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2009

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Articles 61 - 90 of 824

Full-Text Articles in Physical Sciences and Mathematics

Structured P2p Technologies For Distributed Command And Control, Daniel R. Karrels, Gilbert L. Peterson, Barry E. Mullins Dec 2009

Structured P2p Technologies For Distributed Command And Control, Daniel R. Karrels, Gilbert L. Peterson, Barry E. Mullins

Faculty Publications

The utility of Peer-to-Peer (P2P) systems extends far beyond traditional file sharing. This paper provides an overview of how P2P systems are capable of providing robust command and control for Distributed Multi-Agent Systems (DMASs). Specifically, this article presents the evolution of P2P architectures to date by discussing supporting technologies and applicability of each generation of P2P systems. It provides a detailed survey of fundamental design approaches found in modern large-scale P2P systems highlighting design considerations for building and deploying scalable P2P applications. The survey includes unstructured P2P systems, content retrieval systems, communications structured P2P systems, flat structured P2P systems and …

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To Trust Or Not To Trust? Predicting Online Trusts Using Trust Antecedent Framework, Viet-An Nguyen, Ee Peng Lim, Jing Jiang, Aixin Sun Dec 2009

To Trust Or Not To Trust? Predicting Online Trusts Using Trust Antecedent Framework, Viet-An Nguyen, Ee Peng Lim, Jing Jiang, Aixin Sun

Research Collection School Of Computing and Information Systems

This paper analyzes the trustor and trustee factors that lead to inter-personal trust using a well studied Trust Antecedent framework in management science. To apply these factors to trust ranking problem in online rating systems, we derive features that correspond to each factor and develop different trust ranking models. The advantage of this approach is that features relevant to trust can be systematically derived so as to achieve good prediction accuracy. Through a series of experiments on real data from Epinions, we show that even a simple model using the derived features yields good accuracy and outperforms MoleTrust, a trust …

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Computationally Secure Hierarchical Self-Healing Key Distribution For Heterogeneous Wireless Sensor Networks, Yanjiang Yang, Jianying Zhou, Robert H. Deng, Feng Bao Dec 2009

Computationally Secure Hierarchical Self-Healing Key Distribution For Heterogeneous Wireless Sensor Networks, Yanjiang Yang, Jianying Zhou, Robert H. Deng, Feng Bao

Research Collection School Of Computing and Information Systems

Self-healing group key distribution is a primitive aimed to achieve robust key distribution in wireless sensor networks (WSNs) over lossy communication channels. However, all the existing self-healing group key distribution schemes in the literature are designed for homogenous WSNs that do not scale. In contract, heterogeneous WSNs have better scalability and performance. We are thus motivated to study self-healing group key distribution for heterogeneous WSNs. In particular, we propose the concept of hierarchical self-healing group key distribution, tailored to the heterogeneous WSN architecture; we further revisit and adapt Dutta et al.’s model to the setting of hierarchical self-healing group …

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Classification, Clustering And Data-Mining Of Biological Data, Thomas Triplet Nov 2009

Classification, Clustering And Data-Mining Of Biological Data, Thomas Triplet

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The proliferation of biological databases and the easy access enabled by the Internet is having a beneficial impact on biological sciences and transforming the way research is conducted. There are currently over 1100 molecular biology databases dispersed throughout the Internet. However, very few of them integrate data from multiple sources. To assist in the functional and evolutionary analysis of the abundant number of novel proteins, we introduce the PROFESS (PROtein Function, Evolution, Structure and Sequence) database that integrates data from various biological sources. PROFESS is freely available athttp://cse.unl.edu/~profess/. Our database is designed to be versatile and expandable and will not …

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User Survey Regarding The Needs Of Network Researchers In Trace-Anonymization Tools, Jihwang Yeo, Keren Tan, David Kotz Nov 2009

User Survey Regarding The Needs Of Network Researchers In Trace-Anonymization Tools, Jihwang Yeo, Keren Tan, David Kotz

Computer Science Technical Reports

To understand the needs of network researchers in an anonymization tool, we conducted a survey on the network researchers. We invited network researchers world-wide to the survey by sending invitation emails to well-known mailing lists whose subscribers may be interested in network research with collecting, sharing and sanitizing network traces.

