bluuebunny/crossref_metadata_2025 huggingface dataset:
Ex Ante Evaluations of Alternate Data Structures for End User Queries
Authors: Bowen Paul L. , Rohde Fiona H. , Basford Jay
Published: February 2011

The data structure of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. This research develops a methodology for evaluating, ex ante, the relative desirability of alternative data structures for end user queries. This research theorizes that the data structure that yields the lowest weighted average complexity for a representative sample of information requests is the most desirable data structure for end user queries. The theory was tested in an experiment that compared queries from two different relational database schemas. As theorized, end users querying the data structure associated with the less complex queries performed better. Complexity was measured using three different Halstead metrics. Each of the three metrics provided excellent predictions of end user performance. This research supplies strong evidence that organizations can use complexity metrics to evaluate, ex ante, the desirability of alternate data structures. Organizations can use these evaluations to enhance the efficient and effective retrieval of information by creating data structures that minimize end user query complexity.
Semantic Heterogeneity in Multidatabase Systems
Authors: Wang Te-Wei , Murphy Kenneth E.
Published: February 2011

This article reviews current research on the issue of semantic conflict resolution in multidatabase system design. It is observed that in multidatabase systems, semantic conflicts need to be resolved at both schema level and instance level. Based on the literature review, a new taxonomy for differentiating semantic conflicts and a meta-data representation incorporating the taxonomy are proposed. It is argued that the new meta-data representation is effective for summarizing local schemata, and hence it can serve as a common protocol for multidatabase systems that require instance level conflict resolution.
Information Quality
Authors: English Larry P.
Published: February 2011

Information Quality Management is critical for national security not just because of the myriad information types, including textual, audio, video and other complex information types and to the difficulties in collecting intelligence information, but because of the consequences of failure of national security caused by low-quality information. The diversity and breadth of the number of autonomous or semi-autonomous agencies create complexity in aggregating data from disparately defined databases. Federal laws, an open society, human rights and privacy further hinder the ability to collect, access, aggregate and use certain information. The collection of intelligence information requires rigorous procedures and technologies to error-proof the collection processes, to assure information quality and techniques for analyzing less-than-optimum-quality information. Data definition and database design for information required across multiple agencies can and must be standardized to prevent misinterpretation and analysis failure. Standard Information Quality Management processes with specific considerations applied to address the nature of intelligence information. Cultural transformation within various intelligence community organizations will enable agencies to sustain a level of information quality to minimize the risks of national security process failure.
Semantic Association Identification and Knowledge Discovery for National Security Applications
Authors: Sheth Amit , Aleman-Meza Boanerges , Arpinar I. Budak , Bertram Clemens , Warke Yashodhan , Ramakrishanan Cartic , Halaschek Chris , Anyanwu Kemafar , Avant David , Arpinar F. Sena , Kochut Krys
Published: February 2011

Public and private organizations have access to a vast amount of internal, deep Web and open Web information. Transforming this heterogeneous and distributed information into actionable and insightful information is the key to the emerging new classes of business intelligence and national security applications. Although the role of semantics in search and integration has been often talked about, in this paper we discuss semantic approaches to support analytics on vast amounts of heterogeneous data. In particular, we bring together novel academic research and commercialized Semantic Web technology. The academic research related to semantic association identification is built upon commercial Semantic Web technology for semantic metadata extraction. A prototypical demonstration of this research and technology is presented in the context of an aviation security application of significance to national security.
An Investigation of the Impact of Organization Size on Data Quality Issues
Authors: Nord G. Daryl , Nord Jeretta Horn , Xu Hongjiang
Published: February 2011

Data quality issues have become increasingly critical for information systems applications in organizations of all sizes. This paper presents results from a large-scale Australian survey of Australian CPA members. The research investigates major stakeholders’ opinions on the importance of critical success factors affecting data quality and the actual performance on each of those factors. The results reveal whether dissimilarly-sized organizations differ in the way they measure the importance and performance of critical success factors for data quality in accounting information systems.
BACIIS
Authors: Miled Zina Ben , Li Nianhua , Bukhres Omran
Published: February 2011

