bluuebunny/crossref_metadata_2025 huggingface dataset:
Employee Monitoring and Ethics
Authors: Kiser Angelina I. T. , Porter Timothy , Vequist David
Published: February 2011

More advanced technologies that make it possible to monitor employees in the workplace have led to controversies on both legal and ethical grounds. Employers can now easily monitor emails, Internet usage and sites visited, and keystrokes, as well as use GPS systems to track employees’ movements throughout the day. At one end of the spectrum is the employer who claims that monitoring not only improves productivity but is a legal necessity that assists in keeping the company from becoming legally liable for employees’ misuse of technology. Employees, on the other hand, want their privacy protected, and many believe that it is more a matter of them not being trusted. In this paper, an examination is presented that describes various forms of workplace surveillance and monitoring, viewpoints of both employers and employees, policies that companies have implemented, and the ethical and legal implications of such policies.
Binary Equivalents of Ternary Relationships in Entity-Relationship Modeling
Authors: Jones Trevor H. , Song Il-Yeol
Published: February 2011

Little work has been completed which addresses the logical composition and use of ternary relationships in entity-relationship modeling. Many modeling notations and most CASE tools do not allow for ternary relationships. Alternative methods and substitutes for ternary relationship structures do not necessarily reflect the original logic, semantics or constraints of a given situation. Furthermore, it has been shown that ternary relationships can be constrained by additional implicit binary constraints which do not occur in the logic of binary relationships. This paper develops an analytical perspective of ternary relationships. We investigate the logical relationships implicit to the ternary structure and then identify potential simplification through decomposition into binary equivalents. These alternative binary equivalents allow retention of the implicit logical structure, and consequently also retain the semantics of the original structure. The analysis investigates equivalency of lossless decompositions, preservation of functional dependencies and finally the ability to preserve update constraints (insertions and deletions). We identify which ternary relationships have true, fully equivalent, binary equivalents and those which do not. We provide an exhaustive analysis of cardinality combinations found in ternary relationships which practitioners can use to guide the way in which they deal with ternary relationships in conceptual modeling.
Using Business Rules within a Design Process of Active Databases
Authors: Amghar Youssef , Meziane Madjid , Flory Andre
Published: February 2011

Modeling behavior is an important task of the information system engineering process. This task is especially important when information systems are centered on active databases, which allow the replacement of parts of application programs with active rules. To relieve programmers from using either traditional or ad hoc techniques to design active databases, it is necessary to develop new techniques to model business rules. For that reason, inclusion of rules during analysis and design stages becomes an actual requirement. In this paper, we propose a uniform approach to modeling business rules (active rules, integrity constraints, etc. ). To improve the behavior specification, we extend the state diagrams that are widely used for dynamic modeling. This extension is a transformation of state transitions according to rule semantics. In addition, we outline new functionalities of Computer Aided System Engineering (CASE) to take into consideration the active database specificities. In this way, the designer can be assisted to control, maintain, and reuse a set of rules.
Using Weakly Structured Documents to Fill in a Classical Database
Authors: Laforest Frederique , Flory Andre
Published: February 2011

Electronic documents have become a universal way of communication due to Web expansion. But using structured information stored in databases is still essential for data coherence management, querying facilities... We thus face a classical problem known as "impedance mismatch" in the database world: two antagonist approaches have to collaborate. Using documents at the end-user interface level provides simplicity and flexibility. But it is possible to take documents as data sources only if helped by a human being: automatic documents analysis systems have a significant error rate. Databases are an alternative as semantics and format of information are strict: queries via SQL provide 100% correct responses. The aim of this work is to provide a system that associates document capture freedom with database storage structure. The system we propose does not intend to be universal. It can be used in specific cases where people usually work with technical documents dedicated to a particular domain. Our examples concern medicine and more explicitly medical records. Computerization has very often been rejected by physicians because it necessitates too much standardization, and form-based user interfaces are not adapted to their daily practice. In this domain, we think that this study provides a viable alternative approach. This system offers freedom to doctors: they would fill in documents with the information they want to store, in a convenient order and in a more free way. We have developed a system that allows users to fill in a database quasi automatically from document paragraphs. The database used is an already existing database, that can be queried in a classical way for statistical studies or epidemiological purposes. In this system, the document fund and the database containing extractions from documents coexist. Queries are sent to the database, answers include data from the database and references to source documents.
Benchmarking Data Mining Algorithms
Authors: Rajagopalan Balaji , Krovi Ravi
Published: February 2011