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A Privacy Framework For Mobile Health And Home-Care Systems, David Kotz, Sasikanth Avancha, Amit Baxi Nov 2009

A Privacy Framework For Mobile Health And Home-Care Systems, David Kotz, Sasikanth Avancha, Amit Baxi

Dartmouth Scholarship

In this paper, we consider the challenge of preserving patient privacy in the context of mobile healthcare and home-care systems, that is, the use of mobile computing and communications technologies in the delivery of healthcare or the provision of at-home medical care and assisted living. This paper makes three primary contributions. First, we compare existing privacy frameworks, identifying key differences and shortcomings. Second, we identify a privacy framework for mobile healthcare and home-care systems. Third, we extract a set of privacy properties intended for use by those who design systems and applications for mobile healthcare and home-care systems, linking them …

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Rigid And Non-Rigid Point-Based Medical Image Registration, Nestor Andres Parra Nov 2009

Rigid And Non-Rigid Point-Based Medical Image Registration, Nestor Andres Parra

FIU Electronic Theses and Dissertations

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with …

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On Transport Protocol Performance Measurement Over 10gbps High Speed Optical Networks, Yixin Wu, Suman Kumar, Seung Jong Park Nov 2009

On Transport Protocol Performance Measurement Over 10gbps High Speed Optical Networks, Yixin Wu, Suman Kumar, Seung Jong Park

Computer Science Faculty Research & Creative Works

With the integration of IP and optical technology, fast optical network (of the order of 10Gbps) has emerged to support international research cooperation such as massive scientific data transfer and next generation Internet related research. Therefore, it is important to analyze the measurement issues to guide the high-speed transport protocol research for high-speed optical network of the order of 10Gbps. The objectives of this paper are as follows: i) determine the suitability of TCP parameters such as Jumbo Frame size, TCP sender and receiver buffer sizes; ii) evaluate TCP performance measurement tools and emulation tools over 10Gbps high speed optical …

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Mpcs: Mobile-Based Patient Compliance System For Chronic Illness Care, Guanling Chen, Bo Yan, Minho Shin, David Kotz, Ethan Burke Nov 2009

Mpcs: Mobile-Based Patient Compliance System For Chronic Illness Care, Guanling Chen, Bo Yan, Minho Shin, David Kotz, Ethan Burke

Dartmouth Scholarship

More than 100 million Americans are currently living with at least one chronic health condition and expenditures on chronic diseases account for more than 75 percent of the $2.3 trillion cost of our healthcare system. To improve chronic illness care, patients must be empowered and engaged in health self-management. However, only half of all patients with chronic illness comply with treatment regimen. The self-regulation model, while seemingly valuable, needs practical tools to help patients adopt this self-centered approach for long-term care. \par In this position paper, we propose Mobile-phone based Patient Compliance System (MPCS) that can reduce the time-consuming and …

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Katana: A Hot Patching Framework For Elf Executables, Ashwin Ramaswamy, Sergey Bratus, Michael E. Locasto, Sean W. Smith Nov 2009

Katana: A Hot Patching Framework For Elf Executables, Ashwin Ramaswamy, Sergey Bratus, Michael E. Locasto, Sean W. Smith

Computer Science Technical Reports

Despite advances in software modularity, security, and reliability, offline patching remains the predominant form of updating or protecting commodity software. Unfortunately, the mechanics of hot patching (the process of upgrading a program while it executes) remain understudied, even though such a capability offers practical benefits for both consumer and mission-critical systems. A reliable hot patching procedure would serve particularly well by reducing the downtime necessary for critical functionality or security upgrades. Yet, hot patching also carries the risk -- real or perceived -- of leaving the system in an inconsistent state, which leads many owners to forego its benefits as …

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Classifying Sentence-Based Summaries Of Web Documents, Yiu-Kai D. Ng, Maria Soledad Pera Nov 2009

Classifying Sentence-Based Summaries Of Web Documents, Yiu-Kai D. Ng, Maria Soledad Pera