Life science Web databases are becoming increasingly essential in conducting everyday biological research. With more than 300 life science Web databases and the growing size of the life science data, searching and managing these complex data requires technology beyond that of traditional database systems. The open research issues include the interoperability of geographically distributed autonomous databases, which are generally only Web-accessible, and the seamless semantic-based integration of these databases with total transparency to the user. In this paper, the implementation of a Biological and Chemical Information Integration System (BACIIS) is presented. BACIIS supports the integration of multiple heterogeneous life science Web databases and allows the execution of global applications that extend beyond the boundaries of individual databases. This paper discusses the architecture of BACIIS. It also discusses the techniques used to extract and integrate data from the various life science Web databases.
Is Extreme Programming Just Old Wine in New Bottles
Authors: Merisalo-Rantanen Hilkka , Tuunanen Tuure , Rossi Matti
Published: February 2011

This article explores extreme programming (XP) as an information systems development approach and argues that it is mainly old wine in new bottles. We take an interpretive and critical view of the phenomenon. We made an empirical study of two companies that apply an XP-style development approach throughout the information systems development life cycle. The results of our research suggest that XP is a combination of best practices of traditional information systems development methods. It is hindered by its reliance on talented individuals, which makes its large-scale deployment as a general-purpose method difficult. We claim that XP can be useful for small teams of domain experts who are physically close together and able to communicate well with the end users, and who are good designers and implementers. However, these skilled and motivated individuals with high working moral can exhibit high productivity regardless of the methods used if they are not overly constrained by bureaucracy.
Knowledge Management Within Collaboration Processes
Authors: Cai Jian
Published: February 2011

Collaborative projects are relatively complex and, hence, are difficult to handle. Managing distributed knowledge among stakeholders in a systematic way is crucial to improving the collaboration productivity. This article provides a generic modeling approach that explicitly represents the perspectives of stakeholders and their evolution traversing a collaborative process. This approach provides a mechanism to analytically identify the interdependencies among stakeholders and to detect conflicts and reveal their intricate causes and effects. Collaboration is thus improved through efficient knowledge management. This article also introduces a Web-based information system that uses the perspective model and the social network analysis methodology to support knowledge management within collaboration.
Ontology-Supported Web Service Composition
Authors: Chen Ye , Zhou Lina , Zhang Dongsong
Published: February 2011

Web service composition can enhance the efficiency and agility of knowledge management by composing individual Web services together for complex business requirements. There are two main research streams in knowledge representation for Web service composition: the syntactic-based approach and the semantic-based approach. Despite the promises brought by each approach, the two streams are largely separated from each other. In this article, we propose an integrated ontology-supported Web service composition framework, which provides a novel solution to organizational knowledge management. By synergistically leveraging both syntactic-based and semantic-based approaches, this framework provides dual modes to perform service composition. Ontologies are employed to enrich semantics at both the service description and composition levels. The proposed conceptual framework has been implemented in the corporate financial services domain. It is demonstrated that the shared ontology helps to fulfill automated and on-the-fly service composition in particular and knowledge management in general.
Preparing Clinical Text for Use in Biomedical Research
Authors: Pestian John P. , Itert Lukasz , Anderson Charlotte , Duch Wlodzislaw
Published: February 2011

Approximately 57 different types of clinical annotations construct a patient’s medical record. These annotations include radiology reports, discharge summaries, and surgical and nursing notes. Hospitals typically produce millions of text-based medical records over the course of a year. These records are essential for the delivery of care, but many are underutilized or not utilized at all for clinical research. The textual data found in these annotations is a rich source of insights into aspects of clinical care and the clinical delivery system. Recent regulatory actions, however, require that, in many cases, data not obtained through informed consent or data not related to the delivery of care must be made anonymous (as referred to by regulators as harmless), before they can be used. This article describes a practical approach with which Cincinnati Children’s Hospital Medical Center (CCHMC), a large pediatric academic medical center with more than 761,000 annual patient encounters, developed open source software for making pediatric clinical text harmless without losing its rich meaning. Development of the software dealt with many of the issues that often arise in natural language processing, such as data collection, disambiguation, and data scrubbing.
Data Warehouse Design to Support Customer Relationship Management Analysis
Authors: Cunningham Colleen , Song Il-Yeol , Chen Peter P.
Published: February 2011

CRM is a strategy that integrates concepts of knowledge management, data mining, and data warehousing in order to support an organization’s decision-making process to retain long-term and profitable relationships with its customers. This research is part of a long-term study to examine systematically CRM factors that affect design decisions for CRM data warehouses in order to build a taxonomy of CRM analyses and to determine the impact of those analyses on CRM data warehousing design decisions. This article presents the design implications that CRM poses to data warehousing and then proposes a robust multidimensional starter model that supports CRM analyses. Additional research contributions include the introduction of two new measures, percent success ratio and CRM suitability ratio by which CRM models can be evaluated, the identification of and classification of CRM queries, and a preliminary heuristic for designing data warehouses to support CRM analyses.
Designing Information Systems Capabilities to Create Business Value
Authors: Langdon Christoph Schlueter
Published: February 2011