Data mining is the process of sifting through the mass of organizational (internal and external) data to identify patterns critical for decision support. Successful implementation of the data mining effort requires a careful assessment of the various tools and algorithms available. The basic premise of this study is that machine-learning algorithms, which are assumption free, should outperform their traditional counterparts when mining business databases. The objective of this study is to test this proposition by investigating the performance of the algorithms for several scenarios. The scenarios are based on simulations designed to reflect the extent to which typical statistical assumptions are violated in the business domain. The results of the computational experiments support the proposition that machine learning algorithms generally outperform their statistical counterparts under certain conditions. These can be used as prescriptive guidelines for the applicability of data mining techniques.
Issues in Mobile Electronic Commerce
Authors: Dogac Asuman , Tumer Arif
Published: February 2011

In this article we address delivering highly personalized context sensitive (i.e., time and location dependent) information to mobile clients. We believe providing highly personalized information to mobile clients from a variety of resources like e-mail servers, Web servers, and content providers will be an important service. Mobile network operators can play a major role in delivering this information to users by being strategically positioned between customers and content/service providers. Currently, many mobile network operators (MNO) and software companies are offering some personalized services. However the level of personalization is limited to choosing from available content links, icons and services. We believe that the mobile clients will benefit from a much higher level of personalization where it is possible to express complex queries involving a variety of data resources. For such a system to gain acceptance by the users, the process of defining personalized information (that is, user profiles) must be very easy for the user. The most important objective of such systems should be to provide scalability, that is, acceptable performance when the number of users increases dramatically. The article also elaborates on the nature of location dependent services.
Metaschemas for ER, ORM and UML Data Models
Authors: Halpin Terry
Published: February 2011

This paper provides metaschemas for some of the main database modeling notations used in industry. Two Entity Relationship (ER) notations (Information Engineering, and Barker) are examined in detail, as well as Object Role Modeling (ORM) conceptual schema diagrams. The discussion of optionality, cardinality and multiplicity is widened to include Unified Modeling Language (UML) class diagrams. Issues addressed in the metamodel analysis include the normalization impact of non-derived constraints on derived associations, the influence of orthogonality on language transparency, and trade-offs between simplicity and expressibility. To facilitate comparision, the same modeling notation is used to display each metaschema. For this purpose, ORM is used because of its greater expressibility and clarity.
The Use of Subtypes and Stereotypes in the UML Model
Authors: Henderson-Sellers Brian
Published: February 2011

Based on users’ experiences of Version 1.3 of the Unified Modeling Language (UML) of the Object Management Group (OMG), a Request For Information in 1999 elicited several responses which were asked to identify “problems” but not to offer any solutions. One of these responses is examined for “problems” relating to the UML metamodel and here some solutions to the problems identified there are proposed. Specifically, we evaluate the metamodel relating to stereotypes versus subtypes; the various kinds of Classifier (particularly Types, Interfaces and Classes); the introduction of a new subtype for the whole-part relationship; as well as identifying areas in the metamodel where the UML seems to have been used inappropriately in the very definition of the UML’s metamodel.
Conceptual Modelling and Ontology
Authors: Weber Ron
Published: February 2011

Conceptual modelling is an activity undertaken during information systems development work to build a representation of selected semantics about some real-world domain. Ontological theories have been developed to account for the structure and behavior of the real world in general. In this paper, I discuss why ontological theories can be used to inform conceptual modelling research, practice, and pedagogy. I provide examples from my research to illustrate how a particular ontological theory has enabled me to improve my understanding of certain conceptual modelling practices and grammars. I describe, also, how some colleagues and I have used this theory to generate several counter-intuitive, sometimes surprising predictions about widely advocated conceptual modelling practices — predictions that subsequently were supported in empirical research we undertook. Finally, I discuss several possibilities and pitfalls I perceive to be associated with our using ontological theories to underpin research on conceptual modelling.
Process-Embedded Data Integrity
Authors: Lee Yang W. , Pipino Leo , Strong Diane M. , Wang Richard Y.
Published: February 2011