Faculty Publications

Text classification categorizes Web documents in large collections into predefined classes based on their contents. Unfortunately, the classification process can be time-consuming and users are still required to spend considerable amount of time scanning through the classified Web documents to identify the ones that satisfy their information needs. In solving this problem, we first introduce CorSum, an extractive single-document summarization approach, which is simple and effective in performing the summarization task, since it only relies on word similarity to generate high-quality summaries. Hereafter, we train a Naïve Bayes classifier on CorSum-generated summaries and verify the classification accuracy using the summaries …

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A Gis Hub At Pace University, Peggy Minis, Hsui-Lin Winkler Nov 2009

A Gis Hub At Pace University, Peggy Minis, Hsui-Lin Winkler

Cornerstone 2 Reports : Community Outreach and Empowerment Through Service Learning and Volunteerism

The Thinkfinity Grant is to use technology to develop a GIS Hub at Pace University. The Hub is intended to show the larger community the work done at Pace and to show that our students and faculty are using GIS to solve geographically-based problems for communities and organizations. It also is intended to serve as a site from which users can download data to make their own maps and as a place where the larger community can find examples of maps and have the ability to manipulate maps.

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How Does Politics Affect Electronic Healthcare Adoption, Zanifa Omary, Fredrick Mtenzi, Bing Wu Nov 2009

How Does Politics Affect Electronic Healthcare Adoption, Zanifa Omary, Fredrick Mtenzi, Bing Wu

Conference papers

In the 21 century, the term e-healthcare has become the common buzzword in the world. Its popularity is directly related to the rate of its adoption and benefits that it offers to individuals and governments. Among the common benefits include reduction in medical errors, improvements on physician efficiency, improvement in physician-patient relationship and an increase in the quality of care delivered. Despite all these benefits, politics is one among the obstacles hindering its adoption. In this paper we analyse how politics at local, national and international levels affect e-healthcare adoption and thereafter we suggest appropriate alternatives to overcome these obstacles.

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High-Dimensional Software Engineering Data And Feature Selection, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao Nov 2009

High-Dimensional Software Engineering Data And Feature Selection, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao

Computer Science Faculty Publications

Software metrics collected during project development play a critical role in software quality assurance. A software practitioner is very keen on learning which software metrics to focus on for software quality prediction. While a concise set of software metrics is often desired, a typical project collects a very large number of metrics. Minimal attention has been devoted to finding the minimum set of software metrics that have the same predictive capability as a larger set of metrics – we strive to answer that question in this paper. We present a comprehensive comparison between seven commonly-used filter-based feature ranking techniques (FRT) …

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Activity-Aware Ecg-Based Patient Authentication For Remote Health Monitoring, Janani Sriram, Minho Shin, Tanzeem Choudhury, David Kotz Nov 2009

Activity-Aware Ecg-Based Patient Authentication For Remote Health Monitoring, Janani Sriram, Minho Shin, Tanzeem Choudhury, David Kotz

Dartmouth Scholarship

Mobile medical sensors promise to provide an efficient, accurate, and economic way to monitor patients' health outside the hospital. Patient authentication is a necessary security requirement in remote health monitoring scenarios. The monitoring system needs to make sure that the data is coming from the right person before any medical or financial decisions are made based on the data. Credential-based authentication methods (e.g., passwords, certificates) are not well-suited for remote healthcare as patients could hand over credentials to someone else. Furthermore, one-time authentication using credentials or trait-based biometrics (e.g., face, fingerprints, iris) do not cover the entire monitoring period and …

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Activity-Aware Ecg-Based Patient Authentication For Remote Health Monitoring, Janani Sriram, Minho Shin, Tanzeem Choudhury, David Kotz Nov 2009

Activity-Aware Ecg-Based Patient Authentication For Remote Health Monitoring, Janani Sriram, Minho Shin, Tanzeem Choudhury, David Kotz

Dartmouth Scholarship

Mobile medical sensors promise to provide an efficient, accurate, and economic way to monitor patients' health outside the hospital. Patient authentication is a necessary security requirement in remote health monitoring scenarios. The monitoring system needs to make sure that the data is coming from the right person before any medical or financial decisions are made based on the data. Credential-based authentication methods (e.g., passwords, certificates) are not well-suited for remote healthcare as patients could hand over credentials to someone else. Furthermore, one-time authentication using credentials or trait-based biometrics (e.g., face, fingerprints, iris) do not cover the entire monitoring period and …