Despite Internet success and the fact that software has become the factory in many businesses, questions remain concerning information technology (IT) business value, the IT payoff paradox, and why IT even matters. While numerous econometric studies have established that there is significant business value from IT investments at an aggregate level, it is often unclear how this value accrues specifically and how a particular IS design and specific IS capabilities contribute. Therefore, this article focuses on IT business value (ITBV) antecedents. It analyzes the role of two distinct key IS capabilities: integration and flexibility, which are widely considered central to IS analysis and design. This article is a necessary first step toward decomposing and measuring ITBV antecedents. Subsequent efforts can build on it by developing scales and survey instruments for quantitative-empirical evaluation. This article follows a tradition of theory development adapted and condensed into a four-step approach for IS literature by Zmud (1998), defines and clearly delineates the constructs, and evolves a model that links them with IT business value.
Location-Aware Query Resolution for Location-Based Mobile Commerce
Authors: Wyse James E.
Published: February 2011

Location-based mobile commerce incorporates location-aware technologies, wire-free connectivity, and locationalized Web-based services to support the processing of location-referent transactions. In order to provide usable transaction processing services to mobile consumers, location-referent transactions require timely resolution of queries bearing transaction-related locational criteria. This research evaluates Wyse’s location-aware method of resolving these queries. Results obtained in simulated mobile commerce circumstances (1) reveal the query resolution behavior of the location-aware method, (2) confirm the method’s potential to improve the timeliness of transactional support provided to mobile consumers, and (3) identify the method-related adjustments required to maintain optimal levels of query resolution performance. The article also proposes and provides a preliminary evaluation of a heuristic that may be used in efficiently determining the method-related adjustments needed in order to maximize query resolution performance.
Enterprise Application System Reengineering
Authors: Huang Shi-Ming , Hung Shin-Yuan , Yen David , Li Shing-Han , Wu Chun-Ju
Published: February 2011

Due to the rapid changes in information technology (IT), the life cycle to develop an information system has become significantly shorter. Furthermore, companies worldwide have invested much time and effort in developing their existing enterprise application systems in order to maintain their own competitive advantages. Specifically, they are facing a similar problem of preserving the investment. Information system reengineering technology (ISRT) is one way to solve this problem. However, most of the systems reengineered by using traditional ISRT may lack flexibility and reusability and also have some quality concerns. The component-based software engineering can provide some remedy by providing a flexible and reusable enterprise application system. Many companies could benefit from thinking more in terms of building their own business components for their information system areas. This article considers a reengineering approach in order to migrate legacy systems to component-based information systems with a quality control mechanism. Companies can build their own business component libraries in the reengineering process. One additional benefit is to build information systems from business components rather than reinventing the wheel in the future. This study proposed a system architecture and also implemented the prototype system to validate that our mechanism is technically practical. Additionally, we used an example to evaluate that our approach is effective and practicable in the real world.
Elitist and Ensemble Strategies for Cascade Generalization
Authors: Zhao Huimin , Sinha Atish P. , Ram Sudha
Published: February 2011

Several methods have been proposed for cascading other classification algorithms with decision tree learners to alleviate the representational bias of decision trees and, potentially, to improve classification accuracy. Such cascade generalization of decision trees increases the flexibility of the decision boundaries between classes and promotes better fitting of the training data. However, more flexible models may not necessarily lead to more predictive power. Because of potential overfitting problems, the true classification accuracy on test data may not increase. Recently, a generic method for cascade generalization has been proposed. The method uses a parameter — the maximum cascading depth — to constrain the degree that other classification algorithms are cascaded with decision tree learners. A method for efficiently learning a collection (i.e., a forest) of generalized decision trees, each with other classification algorithms cascaded to a particular depth, also has been developed. In this article, we propose several new strategies, including elitist and ensemble (weighted or unweighted), for using the various decision trees in such a collection in the prediction phase. Our empirical evaluation using 32 data sets in the UCI machine learning repository shows that, on average, the elitist strategy outperforms the weighted full ensemble strategy, which, in turn, outperforms the unweighted full ensemble strategy. However, no strategy is universally superior across all applications. Since the same training process can be used to evaluate the various strategies, we recommend that several promising strategies be evaluated and compared before selecting the one to use for a given application.
A Scalable Middleware for Web Databases
Authors: Bouguettaya Athman , Malik Zaki , Rezgui Abdelmounaam , Korff Lori
Published: February 2011

