By Topic

Information Reuse & Integration, 2009. IRI '09. IEEE International Conference on

Date 10-12 Aug. 2009

Filter Results

Displaying Results 1 - 25 of 99
  • Message from Program Co-chairs

    Publication Year: 2009 , Page(s): i
    Save to Project icon | Request Permissions | PDF file iconPDF (58 KB) |  | HTML iconHTML  
    Freely Available from IEEE
  • Forward

    Publication Year: 2009 , Page(s): ii
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (78 KB) |  | HTML iconHTML  

    The following topics are dealt with: fuzzy systems and bioinformatics; data mining; Web services and eBusiness; information reuse; mobile networks and security; software testing; semantic Web and text mining; knowledge management; data visualization; human computer interface; formal methods and software development; schema mapping; database systems; ontology; Web engineering; and natural language processing. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Conference organizers

    Publication Year: 2009 , Page(s): iii
    Save to Project icon | Request Permissions | PDF file iconPDF (83 KB)  
    Freely Available from IEEE
  • International Technical Program Committee

    Publication Year: 2009 , Page(s): iv - vii
    Save to Project icon | Request Permissions | PDF file iconPDF (78 KB)  
    Freely Available from IEEE
  • Computing with Words and perceptions—A paradigm shift

    Publication Year: 2009 , Page(s): viii - x
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | PDF file iconPDF (97 KB) |  | HTML iconHTML  
    Freely Available from IEEE
  • 10th-year anniversary keynote presentation on information reuse and integration

    Publication Year: 2009 , Page(s): xi - xii
    Save to Project icon | Request Permissions | PDF file iconPDF (93 KB)  
    Freely Available from IEEE
  • Building trustworthy semantic webs

    Publication Year: 2009 , Page(s): xiii - xv
    Save to Project icon | Request Permissions | PDF file iconPDF (97 KB)  
    Freely Available from IEEE
  • Efficient reuse and integration at NASA - Its not just the technology

    Publication Year: 2009 , Page(s): xvi - xvii
    Save to Project icon | Request Permissions | PDF file iconPDF (92 KB) |  | HTML iconHTML  
    Freely Available from IEEE
  • Critical need for funding of basic and applied research in large-scale computing

    Publication Year: 2009 , Page(s): xviii
    Save to Project icon | Request Permissions | PDF file iconPDF (73 KB)  
    Freely Available from IEEE
  • Table of contents

    Publication Year: 2009 , Page(s): xix - xxvii
    Save to Project icon | Request Permissions | PDF file iconPDF (152 KB)  
    Freely Available from IEEE
  • Author index

    Publication Year: 2009 , Page(s): xxviii - xxxiv
    Save to Project icon | Request Permissions | PDF file iconPDF (84 KB)  
    Freely Available from IEEE
  • [Copyright notice]

    Publication Year: 2009 , Page(s): xxxv
    Save to Project icon | Request Permissions | PDF file iconPDF (236 KB)  
    Freely Available from IEEE
  • Using contextual information to clarify Gene Normalization ambiguity

    Publication Year: 2009 , Page(s): 1 - 5
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1042 KB) |  | HTML iconHTML  

    The goal of gene normalization (GN) is to identify the unique database identifiers of genes and proteins mentioned in biomedical literature. A major difficulty in GN comes from inter-species gene ambiguity. That is, the same gene name can refer to different database identifiers depending on the species in question. In this paper, we introduce a method to exploit contextual information in an abstract, like tissue type, chromosome location, etc., to tackle this problem. Using this technique, we have been able to improve system performance (F-score) by 14.3% on the BioCreAtIvE-II GN task test set. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Processing of Transcranial Doppler for assessment of blood volume loss

    Publication Year: 2009 , Page(s): 6 - 10
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (163 KB) |  | HTML iconHTML  

    Among all fields of critical patient care, hemorrhagic shock, which is encountered in most traumatic injuries, is a significant factor associated with the chance of survival. Then, it is highly desirable to assess the severity of blood loss and predict the occurrence of hemorrhagic shock (HS) from biomedical signals. In this study, transcranial Doppler (TCD) signal is used to predict and classify the degree of severity of blood loss either as mild, moderate, and severe or as severe and non-severe. The data for this study were generated using the human simulated model of hemorrhage which is called lower body negative pressure (LBNP). The analysis is done by applying discrete wavelet transformation (DWT). The wavelet-based features are defined using the detail and approximate coefficients and machine learning algorithms. The objective of this study is to assess our methods of processing TCD signal for predicting the hemorrhagic. The results of this study show the prediction accuracy of 84.2% achieved by support vector machine for predicting severe/non-severe states. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Semantic data integration and monitoring in the railway domain