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An Anytime Algorithm For Computing Inconsistency Measurement, Yue Ma, Guilin Qi, Guohui Xiao, Pascal Hitzler, Zuoquan Lin Nov 2009

An Anytime Algorithm For Computing Inconsistency Measurement, Yue Ma, Guilin Qi, Guohui Xiao, Pascal Hitzler, Zuoquan Lin

Computer Science and Engineering Faculty Publications

Measuring inconsistency degrees of inconsistent knowledge bases is an important problem as it provides context information for facilitating inconsistency handling. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. In this paper, we consider the computational aspects of inconsistency degrees of propositional knowledge bases under 4-valued semantics. We first analyze its computational complexity. As it turns out that computing the exact inconsistency degree is intractable, we then propose an anytime algorithm that provides tractable approximation of the inconsistency degree from above and below. We show that …

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Smartstore: A New Metadata Organization Paradigm With Semantic-Awareness For Next-Generation File Systems, Yu Hua, Hong Jiang, Yifeng Zhu, Dan Feng, Lei Tian Nov 2009

Smartstore: A New Metadata Organization Paradigm With Semantic-Awareness For Next-Generation File Systems, Yu Hua, Hong Jiang, Yifeng Zhu, Dan Feng, Lei Tian

CSE Conference and Workshop Papers

Existing storage systems using hierarchical directory tree do not meet scalability and functionality requirements for exponentially growing datasets and increasingly complex queries in Exabyte-level systems with billions of files. This paper proposes semantic-aware organization, called SmartStore, which exploits metadata semantics of files to judiciously aggregate correlated files into semantic-aware groups by using information retrieval tools. Decentralized design improves system scalability and reduces query latency for complex queries (range and top-k queries), which is conducive to constructing semantic-aware caching, and conventional filename-based query. SmartStore limits search scope of complex query to a single or a minimal number of semantically related groups …

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Mining Hierarchical Scenario-Based Specifications, David Lo, Shahar Maoz Nov 2009

Mining Hierarchical Scenario-Based Specifications, David Lo, Shahar Maoz

Research Collection School Of Computing and Information Systems

Scalability over long traces, as well as comprehensibility and expressivity of results, are major challenges for dynamic analysis approaches to specification mining. In this work we present a novel use of object hierarchies over traces of inter-object method calls, as an abstraction/refinement mechanism that enables user-guided, top-down or bottom-up mining of layered scenario-based specifications, broken down by hierarchies embedded in the system under investigation. We do this using data mining methods that provide statistically significant sound and complete results modulo user-defined thresholds, in the context of Damm and Harel’s live sequence charts (LSC); a visual, modal, scenario-based, inter-object language. Thus, …

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What Makes Categories Difficult To Classify?, Aixin Sun, Ee Peng Lim, Ying Liu Nov 2009

What Makes Categories Difficult To Classify?, Aixin Sun, Ee Peng Lim, Ying Liu

Research Collection School Of Computing and Information Systems

In this paper, we try to predict which category will be less accurately classified compared with other categories in a classification task that involves multiple categories. The categories with poor predicted performance will be identified before any classifiers are trained and additional steps can be taken to address the predicted poor accuracies of these categories. Inspired by the work on query performance prediction in ad-hoc retrieval, we propose to predict classification performance using two measures, namely, category size and category coherence. Our experiments on 20-Newsgroup and Reuters-21578 datasets show that the Spearman rank correlation coefficient between the predicted rank of …

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Mining Communities In Networks: A Solution For Consistency And Its Evaluation, Haewoon Kwak, Yoonchan Choi, Young-Ho Eom, Hawoong Jeong, Sue Moon Nov 2009

Mining Communities In Networks: A Solution For Consistency And Its Evaluation, Haewoon Kwak, Yoonchan Choi, Young-Ho Eom, Hawoong Jeong, Sue Moon

Research Collection School Of Computing and Information Systems

Online social networks pose significant challenges to computer scientists, physicists, and sociologists alike, for their massive size, fast evolution, and uncharted potential for social computing. One particular problem that has interested us is community identification. Many algorithms based on various metrics have been proposed for communities in networks [18, 24], but a few algorithms scale to very large networks. Three recent community identification algorithms, namely CNM [16], Wakita [59], and Louvain [10], stand out for their scalability to a few millions of nodes. All of them use modularity as the metric of optimization. However, all three algorithms produce inconsistent communities …