The emergence of Web databases has introduced new challenges related to their organization, access, integration, and interoperability. New approaches and techniques are needed to provide across-the-board transparency for accessing and manipulating Web databases irrespective of their data models, platforms, locations, or systems. In meeting these needs, it is necessary to build a middleware infrastructure to support flexible tools for information space organization, communication facilities, information discovery, content description, and assembly of data from heterogeneous sources. In this paper, we describe a scalable middleware for efficient data and application access that we have built using the available technologies. The resulting system is called WebFINDIT. It is a scalable and uniform infrastructure for locating and accessing heterogeneous and autonomous databases and applications.
A Measurement Ontology Generalizable for Emerging Domain Applications on the Semantic Web
Authors: Kim Henry M. , Sengupta Arijit , Fox Mark S. , Dalkilic Mehmet
Published: February 2011

This article introduces a measurement ontology for applications to Semantic Web applications, specifically for emerging domains such as microarray analysis. The Semantic Web is the next generation Web of structured data that are automatically shared by software agents, which apply definitions and constraints organized in ontologies to correctly process data from disparate sources. One facet needed to develop Semantic Web ontologies of emerging domains is creating ontologies of concepts that are common to these domains. These general “common-sense” ontologies can be used as building blocks to develop more domain-specific ontologies. However most measurement ontologies concentrate on representing units of measurement and quantities, and not on other measurement concepts such as sampling, mean values, and evaluations of quality based on measurements. In this article, we elaborate on a measurement ontology that represents all these concepts. We present the generality of the ontology, and describe how it is developed, used for analysis and validated.
A Knowledge Integration Approach for Organizational Decision Support
Authors: Kwahk Kee-Young , Kim Hee-Woong , Chan Hock Chuan
Published: February 2011

This study proposes a new methodology that facilitates organizational decision support through knowledge integration across organizational units. For this purpose, this study develops a decision support loop and explains how to organize individual knowledge related to a specific business problem and formulate and test the organized knowledge using cognitive modeling techniques for decision support. This study discusses the proposed approach in the context of an application case involving a beverage company. The application case shows the validity and usefulness of the proposed approach.
Temporal Aggregation Using a Multidimensional Index
Authors: Woo Joon-Ho , Lee Byung Suk , Lee Min-Jae , Loh Woong-Kee , Whang Kyu-Young
Published: February 2011

We present a new method for computing temporal aggregation that uses a multidimensional index. The novelty of our method lies in mapping the start time and end time of a temporal tuple to a data point in a two-dimensional space, which is stored in a two-dimensional index, and in calculating the temporal aggregates through a temporal join between the data in the index and the base intervals (defined as the intervals delimited by the start times or end times of the tuples). To enhance the performance, this method calculates the aggregates by incrementally modifying the aggregates from that of the previous base interval without re-reading all tuples for the current base interval. We have compared our method with the SB-tree, which is the state-of-the-art method for temporal aggregation. The results show that our method is an order of magnitude more efficient than the SB-tree method in an environment with frequent updates, while comparable in a read-only environment as the number of aggregates calculated in a query increases.
BROOD
Authors: Loucopoulos Pericles , Kadir Wan Mohd Nasir Wan
Published: February 2011

A critical success factor for information systems is their ability to evolve as their environment changes. There is compelling evidence that the management of change in business policy can have a profound effect on an information system’s ability to evolve effectively and efficiently. For this to be successful, there is a need to represent business rules from the early requirements stage, expressed in user-understandable terms, to downstream system design components and maintain these throughout the lifecycle of the system. Any user-oriented changes could then be traced and if necessary propagated from requirements to design specifications and evaluated by both end-users and developers about their impact on the system. The BROOD approach, discussed in this article, aims to provide seamless traceability between requirements and system designs through the modelling of business rules and the successive transformations, using UML as the modelling framework.
Exploring the Effects of Process Characteristics on Products Quality in Open Source Software Development
Authors: Koch Stefan , Neumann Christian
Published: February 2011