    Publication Year: 2009 , Page(s): 11 - 16
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (682 KB) |  | HTML iconHTML  

    Information integration is a key for further growth of efficiency in management decisions for the railway domain. In the context of the EU project InteGRail (funded in the 6th Framework Programme) an integration approach leveraged by ontologies known from the semantic Web and logic-based reasoning mechanisms has been successfully demonstrated. To this effect existing heterogeneous monitoring data acquired across the European railways (in the context of rolling stock, infrastructure, operations and traffic management) is logically integrated according to a formal information model. Based on distributed reasoning mechanism decentralized data and inferred knowledge does not have to be aggregated in a central repository but can be transparently accessed by applications independently from where it is acquire. We explain how the proposed techniques facilitate integration, analysis and interpretation of distributed observation data in the railway domain. Finally the implementation of the presented approach is presented by a demonstration scenario, which integrates existing real-world data for symptom identification and fault detection. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fusion of uncertain information using vague sets and Dempster-Shafer theories

    Publication Year: 2009 , Page(s): 17 - 22
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (519 KB) |  | HTML iconHTML  

    During the process of fusing multi-source information, a challenging problem is how to deal effectively with the available data and information that are vague, imprecise and uncertain. Vague sets are suitable for accurately describing the uncertain information. Dempster-Shafer (D-S) theory is a promising method for the combination of evidence obtained from different source. A new approach is proposed by combining vague sets and D-S theory as there are some similarities between these two theories. By the use of vague sets, characteristics of the factors related to evaluate a component could be described in crisp form and can be represented using belief and plausibility functions defined in D-S theory. Then they are combined using an enhanced weight normalized combination algorithm based on D-S evidence combination rule to reduce the incompleteness and uncertainty. An example is conducted to demonstrate the effectiveness of the proposed method. According to its firm mathematical foundation, the proposed approach can be applied to any bodies of multi-source information fusion without changing the recursive combination algorithm. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Feature selection with biased sample distributions

    Publication Year: 2009 , Page(s): 23 - 28
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (102 KB) |  | HTML iconHTML  

    Feature selection concerns the problem of selecting a number of important features (w.r.t. the class labels) in order to build accurate prediction models. Traditional feature selection methods, however, fail to take the sample distributions into the consideration which may lead to poor predictions for minority class examples. Due to the sophistication and the cost involved in the data collection process, many applications, such as biomedical research, commonly face biased data collections with one class of examples (e.g., diseased samples) significantly less than other classes (e.g., normal samples). For these applications, the minority class examples, such as disease samples, credit card frauds, and network intrusions, are only a small portion of the data collections but deserve full attentions for accurate prediction. In this paper, we propose three filtering techniques, higher weight (HW), differential minority repeat (DMR) and balanced minority repeat (BMR), to identify important features from biased data collections. Experimental comparisons with the ReliefF method on five datasets demonstrate the effectiveness of the proposed methods in selecting informative features from data with biased sample distributions. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An empirical comparison of repetitive undersampling techniques

    Publication Year: 2009 , Page(s): 29 - 34
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (155 KB) |  | HTML iconHTML  

    A common problem for data mining and machine learning practitioners is class imbalance. When examples of one class greatly outnumber examples of the other class (es), traditional machine learning algorithms can perform poorly. Random undersampling is a technique that has shown great potential for alleviating the problem of class imbalance. However, undersampling leads to information loss which can hinder classification performance in some cases. To overcome this problem, repetitive undersampling techniques have been proposed. These techniques generate an ensemble of models, each trained on a different, undersampled subset of the training data. In doing so, less information is lost and classification performance is improved. In this study, we evaluate the performance of several repetitive undersampling techniques. To our knowledge, no study has so thoroughly compared repetitive undersampling techniques. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Aggregating performance metrics for classifier evaluation

    Publication Year: 2009 , Page(s): 35 - 40
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (124 KB) |  | HTML iconHTML  

    There are several performance metrics that have been proposed for evaluating a classification model, e.g., accuracy, error rates, precision, recall, etc. While it is known that evaluating a classifier on only one performance metric is not advisable, the use of multiple performance metrics poses unique comparative challenges for the analyst. Since different performance metrics provide different perspectives into the classifier performance space, it is common for a learner to be relatively better on one performance metric and not better on another performance metric. We present a novel approach to aggregating several individual performance metrics into one metric, called the relative performance metric (RPM). A large case study consisting of 35 real-world classification datasets, 12 classification algorithms, and 10 commonly used performance metrics illustrates the practical appeal of RPM. The empirical results clearly demonstrate the benefits of using RPM when classifier evaluation requires the consideration of a large number of individual performance metrics. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Modeling knowledge discovery in financial forecasting