Despite the established theory and the history of the practical use of integrity rules, data quality problems, which should be solvable using data integrity rules, persist in organizations. One effective mechanism to solve this problem is to embed data integrity in a continuous data quality improvement process. The result is an iterative data quality improvement process as data integrity rules are defined, violations of these rules are measured and analyzed, and then the rules are redefined to reflect the dynamic and global context of business process changes. Using action research, we study a global manufacturing company that applied these ideas for improving data quality as it built a global data warehouse. This research merges data integrity theory with management theories about quality improvement using a data quality lens, and it demonstrates the usefulness of the combined theory for data quality improvement.
Applying Ontologies to Business and Systems Modelling Techniques and Perspectives
Authors: Green Peter , Rosemann Michael
Published: February 2011

For many years in the area of business systems analysis and design, practitioners and researchers alike have been searching for some comprehensive basis on which to evaluate, compare, and engineer techniques that are promoted for use in the modelling of systems’ requirements. To date, while many frameworks, factors, and facets have been forthcoming, none appear to be based on a sound theory. In light of this dilemma, over the last 10 years, attention has been devoted by researchers to the use of ontology to provide some theoretical basis for the advancement of the business systems modelling discipline. This paper outlines how we have used a particular ontology for this purpose over the last five years. In particular, we have learned that the understandability and the applicability of the selected ontology must be clear for IS professionals, the results of any ontological evaluation must be tempered by economic efficiency considerations of the stakeholders involved, and ontologies may have to be focused for the business purpose and type of user involved in the modelling situation.
Application of Mobile Agents in Mobile Data Access Systems
Authors: Jiao Yu , Hurson Ali R.
Published: February 2011

Creating a global information-sharing environment in the presence of autonomy and heterogeneity of data sources is a difficult task. When adding mobility and wireless medium to this mix, the constraints on bandwidth, connectivity, and resources worsen the problem. Our past research in global information sharing systems resulted in the design, implementation, and prototype of a search engine, the summary schemas model, which supports imprecise global accesses to the data sources while preserving local autonomy. We extended the scope of our search engine by incorporating mobile agent technology. The use of mobile agents alleviates many problems associated with wireless communication. We devised and implemented the MAMDAS system, which applies mobile agent technology in a mobile data access system framework. As shown by our experimental study, MAMDAS achieved better performance, scalability, portability, and robustness compared to its predecessors.
Creating a Dual-Agility Method
Authors: Henderson-Sellers B. , Serour M. K.
Published: February 2011

Agile approaches to software development provide flexibility within the method, but provide little or no flexibility to support software process improvement (SPI). This second kind of flexibility is important to permit organizations to improve with time. To accomplish such improvement, a method-engineering approach is shown here to be useful. Examples of the application of method engineering to agile method construction are given based on the use of the OPEN process framework. A dual-agility method to support both intraproject and interproject flexibility can then be constructed by the selection of appropriate method fragments from this repository with the use of the accompanying guidelines. This is illustrated in an industry study of an organization transitioning to an agile software-development environment in which a minimalistic agile method was first constructed and then enhancements were made as the organization itself improved the process.
Assumptions Underlying Agile Software-Development Processes
Authors: Turk Daniel , France. Robert  , Rumpe Bernhard
Published: February 2011