There has been considerable discussion on the possible impacts of open source software development practices, especially in regard to the quality of the resulting software product. Recent studies have shown that analyzing data from source code repositories is an efficient way to gather information about project characteristics and programmers, showing that OSS projects are very heterogeneous in their team structures and software processes. However, one problem is that the resulting process metrics measuring attributes of the development process and of the development environment do not give any hints about the quality, complexity, or structure of the resulting software. Therefore, we expanded the analysis by calculating several product metrics, most of them specifically tailored to object-oriented software. We then analyzed the relationship between these product metrics and process metrics derived from a CVS repository. The aim was to establish whether different variants of open source development processes have a significant impact on the resulting software products. In particular we analyzed the impact on quality and design associated with the numbers of contributors and the amount of their work, using the GINI coefficient as a measure of inequality within the developer group.
Delivering the Whole Product
Authors: Feller Joseph , Finnegan Patrick , Hayes Jeremy
Published: February 2011

It has been argued that competitive necessities will increasingly require OSS companies to participate in cooperative business networks in order to offer the complete product/service (whole product) demanded by customers. It is envisaged that these business networks will enhance the business models of participant firms by supplementing their value-adding activities and increasing responsiveness to customers. However, while such propositions have intuitive appeal, there is a lack of empirical research on such networks. This article examines Zea Partners, a network of small open source companies cooperating to deliver the ‘whole product’ in the area of content management systems (CMSs). It investigates how participation in the network augments the business models of participant companies and identifies the business agility challenges faced by the network. The article concludes that reconciling the coordination needs of OSS networks with the operational practices of participant firms is a critical issue if such networks are to achieve adaptive efficiency to deliver whole products in a ‘bazaar-friendly’ manner.
A Multiple-Bits Watermark for Relational Data
Authors: Li Yingjiu , Guo Huiping , Wang Shuhong
Published: February 2011

At the heart of the information economy, commercially and publicly useful databases must be sufficiently protected from pirated copying. Complementary to the Database Protection Act, database watermarking techniques are designed to thwart pirated copying by embedding owner-specific information into databases so that the ownership of pirated copies of protected databases can be claimed if the embedded information is detected. This article presents a robust watermarking scheme for embedding a multiple-bits watermark to numerical attributes in database relations. The scheme is robust in the sense that it provides an upper bound for the probability that a valid watermark is detected from unmarked data, or a fictitious secret key is discovered from pirated data. This upper bound is independent of the size of the data. The scheme is extended to database relations without primary-key attributes to thwart attribute-related attacks. The scheme is also extended to multiple watermarks for defending additive attacks and for proving joint ownership.
Web Services, Service-Oriented Computing, and Service-Oriented Architecture
Authors: Erickson John , Siau Keng
Published: February 2011

Service-oriented architecture (SOA), Web services, and service-oriented computing (SOC) have become the buzz words of the day for many in the business world. It seems that virtually every company has implemented, is in the midst of implementing, or is seriously considering SOA projects, Web services projects, or service-oriented computing. A problem many organizations face when entering the SOA world is that there are nearly as many definitions of SOA as there are organizations adopting it. Further complicating the issue is an unclear picture of the value added from adopting the SOA or Web services paradigm. This article attempts to shed some light on the definition of SOA and the difficulties of assessing the value of SOA or Web services via return on investment (ROI) or nontraditional approaches, examines the scant body of evidence empirical that exists on the topic of SOA, and highlights potential research directions in the area.
Theories of Meaning in Schema Matching
Authors: Evermann Joerg
Published: February 2011

Schema matching is the identification of database elements with similar meaning as preparation for subsequent database integration. Over the past 20 years, different schema-matching methods have been proposed and have been shown to be successful to various degrees. However, schema matching is an ongoing research area and the problem is not yet considered to be solved. This article reviews existing schema-matching methods from the perspective of theories of meanings drawn from philosophy and psychology. It positions existing methods, raises questions for future research based on these theories, and shows how these theories can form a firm theoretical basis as well as guide future schema-matching research.
Relaxing Queries with Hierarchical Quantified Data Abstraction
Authors: Shin Myung Keun , Huh Soon Young , Park Donghyun , Lee Wookey
Published: February 2011

Query relaxation is one of the crucial components for approximate query answering. Query relaxation has extensively been investigated in terms of categorical data; few studies, however, have been effectively established for both numerical and categorical data. In this article, we develop a query relaxation method by exploiting hierarchical quantified data abstraction, and a novel method is proposed to quantify the semantic distances between the categorical data so that the query conditions for categorical data are effectively relaxed. We additionally introduce query relaxation algorithms to modify the approximate queries into ordinary queries, which are followed by a series of examples to represent the modification process. Our method outperformed the conventional approaches for the various combinations of complex queries with respect to the cost model and the number of child nodes.
Use Case Diagrams in Support of Use Case Modeling
Authors: Gemino Andrew , Parker Drew
Published: February 2011