    Publication Year: 2009 , Page(s): 41 - 46
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (255 KB) |  | HTML iconHTML  

    Knowledge discovery in financial databases has important implications. Decision making process on financial datasets is known to be difficult because of the complex knowledge domain and specific statistical characteristics of the data. In this paper, we investigate the decision making problem on financial datasets such as stock market fluctuations by means of financial ratio measurements while maintaining the interpretable results based on the association rules discovered. We approach this problem by considering different categories of financial ratios as input to the rough set model. A stepwise forecasting procedure is presented together with experimental results. The contribution of the paper is that we have successfully applied the static data mining techniques to the important financial domain and made a user friendly model that benefits individual investors in making investment decisions. We also discuss the extensions to embed the analysis and forecasting model into real time enterprise resources planning (ERP) systems. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A SOA-based approach for the integration of a data propagation system

    Publication Year: 2009 , Page(s): 47 - 52
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (554 KB) |  | HTML iconHTML  

    Major challenges that companies face nowadays are extremely volatile markets, a globally distributed supplier network and constantly changing business environments. These circumstances demand a high level of agility and extraordinary flexibility in the business modeling and the organizational structures of a company as well as adaptive and interoperable IT systems. In order to meet these requirements an integration of systems needs to be achieved. A possible solution for this problem is Champagne, which is a data propagation system that ensures the interoperability of enterprise applications at the data level. However, Champagne provides a tightly-coupled integration of applications and its architecture lacks the needed flexibility to link business processes. These deficiencies can be overcome with the adoption of a service-oriented architecture (SOA), based on loosely-coupled services, which enable a higher level of flexibility and interoperability. Therefore, we explore in this paper a number of options to reuse and integrate champagne into a service-oriented architecture in order to benefit from SOA principles. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • ASOW-Science: A service oriented framework to support e-Science applications

    Publication Year: 2009 , Page(s): 53 - 56
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (566 KB) |  | HTML iconHTML  

    The amount of information generated by biological researches has lead to a huge volume of biomedical data Internet-available. However, data are distributed into heterogeneous biological data sources, with little or even none information organization. Therefore, integration and exchange of data and scientific applications within and among organizations is a need in bioinformatics. In this paper, we introduce the ASOW-Science framework. This framework aims to help scientists collaborate trying to solve the problem of semantic heterogeneity of biological data and applications. ASOW-Science exploits semantic Web services and ontology technology to assist users in discovering and use data and applications available on the Internet. It aims to improve reuse and composition of existent applications and allow semantic validation of data. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Semantic similarity analysis of XML schema using grid computing

    Publication Year: 2009 , Page(s): 57 - 62
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (138 KB) |  | HTML iconHTML  

    A growing number of e-businesses have been using XML schemas in recent years. Schema mapping now plays a crucial role in integrating heterogeneous e-business applications. Since large-scale XML schema mapping using complex and hybrid similarity measures requires significant amount of processing time, a sophisticated similarity analysis algorithm is needed to handle its complexity and performance. In this paper, we focus on designing a service-oriented architecture (SoA) for schema mapping, based on a grid computing technology in order to enhance the effectiveness of the mapping algorithm. After comparing three different grid computing technologies (MPJ, Hadoop, and Globus), we explain why MPJ is the most suitable. We propose SoA XML schema mapping based on MPJ, and demonstrate its performance. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An analysis of the third party payment system based on service supply chain

    Publication Year: 2009 , Page(s): 63 - 67
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (122 KB) |  | HTML iconHTML  

    As an important form of payment, online payment continues to develop and boosts a large number of third party payment companies. With the third party payment companies growing, they gradually have conflict with the bank system. Both the banks and payment companies want to lead the third party payment market. In the third party payment market they are not only collaborators but also competitors. In order to analyze this issue and its deep-seated causes more clearly, this paper introduces the theory of services supply chain and creates a model to analyze the bargaining power of bank and payment company, and come to conditions of equilibrium which will keep the third party payment service supply chain stable. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Integrating services: Control vs. flow

    Publication Year: 2009 , Page(s): 68 - 73
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (552 KB) |  | HTML iconHTML  

    Specification of business processes is becoming a significant aspect of development of Web-based services. Workflows are applied to a business process in order to identify and describe details in the relationships among different business activities. In structuring the relationships among processes, workflows focus mainly on control flow aspects. In this paper we advocate an alternative method for specifying business processes at the conceptual level. The method is based on the principle of separating different types of flows that trigger each other. We first scrutinize current modeling used in workflows, and then introduce our flow-based conceptual description through case studies. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.