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Adaptive Distributed Fair Scheduling For Multiple Channels In Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda Nov 2009

Adaptive Distributed Fair Scheduling For Multiple Channels In Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda

Electrical and Computer Engineering Faculty Research & Creative Works

A novel adaptive and distributed fair scheduling (ADFS) scheme for wireless sensor networks (WSN) in the presence of multiple channels (MC-ADFS) is developed. The proposed MC-ADFS increases available network capacity and focuses on quality-of-service (QoS) issues. when nodes access a shared channel, the proposed MC-ADFS allocates the channel bandwidth proportionally to the packet's weight which indicates the priority of the packet's flow. The packets are dynamically assigned to channels based on the packet weight and current channel utilization. The dynamic assignment of channels is facilitated by use of receiver-based allocation and alternative routes. Moreover, MC-ADFS allows the dynamic allocation of …

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Ensemble And Individual Noise Reduction Method For Induction-Motor Signature Analysis, Zhaoxia Wang, C.S. Chang, Tw Chua, W.W Tan Nov 2009

Ensemble And Individual Noise Reduction Method For Induction-Motor Signature Analysis, Zhaoxia Wang, C.S. Chang, Tw Chua, W.W Tan

Research Collection School Of Computing and Information Systems

Unlike a fixed-frequency power supply, the voltagesupplying an inverter-fed motor is heavily corrupted by noises,which are produced from high-frequency switching leading tonoisy stator currents. To extract useful information from statorcurrentmeasurements, a theoretically sound and robust denoisingmethod is required. The effective filtering of these noisesis difficult with certain frequency-domain techniques, such asFourier transform or Wavelet analysis, because some noises havefrequencies overlapping with those of the actual signals, andsome have high noise-to-frequency ratios. In order to analyze thestatistical signatures of different types of signals, a certainnumber is required of the individual signals to be de-noisedwithout sacrificing the individual characteristic and quantity ofthe …

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Ontology-Driven Provenance Management In Escience: An Application In Parasite Research, Satya S. Sahoo, D. Brent Weatherly, Raghava Mutharaju, Pramod Anantharam, Amit P. Sheth, Rick L. Tarleton Nov 2009

Ontology-Driven Provenance Management In Escience: An Application In Parasite Research, Satya S. Sahoo, D. Brent Weatherly, Raghava Mutharaju, Pramod Anantharam, Amit P. Sheth, Rick L. Tarleton

Kno.e.sis Publications

Provenance, from the French word “provenir”, describes the lineage or history of a data entity. Provenance is critical information in scientific applications to verify experiment process, validate data quality and associate trust values with scientific results. Current industrial scale eScience projects require an end-to-end provenance management infrastructure. This infrastructure needs to be underpinned by formal semantics to enable analysis of large scale provenance information by software applications. Further, effective analysis of provenance information requires well-defined query mechanisms to support complex queries over large datasets. This paper introduces an ontology-driven provenance management infrastructure for biology experiment data, as part …

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Educational Data Mining Approaches For Digital Libraries, Mimi Recker, Sherry Hsi, Beijie Xu, Rob Rothfarb Nov 2009

Educational Data Mining Approaches For Digital Libraries, Mimi Recker, Sherry Hsi, Beijie Xu, Rob Rothfarb

Instructional Technology and Learning Sciences Faculty Publications

This collaborative research project between the Exploratorium and Utah State's Department of Instructional Technology and Learning Sciences investigates online evaluation approaches and the application of educational data mining to educational digital libraries and services. Much work over the past decades has focused on developing algorithms and methods for discovering patterns in large datasets, known as Knowledge Discovery from Data (KDD). Webmetrics, the application of KDD to web usage mining, is growing rapidly in areas such as e-commerce. Educational Data Mining (EDM) is just beginning to emerge as a tool to analyze the massive, longitudinal user data that are captured in …

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Mcc: A Runtime Verification Tool For Mcapi User Applications, Eric G. Mercer, Ganesh Gopalakrishnan, Jim Holt, Subodh Sharma Nov 2009