Use case modeling in the Unified Modeling Language (UML) is a popular text-based tool for systems analysis and design. Use cases can be used with or without supporting use case diagrams. This paper uses an experiment to explore the effectiveness of including a use case diagram with a set of use cases. The Cognitive Theory of Multimedia Learning is used to hypothesize that the use case diagram improves the effectiveness of use cases for novice users by providing visual cues aiding model viewers in selecting and integrating relevant information. The level of understanding developed by participants viewing either uses cases or use cases with a supporting use case diagram was measured using comprehension, retention, and problem solving tasks. Results showed that participants viewing the use cases with the supporting diagram developed a significantly higher level of understanding, as measured by performance on the problem solving task, than participants provided with use cases alone. This analysis suggests practitioners should consider combining a visual representation, such as a use case diagram, with text-based use cases to achieve higher levels of understanding in persons viewing these descriptions.
Towards Autonomic Workload Management in DBMSs
Authors: Niu Baoning , Martin Patrick , Powley Wendy
Published: February 2011

Workload management is the discipline of effectively managing, controlling, and monitoring work flow across computing systems. It is an increasingly important requirement of database management systems (DBMSs) in view of the trends towards server consolidation and more diverse workloads. Workload management is necessary so the DBMS can be business-objective oriented, can provide efficient differentiated service at fine granularity, and can maintain high utilization of resources with low management costs. The authors see that workload management is shifting from offline planning to online adaptation. In this article, the authors discuss the objectives of workload management in autonomic DBMSs and provide a framework for examining how current workload management mechanisms match up with these objectives. They then use the framework to study several mechanisms from both DBMS products and research efforts. They also propose directions for future work in the area of workload management for autonomic DBMSs.
OOXKSearch
Authors: Taha Kamal , Elmasri Ramez
Published: February 2011

OOXKSearch is a semantic search engine that answers XML keyword-based queries as well as loosely structured queries using Object Oriented techniques. There has been extensive research in XML keyword-based and loosely structured querying. Some frameworks work well for certain types of XML data models while fail in others. The reason is that the proposed techniques are based solely on establishing relationships between individual elements while overlooking the context of these elements. The context of a data element is determined by its parent, because it specifies one of the characteristics of the parent. Since data elements are nothing but characteristics of their parents, we observe that we could treat each parent-children set of elements as one unified entity. We then find semantic relationships between the different unified entities. If two distinct unified entities are semantically related, their data elements are also semantically related. The search performance and quality of OOXKSearch were evaluated experimentally and compared with three recent proposed systems. The results showed marked improvement.
An Integrated Query Relaxation Approach Adopting Data Abstraction and Fuzzy Relation
Authors: Huh Soon-Young , Moon Kae-Hyun , Park Jinsoo
Published: February 2011

This paper proposes a cooperative query answering approach that relaxes query conditions to provide approximate answers by utilizing similarity relationships between data values. The proposed fuzzy abstraction hierarchy (FAH) represents a similarity relationship based on the integrated notion of data abstraction and fuzzy relations. Based on FAH, the authors develop query relaxation operators like query generalization, approximation, and specialization of a value. Compared with existing approaches, FAH supports more effective information retrieval by processing various kinds of cooperative queries through elaborate relaxation control and providing ranked query results according to fitness scores. Moreover, FAH reduces maintenance cost by decreasing the number of similarity relationships to be managed.
Disclosure Control of Confidential Data by Applying Pac Learning Theory
Authors: He Ling , Aytug Haldun , Koehler Gary J.
Published: February 2011

This paper examines privacy protection in a statistical database from the perspective of an intruder using learning theory to discover private information. With the rapid development of information technology, massive data collection is relatively easier and cheaper than ever before. The challenge is how to provide database users with reliable and useful data while protecting the privacy of the confidential information. This paper discusses how to prevent disclosing the identity of unique records in a statistical database. The authors’ research extends previous work and shows how much protection is necessary to prevent an adversary from discovering confidential data with high probability at small error.
A Link-Based Ranking Algorithm for Semantic Web Resources
Authors: Park Hyunjung , Rho Sangkyu , Park Jinsoo
Published: February 2011