Agile processes focus on the early facilitation and fast production of working code, and are based on software-development process models that support iterative, incremental development of software. Although agile methods have existed for a number of years now, answers to questions concerning the suitability of agile processes to particular software-development environments are still often based on anecdotal accounts of experiences. An appreciation of the (often unstated) assumptions underlying agile processes can lead to a better understanding of the applicability of agile processes to particular situations. Agile processes are less likely to be applicable in situations in which core assumptions do not hold. This article examines the principles and advocated practices of agile processes to identify underlying assumptions. It also identifies limitations that may arise from these assumptions and outlines how the limitations can be addressed by incorporating other software-development techniques and practices into agile development environments.
Agile Modeling, Agile Software Development, and Extreme Programming
Authors: Erickson John , Lyytinen Kalle , Siau Keng
Published: February 2011

While there are many claims for the successful use of extreme programming (XP) and agile modeling (AM), and the proponents can often be vocal in the extreme regarding their supposed benefits, research evidence supporting proponents‘ claims is somewhat lacking. Currently, the only research appearing to investigate the phenomena consists of two prominent streams. A small number of case studies and experience reports that generally promote the success of XP in various development environments, and a well-established stream of research into pair programming has generated results that in part support the idea of XP. Research into AM appears to be even more sparse than that for XP. Case studies, comparative analyses, and experience reports comprise the majority of the research in the area, while very few empirical research efforts have been conducted. This article reviews the state of research in XP and AM, and recommends areas that could benefit from further study. Since nearly all empirical XP research relates to pair programming, a closer look into the unstudied XP core practices would be beneficial, although interaction between related core practice areas could confound such efforts. It might also be possible to group related core XP concepts and study the groups individually. Finally, there are those who claim that XP and AM, or even agility in general, are really nothing more than a repackaging of old concepts. This claim needs to be investigated.
The Critical Role of Information Processing in Creating an Effective Knowledge Organization
Authors: King William R.
Published: February 2011

This article provides a conceptual framework and an architecture for an effective knowledge organization (EKO) that emphasizes the important role of information processing in facilitating the creation of a dynamic knowledge capability, which is the essence of an EKO. The architecture links core knowledge management, intellectual property management, organizational learning, and innovation modules with information processing as the hub, or linchpin. The organization’s need to distinguish among these components of an EKO is argued by comparing and contrasting the conceptual bases, objectives, processes, systems, performance measures, and culture of each module. This EKO viewpoint integrates many concepts and applications from various literatures, but it is somewhat contrary to the conventional wisdom that has tended to de-emphasize the significance of information technology in knowledge management.
Node Partitioned Data Warehouses
Authors: Furtado Pedro
Published: February 2011

Data Warehouses (DWs) with large quantities of data present major performance and scalability challenges, and parallelism can be used for major performance improvement in such context. However, instead of costly specialized parallel hardware and interconnections, we focus on low-cost standard computing nodes, possibly in a non-dedicated local network. In this environment, special care must be taken with partitioning and processing. We use experimental evidence to analyze the shortcomings of a basic horizontal partitioning strategy designed for that environment, then propose and test improvements to allow efficient placement for the low-cost Node Partitioned Data Warehouse. We show experimentally that extra overheads related to processing large replicated relations and repartitioning requirements between nodes can significantly degrade speedup performance for many query patterns. We analyze a simple, easy-to-apply partitioning and placement decision that achieves good performance improvement results. Our experiments and discussion provide important insight into partitioning and processing issues for data warehouses in shared-nothing environments.
A Framework for Efficient Association Rule Mining in XML Data
Authors: Zhang Ji , Liu Han , Ling Tok Wang , Bruckner Robert M. , Tjoa A Min
Published: February 2011

In this article, we propose a framework, called XAR-Miner, for mining ARs from XML documents efficiently. In XAR-Miner, raw data in the XML document first are preprocessed to transform either to an Indexed XML Tree (IX-tree) or to Multirelational Databases (Multi-DB), depending on the size of the XML document and the memory constraint of the system, for efficient data selection and AR mining. Concepts that are relevant to the AR mining task are generalized to produce generalized metapatterns. A suitable metric is devised for measuring the degree of concept generalization in order to prevent undergeneralization or overgeneralization. Resulting generalized metapatterns are used to generate large ARs that meet the support and confidence levels. A greedy algorithm is also presented in order to integrate data selection and large itemset generation to enhance the efficiency of the AR mining process. The experiments conducted show that XAR-Miner is more efficient in performing a large number of AR mining tasks from XML documents than the state-of-the-art method of repetitively scanning through XML documents in order to perform each of the mining tasks.
Semantic Integrity Constraint Checking for Multiple XML Databases
Authors: Madiraju Praveen , Sunderraman Rajshekhar , Navathe Shamkant B. , Wang Haibin
Published: February 2011

