, one can visualize patterns of creative destruction in the U.S. economy, particularly broad historic patterns of whole-economy expansion, all aggregated from industrylevel views of new business births and deaths. A novel, interactive viewer built on the visual language the common pie-chart, HiFi Pie allows economic development organizations focused on entrepreneurship, as well as economists and other policy makers, to visualize new business creation trends, including dynamics of entrepreneurial job creation and industry innovation. |
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Session - Databases, Information Retrieval and Search + Bookmarking Methods + Agent Technologies |
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Bookmarking and Tagging Patterns in Social Bookmarking Systems |
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Int'l Conf. Information and Knowledge Engineering | IKE'14 | 55 Bookmarking and Tagging Patterns in Social Bookmarking Systems Alawya Alawami1 School of information Science, University Of Pittsburgh, Pittsburgh, PA,USA Abstract - Social bookmarking systems are a promising tool for classifying web resources. To be able to use such systems intelligently, it is important to understand how they work. This study takes a look at one such system to examine tagging and bookmarking patterns. The existing literature tends to view these patterns somewhat simplistically. We specifically examine three questions: (1) at what rate do bookmarks accumulate? (2) To what extent do early tags influence later tagging behavior? (3) How do the top 10 tags evolve? Given the influence of the literature on the direction of future research on social bookmarking systems, a more careful analysis may be of use. Keywords: Tagging patterns, Social Bookmarking Systems, Tagging behavior. 1 Introduction With the development of the social web, many interesting tools that focus on the social interaction and collaboration between users have appeared including |
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The Use of Merging Algorithm to Real Ranking for Graph Search |
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62 Int'l Conf. Information and Knowledge Engineering | IKE'14 | The Use of Merging Algorithm to Real Ranking for Graph Search A. Mohammad Reza Nami , B. Mehdi Ebadian Faculty of Electrical, Computer, and IT Engineering, Islamic Azad University- Qazvin Branch, Qazvin, IRAN ABSTRACT Ranking problem is becoming an important issue in many fields, especially in information retrieval. This paper presents an automatic technique for spam monitoring in the graph. The technique is based on combining information from two different sources: Truncated page rank and Semi-Streaming Graph Algorithms. In this paper we conduct further study on the heuristically ranking framework and provide measuring page rank of link farm. Twenty-six articles from 15 venues have been reviewed and classified within the taxonomy in order to organize and structure existing work in the field of Information Retrieval. Keywords Information retrieval (IR), Page rank (PR), Streaming Algorithms, Internet Marketing, Spam and Search Engine Optimization. |
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Keyword Searches with Customized Preferences |
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Int'l Conf. Information and Knowledge Engineering | IKE'14 | 69 Keyword Searches with Customized Preferences Yu-Chin Liu, Yi-Hsuan Chiang and Yu-Lien Hsieh � Abstract—In accordance with the great business opportunities emerging through SNSs, entrepreneurs strive to explore the potential benefits by analyzing data collected from SNSs. For example, Google+ attempts to integrate keyword searches with the individual’s social network. In this paper, we propose a new method for considering the common preferences of friends on social networks while ranking the order of related web pages returned from search engines. The simulation shows the proposed method performing well comparing to general search engines. I. INTRODUCTION I NFORMATION searching has become as one of the most important tasks for on-line information retrieval. At present, there are three main methods of information searching on the Internet: searching by web pages, by directories, and by keywords. For users, tools supporting timely searching are in great demands. |
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Multi-Projects Scheduling Via Non-cooperative Agents Through Heterogeneous Multiprocessor Systems For Energy Efficiency |
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Int'l Conf. Information and Knowledge Engineering | IKE'14 | 73 Multi-Projects Scheduling Via Non-cooperative Agents Through Heterogeneous Multiprocessor Systems For Energy Efficiency Marjan Abdeyazdan1, Mohammad Reza Moini2 1 Department of Computer Engineering, College of Electricity and Computer, Mahshahr branch, Islamic Azad University, Mahshahr, Iran. e-mail: abdeyazdan87@yahoo.com , m.abdeyazdan@mahshahriau.ac.ir 2 Department of Computer Engineering, College of Electricity and Computer, Mahshahr branch, Islamic Azad University, Mahshahr, Iran. e-mail: rezamoini_it@yahoo.com Abstract. Multiprocessor systems started a revolution in high performance computing that brought about fundamental changes in computation. This article examines scheduling of multiprojects, in which each project is assumed as an agent. Scheduling is done by assignment of agents to homogeneous and heterogeneous processors in parallel where every agent is comprised of some tasks and the related tasks in each agent constitute task graphs. Every agent has one initial point and a final point. To go from the initial point to the final point, there are some strategies, namely, various scenarios, which are selected based on the two objectives of minimizing energy consumption |
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Session Data and Information Mining + Forecasting Methods + Simulation + Crowd-Sourcing |
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Identification of Compromised Power System State Variables |
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Int'l Conf. Information and Knowledge Engineering | IKE'14 | 83 Identification of Compromised Power System State Variables Nathan Wallace, Stainislav Ponomarev, and Travis Atkison Deptartments of Electrical Engineering, Cyber Engineering, and Computer Science, Louisiana Tech University, Ruston, LA, United States Abstract— Securing the critical infrastructure power grid is one of the biggest challenges in securing cyberspace. In this environment, control devices are spread across large geographic distances and utilize several mediums for communication. Given the required network topology of the power grid several entry points may exist that can be utilized for compromising a control network. This article explores a cyber event detection scheme based on the Grubbs’ test to classify univariate values. The test is conducted only after a power system instance has been classified as containing a cyber-event. The classification of each instance is made via principal component analysis and the Hoteling’s T2 value. |
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Multidimensional Scaling using Neurofuzzy System and Multivariate Analyses |
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Int'l Conf. Information and Knowledge Engineering | IKE'14 | 89 Multidimensional Scaling using Neurofuzzy System and Multivariate Analyses Deok Hee Nam Engineering and Computing Science, Wilberforce University, Wilberforce, OHIO, USA Abstract - Multidimensional scaling is one of the important techniques for a big data management. In this paper, various statistical analyses are compared to find the best-fitting method for a representation of a higher dimensional data using the reduced or smaller dimensional data using various multivariate analyses with maximum likelihood estimation through the neurofuzzy systems, which estimate the predicted output values. In addition, the estimated results are examined to find the best fitting technique through the comparison of the various statistical criteria. Keywords: data mining, factor analysis, maximum likelihood estimation, multidimensional scaling, neurofuzzy system, principal component analysis 1 Introduction In these days, many scientists are interested in reducing a very large data set efficiently and equivalently without losing any significant meaning of the original data set. |
Details
- Title
- Information and Knowledge Engineering
- Authors
- Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti
- Isbn
- 9781601323231
- Publisher
- CSREA Press
- Imprint
- Price
- 39.95
- Street date
- December 16, 2014
- Format name
- Encrypted
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- Sku
- B000000032175
- Isbn
- 9781601323231
- File size
- 7.91 MB
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- Format name
- Encrypted
- No
- Printing
- Allowed
- Copying
- Allowed
- Read aloud
- Allowed
- Sku
- In metadata
- Isbn
- In metadata
- File size
- In metadata