The information space of the Semantic Web has different characteristics from that of the World Wide Web (WWW). One main difference is that in the Semantic Web, the direction of Resource Description Framework (RDF) links does not have the same meaning as the direction of hyperlinks in the WWW, because the link direction is determined not by a voting process but by a specific schema in the Semantic Web. Considering this fundamental difference, the authors propose a method for ranking Semantic Web resources independent of link directions and show the convergence of the algorithm and experimental results. This method focuses on the classes rather than the properties. The property weights are assigned depending on the relative significance of the property to the resource importance of each class. It solves some problems reported in prior studies, including the Tightly Knit Community (TKC) effect, as well as having higher accuracy and validity compared to existing methods.
A Study of Open Source Software Development from Control Perspective
Authors: Xu Bo , Lin Zhangxi , Xu Yan
Published: February 2011

Open source software (OSS) has achieved great success and exerted significant impact on the software industry. OSS development takes online community as its organizational form, and developers voluntarily work for the project. In the project execution process, control aligns individual behaviors toward the organizational goals via the Internet and becomes critical to the success of OSS projects. This paper investigates the control modes in OSS project communities, and their effects on project performance. Based on a web survey and archival data from OSS projects, it is revealed that three types of control modes, that is, outcome, clanship, and self-control, are effective in an OSS project community. The study contributes to a better understanding of OSS project organizations and processes, and provides advice for OSS development.
Understanding Business Domain Models
Authors: Poels Geert
Published: February 2011

In this paper, the author investigates the effect on understanding of using business domain models that are constructed with Resource-Event-Agent (REA) modeling patterns. First, the author analyzes REA modeling structures to identify the enabling factors and the mechanisms by means of which users recognize these structures in a conceptual model and description of an information retrieval and interpretation task. Based on this understanding, the author hypothesizes positive effects on model understanding for situations where REA patterns can be recognized in both task and model. An experiment is then conducted to demonstrate a better understanding of models with REA patterns compared to information equivalent models without REA patterns. The results of this experiment indicate that REA patterns can be recognized with minimal prior patterns training and that the use of REA patterns leads to models that are easier to understand for novice model users.
A Survey of Approaches to Web Service Discovery in Service-Oriented Architectures
Authors: Crasso Marco , Zunino Alejandro , Campo Marcelo
Published: February 2011

Discovering services acquires importance as Service-Oriented Computing (SOC) becomes an adopted paradigm. SOC’s most popular materializations, namely Web Services technologies, have different challenges related to service discovery and, in turn, many approaches have been proposed. As these approaches are different, one solution may be better than another according to certain requirements. In consequence, choosing a service discovery system is a hard task. To alleviate this task, this paper proposes eight criteria, based on the requirements for discovering services within common service-oriented environments, allowing the characterization of discovery systems. These criteria cover functional and non-functional aspects of approaches to service discovery. The results of the characterization of 22 contemporary approaches and potential research directions for the area are also shown.
Decision-Making Approach for Catastrophic Scenario Selection in Disaster Recovery Planning
Authors: Ramirez-Marquez Jose Emmanuel , Farr John V.
Published: February 2011

Generally, throughout history, societies have failed to prepare beforehand for potential man made and natural catastrophic events. However, as societies evolve, their view on what can and should be done when affected by these types of events has shifted from a passive acknowledgement that catastrophes will happen, into a proactive stance on planning and organizing resources to mitigate their effects. This paper presents a decision-making based approach for catastrophic scenario selection to guide the process of disaster recovery planning development. The approach proposed can be used to identify the most damaging scenarios in terms of probability of outcome occurrence. Once these scenarios have been identified, the proposed approach produces a set of indices that allow for the computation of similarity, dissimilarity, coverage and exposure for a potential scenario with respect to all possible scenarios. Finally, based on these indices, scenarios are ranked and then selected for disaster recovery plan development.
Context-Based Methodology for Decision Making
Authors: Brezillon Patrick , Brezillon Juliette , Pomerol Jean-Charles
Published: February 2011

Our objective is to support decision makers for improving their behavior by combining bottom-up and top-down approaches. The context-based methodology establishes a conceptual description of behaviors that addresses the initial objective of behavior management. Decision makers’ behaviors are represented in two spaces, namely a behavior space and a situation space. The identification of an “expected behavior” determines the class where the decision maker is and the types of errors associated with this initial class. Validation is realized by the comparison of the “expected” and “effective” behaviors, and the use of scenarios with the same errors but in different contexts allows a second validation. This work, initiated in road safety, is now applicable in other domains where it is more important to work on behaviors of decision makers than decision makers themselves.
The Development of an Organic Agriculture Model
Authors: Rozman Crtomir , Škraba Andrej , Kljajic Miroljub , Pažek Karmen , Bavec Martina , Bavec Franci
Published: February 2011