Global semantic integrity constraints ensure integrity and consistency of data spanning multiple databases. In this paper, we take initial steps towards representing global semantic integrity constraints for XML databases. We also provide a general framework for checking global semantic integrity constraints for XML databases. Furthermore, we set forth an efficient algorithm for checking global semantic integrity constraints across multiple XML databases. Our algorithm is efficient for three reasons: (1) the algorithm does not require the update statement to be executed before the constraint check is carried out; hence, we avoid any potential problems associated with rollbacks, (2) sub constraint checks are executed in parallel, and (3) most of the processing of algorithm could happen at compile time; hence, we save time spent at run-time. As a proof of concept, we present a prototype of the system implementing the ideas discussed in this paper.
UB2SQL
Authors: Mammar Amel , Laleau Régine
Published: February 2011

UB2SQL is a tool for designing and developing database applications using UML and B formal method. The approach supported by UB2SQL consists of two successive phases. In the first phase, with the design of applications using class, state and collaboration diagrams, B specifications are automatically generated from UML diagrams; the diagrams are then augmented with these B specifications in place. The second phase deals with the refinement of these B specifications into a relational database implementation, for which UML representation is constructed. In both phases, proofs are achieved to ensure correctness of the obtained B specification and correctness of the refinement process. To overcome the lack of rules and tactics in the B prover, UB2SQL defines specific rules and tactics making the proof task seem like a push-button activity. To increase the usability of UB2SQL in both academic and industrial contexts, the tool has been integrated as a plug-in to the Rational Rose CASE tool. Such integration allows users to develop and be able to visualize graphical UML diagrams and formal B notation in a single environment.
Information Mediation Using Metamodels
Authors: Zhao Luyin , Siau Keng
Published: February 2011

Information mediation is an approach used to resolve heterogeneity of online information sources. This article discusses the concept of information mediation and several related research projects that use a typical mediation model. The problems and issues with existing approaches are discussed. This article then proposes the use of metamodels as an advanced architecture for information mediation, where XML is a main driving force. The new architecture is partly established on the common warehouse metamodel (CWM), a standard adopted by the Object Management Group (OMG). Illustrative examples are presented in the article to describe and discuss the new architecture.
Empirical Assessment of Factors Influencing Success of Enterprise Resource Planning Implementations
Authors: Nah Fiona Fui-Hoon , Islam Zahidul , Tan Mathew
Published: February 2011

Enterprise resource planning (ERP) implementations in multinational manufacturing companies have experienced various degrees of success. This article investigates factors influencing the success of ERP implementations in multinational manufacturing companies in the Malaysian Free Trade Zone. The results indicate that enterprise-wide communication and a project management program are key factors influencing the success of ERP implementations, while other factors such as top management support as well as teamwork and composition are not as critical to the outcome. Organizational culture is a moderator of the relationships between enterprise-wide communication, a project management program, and the success of ERP implementations.
The Impact of Ideology on the Organizational Adoption of Open Source Software
Authors: Ven Kris , Verelst Jan
Published: February 2011

Previous research has shown that the open source movement shares a common ideology. Employees belonging to the open source movement often advocate the use of open source software within their organization. Hence, their belief in the underlying open source software ideology may influence the decision making on the adoption of open source software. This may result in an ideological—rather than pragmatic—decision. A recent study has shown that American organizations are quite pragmatic in their adoption decision. We argue that there may be circumstances in which there is more opportunity for ideological behavior. We therefore investigated the organizational adoption decision in Belgian organizations. Our results indicate that most organizations are pragmatic in their decision making. However, we have found evidence that suggests that the influence of ideology should not be completely disregarded in small organizations.
An Open ECA Server for Active Applications
Authors: Daniel Florian , Pozzi Giuseppe
Published: February 2011