Mcc: A Runtime Verification Tool For Mcapi User Applications, Eric G. Mercer, Ganesh Gopalakrishnan, Jim Holt, Subodh Sharma

Faculty Publications

We present a dynamic verification tool MCC for Multicore Communication API applications – a new API for communication among cores. MCC systematically explores all relevant interleavings of an MCAPI application using a tailormade dynamic partial order reduction algorithm (DPOR). Our contributions are (i) a way to model the non-overtaking message matching relation underlying MCAPI calls with a high level algorithm to effect DPOR for MCAPI that controls the lower level details so that the intended executions happen at runtime; and (ii) a list of default safety properties that can be utilized in the process of verification. To our knowledge, this …

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A Coherent Measurement Of Web-Search Relevance, William Mahoney, Peter Hospodka, William Sousan, Ryan Nickell, Qiuming Zhu Nov 2009

A Coherent Measurement Of Web-Search Relevance, William Mahoney, Peter Hospodka, William Sousan, Ryan Nickell, Qiuming Zhu

Computer Science Faculty Publications

We present a metric for quantitatively assessing the quality of Web searches. The relevance-of-searching-on-target index measures how relevant a search result is with respect to the searcher's interest and intention. The measurement is established on the basis of the cognitive characteristics of common user's online Web-browsing behavior and processes. We evaluated the accuracy of the index function with respect to a set of surveys conducted on several groups of our college students. While the index is primarily intended to be used to compare the Web-search results and tell which is more relevant, it can be extended to other applications. For …

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Dynamic Load Balancing For I/O-Intensive Applications On Clusters, Xiao Qin, Hong Jiang, Adam Manzanares, Xiaojun Ruan, Shu Yin Nov 2009

Dynamic Load Balancing For I/O-Intensive Applications On Clusters, Xiao Qin, Hong Jiang, Adam Manzanares, Xiaojun Ruan, Shu Yin

School of Computing: Faculty Publications

Load balancing for clusters has been investigated extensively, mainly focusing on the effective usage of global CPU and memory resources. However, previous CPU- or memory-centric load balancing schemes suffer significant performance drop under I/O-intensive workloads due to the imbalance of I/O load. To solve this problem, we propose two simple yet effective I/O-aware load-balancing schemes for two types of clusters: (1) homogeneous clusters where nodes are identical and (2) heterogeneous clusters, which are comprised of a variety of nodes with different performance characteristics in computing power, memory capacity, and disk speed. In addition to assigning I/O-intensive sequential and parallel jobs …

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Why It Managers Don't Go For Cyber-Insurance Products, Tridib Bandyopadhyay, Vijay S. Mookerjee, Ram C. Rao Nov 2009

Why It Managers Don't Go For Cyber-Insurance Products, Tridib Bandyopadhyay, Vijay S. Mookerjee, Ram C. Rao

Faculty and Research Publications

Despite positive expectations, cyber-insurance products have failed to take center stage in the management of IT security risk. Market inexperience, leading to conservatism in pricing cyber-insurance instruments, is often cited as the primary reason for the limited growth of the cyber-insurance market. In contrast, here we provide a demand-side explanation for why cyber-insurance products have not lived up to their initial expectations. We highlight the presence of information asymmetry between customers and providers, showing how it leads to overpricing cyber-insurance contracts and helps explain why cyber insurance might have failed to deliver its promise as a cornerstone of IT security-management …

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Trust Relationship Prediction Using Online Product Review Data, Nan Ma, Ee Peng Lim, Viet-An Nguyen, Aixin Sun Nov 2009

Trust Relationship Prediction Using Online Product Review Data, Nan Ma, Ee Peng Lim, Viet-An Nguyen, Aixin Sun

Research Collection School Of Computing and Information Systems

Trust between users is an important piece of knowledge that can be exploited in search and recommendation.Given that user-supplied trust relationships are usually very sparse, we study the prediction of trust relationships using user interaction features in an online user generated review application context. We show that trust relationship prediction can achieve better accuracy when one adopts personalized and cluster-based classification methods. The former trains one classifier for each user using user-specific training data. The cluster-based method first constructs user clusters before training one classifier for each user cluster. Our proposed methods have been evaluated in a series of experiments …

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