This article describes the problem state of organic farming development and procedures for modeling by the means of system dynamics, with emphasis on the organic products market. The modeling principles are described in the following steps: problem state formulation, development of causal loop diagrams, model development, scenario analysis and formulation of acceptable strategies. Basic structures developed by the system dynamics principle are presented. The concept of archetypes in the field of organic agriculture modeling is described. The simulation scenarios are formulated as a case study for the Slovenian organic agriculture.
Trusted Platform Validation and Management
Authors: Schmidt Andreas U. , Leicher Andreas , Cha Inhyok , Shah Yogendra
Published: February 2011

Computing platforms are approaching the era of truly distributed and mobile systems. For such large scale deployments of partly autonomously communicating and connecting network elements, trust issues acquire new qualities. Remote establishment of trust and an enabling architecture to manage distributed network elements remotely become essential. Following the authors’ previous analysis on trust establishment, this paper presents base concepts for platform validation and management, with scalable trust properties and flexible security. The presentation is set in context of machine-to-machine communication and intelligent gateways in mobile networks.
Human-Machine Trust Interaction
Authors: Liu Conghui
Published: February 2011

Improving user’s trust appropriately could help in designing an intelligent system and make it work effectively, especially with the fast growth of Web-base technology. This chapter introduces the solutions of improving user’s trust in human-machine interaction (HMI), especially for electronic commerce (e-commerce). The author firstly reviews the concept of trust and the main factors that affects the appropriateness of user’s trust in human-machine interaction, such as the properties of machine systems, the properties of human, and context. On the basis of these, the author further discusses the current state, challenges, problems and limitations of establishing and improving the user’s trust in human-machine interaction. Finally, the author summarizes and evaluates the existing solutions for improving the user’s trust appropriately in e-commerce environment.
Mining Association Rules in Data Warehouses
Authors: Tjioe Haorianto Cokrowijoyo , Taniar David
Published: February 2011

Data mining applications have enormously altered the strategic decision-making processes of organizations. The application of association rules algorithms is one of the well-known data mining techniques that have been developed to cope with multidimensional databases. However, most of these algorithms focus on multidimensional data models for transactional data. As data warehouses can be presented using a multidimensional model, in this paper we provide another perspective to mine association rules in data warehouses by focusing on a measurement of summarized data. We propose four algorithms — VAvg, HAvg, WMAvg, and ModusFilter — to provide efficient data initialization for mining association rules in data warehouses by concentrating on the measurement of aggregate data. Then we apply those algorithms both on a non-repeatable predicate, which is known as mining normal association rules, using GenNLI, and a repeatable predicate using ComDims and GenHLI, which is known as mining hybrid association rules.
Toward a Grid-Based Zero-Latency Data Warehousing Implementation for Continuous Data Streams Processing
Authors: Nguyen Tho Manh , Brezany Peter , Tjoa A. Min , Weippl Edgar
Published: February 2011

Continuous data streams are information sources in which data arrives in high volume in unpredictable rapid bursts. Processing data streams is a challenging task due to (1) the problem of random access to fast and large data streams using present storage technologies and (2) the exact answers from data streams often being too expensive. A framework of building a Grid-based Zero-Latency Data Stream Warehouse (GZLDSWH) to overcome the resource limitation issues in data stream processing without using approximation approaches is specified. The GZLDSWH is built upon a set of Open Grid Service Infrastructure (OGSI)-based services and Globus Toolkit 3 (GT3) with the capability of capturing and storing continuous data streams, performing analytical processing, and reacting autonomously in near real time to some kinds of events based on a well-established knowledge base. The requirements of a GZLDSWH, its Grid-based conceptual architecture, and the operations of its service are described in this paper. Furthermore, several challenges and issues in building a GZLDSWH, such as the Dynamic Collaboration Model between the Grid services, the Analytical Model, and the Design and Evaluation aspects of the Knowledge Base Rules are discussed and investigated.
An Approach to Mining Crime Patterns
Authors: Bagui Sikha
Published: February 2011

This paper presents a knowledge discovery effort to retrieve meaningful information about crime from a U.S. state database. The raw data were preprocessed, and data cubes were created using Structured Query Language (SQL). The data cubes then were used in deriving quantitative generalizations and for further analysis of the data. An entropy-based attribute relevance study was undertaken to determine the relevant attributes. A machine learning software called WEKA was used for mining association rules, developing a decision tree, and clustering. SOM was used to view multidimensional clusters on a regular two-dimensional grid.