Event monitoring and active behaviors are important aspects in many software systems and application domains, not only in database management systems. In this article, we propose an event-condition-action (ECA) approach that spans from application data to application components and behaviors. Starting from an exception manager we previously developed in the context of a workflow management system, we derived an autonomous active component capable of handling a variety of events and enacting actions in response to detected events. The ECA server runs as an autonomous engine and can be seamlessly integrated with existing systems, thus enhancing the systems’ functionalities and maintainability by separating active and nonactive design concerns.
Applying Learner-Centered Design Principles to UML Sequence Diagrams
Authors: VanderMeer Debra , Dutta kaushik
Published: February 2011

The Unified Modeling Language has been shown to be complex and difficult to learn. The difficulty of learning to build the individual diagrams in the UML, however, has received scant attention. In this article, we consider the case of the UML sequence diagram. Despite the fact that these diagrams are among the most frequently used in practice, they are difficult to learn to build. In this article, we consider the question of why these diagrams remain so difficult to learn to build. Specifically, we analyze the process of learning to build sequence diagrams in the context of cognitive complexity theory. Based on this analysis, and drawing on the theory of learner-centered design, we develop a set of recommendations for presenting the sequence diagram building task to the student analyst to reduce the complexity of learning how to build them.
Co-creation and Collaboration in a Virtual World
Authors: Siau Keng , Nah Fiona Fui-Hoon , Mennecke Brian E. , Schiller Shu Z.
Published: February 2011

One of the most successful and useful implementations of 3D virtual worlds is in the area of education and training. This paper discusses the use of virtual worlds in education and describes an innovative 3D visualization design project using one of the most popular virtual worlds, Second Life. This ongoing project is a partnership between IBM and three universities in the United States: the University of Nebraska-Lincoln, Iowa State University, and Wright State University. More than 400 MBA students have participated in this project by completing a creative design project that involves co-creation and collaboration in Second Life. The MBA students from the three universities worked in pairs to create designs to represent concepts related to IBM Power Systems, a family of IBM servers. The paper discusses observations and reflections on the 3D visualization design project. The paper concludes with a discussion of future research directions in applying virtual worlds in education.
Enabling On-Line Deliberation and Collective Decision-Making through Large-Scale Argumentation
Authors: Iandoli Luca , Klein Mark , Zollo Giuseppe
Published: February 2011

The successful emergence of on-line communities, such as open source software and Wikipedia, seems due to an effective combination of intelligent collective behavior and internet capabilities However, current internet technologies, such as forum, wikis and blogs appear to be less supportive for knowledge organization and consensus formation. In particular very few attempts have been done to support large, diverse, and geographically dispersed groups to systematically explore and come to decisions concerning complex and controversial systemic challenges. In order to overcome the limitations of current collaborative technologies, in this article, we present a new large-scale collaborative platform based on argumentation mapping. To date argumentation mapping has been effectively used for small-scale, co-located groups. The main research questions this work faces are: can argumentation scale? Will large-scale argumentation outperform current collaborative technologies in collective problem solving and deliberation? We present some preliminary results obtained from a first field test of an argumentation platform with a moderate-sized (few hundred) users community.
A Mediator for Biospatial Information Systems
Authors: Barrera Renato , Alcántara Abraham , Alegría Carlos , Ávila Ana L. , Esparza David
Published: February 2011

This article presents a system to enable access to those Information Systems at the National Autonomous University of Mexico (UNAM) that are related to Biodiversity and the Environment. The system in question associates existing Geographic Information Systems (GIS’s) as well as standard relational databases in a federation, allows the contents of the individual GIS (or relational databases) to be consulted in a manner transparent to the user, and permits the exports of the underlying systems’ data under the corresponding set of permissions. Our approach is based upon three principles: compliance with international standards, reliance upon Open Source Software in implementation, and usage of servers of proven reliability and robustness.
Robust Strategic Planning Employing Scenario Planning and Fuzzy Inference System
Authors: Hanafizadeh Payam , Hashemi Ali , Parvin Esmael Salahi
Published: February 2011

Time and uncertainty play crucial roles in the strategic planning process. Organizations are faced with unpredictable changes in new technologies, products and marketplaces but it is noteworthy that they can prepare themselves to face such changes and this readiness results in competitive advantages. This article aims at introducing a method that enables organizations to draw up robust strategies in uncertain situations and leads to formulation of strategies to immunize them against environmental changes. The proposed method has combined ‘scenario planning method’ and ‘fuzzy inference system’ with traditional strategic planning by adopting a new and creative approach. Using the values of uncertain factors in the external environment, this method designs some probable forthcoming scenarios of the organization and then based on fuzzy information described by experts for fuzzy inference systems, defines a robust strategy to deal with the designed scenarios and assists managers in their evaluations of future environment.
An Empirical Study of Group Awareness Information in a Web-Based Group Decision Support System
Authors: Jongsawat Nipat , Premchaiswadi Wichian
Published: February 2011

Group awareness information is important information for group work. It represents group members’ roles and responsibilities, their positions on an issue, their status, and the state of various group processes. The group awareness information presented in this article is designed to capture group member activities and their behaviors in web-based collaborative work. In this article, group awareness information is represented with a visual display and consists of activity and availability information. The application of this proposed scheme is designed and implemented in a web-based group decision support system. This article reports on the results of a study that examined group performance on a given task in a web-based group decision support system with and without group awareness information. The study examined how group awareness information impacts the quality of the work effort and a given task, group decision making by members in the same group and different groups, the communications among group members in the completion of an online collaborative authoring task, the cohesiveness among group members in a web-based group decision support system, and the commitment/disposition of group engagement.
OBIRE
Authors: Liu Xiangyu , Li Maozhen , Liu Yang , Qi Man
Published: February 2011

It has been widely recognized that bibliographic information plays an increasingly important role for scientific research. Peer-to-peer (P2P) networks provide an effective environment for people belonging to a community to share various resources on the Internet. This paper presents OBIRE, an ontology based P2P network for bibliographic information retrieval. For a user query, OBIRE computes the degree of matches to indicate the similarity of a published record to the query. When searching for information, users can incorporate their domain knowledge into their queries which guides OBIRE to discover the bibliographic records that are of most interest of users. In addition, fuzzy logic based user recommendations are used to compute the trustiness of a set of keywords used by a bibliographic record which assists users in selecting bibliographic records. OBIRE is evaluated from the aspects of precision and recall, and experimental results show the effectiveness of OBIRE in bibliographic information retrieval.
Mobile Trusted Computing Based on MTM
Authors: Ekberg Jan-Erik
Published: February 2011

Trusted computing (TC) denotes a set of security-related hardware and software mechanisms that make a computing device work in a consistent manner, even in the presence of external attacks. For personal computers, TC typically is interpreted to be a software architecture designed around the trusted platform module (TPM), a hardware chip residing on the motherboard and implemented according to the specifications of the Trusted Computing Group (Trusted Computing Group, 2008A). In embedded devices, the state-of-the art in terms of hardware security and operating systems is significantly different from what is present on personal computers. So to stimulate the take-up of TCG technology on handsets as well, the recently approved mobile trusted module (MTM) specification (Trusted Computing Group, 2008B) defines new interfaces and adaptation options that match the requirements of the handset business ecosystem, as well as the hardware in use in the embedded domain. This chapter provides an overview of a few hardware security architectures (in handsets) to introduce the reader to the problem domain. The main focus of the text is in introducing the MTM specification – by first presenting its main functional concepts, and then by adapting it to one of the hardware architectures first described, essentially presenting a plausible practical deployment. The author also presents a brief security analysis of the MTM component, and a few novel ideas regarding how the (mobile) trusted module can be extended, and be made more versatile.
Internet Trust as a Specific Form of Technology Trust and its Influence on Online Banking Adoption
Authors: Grabner-Kräuter Sonja , Faullant Rita
Published: February 2011

The construct of trust is important for online banking, because it underlines what is conducive to an enabling online banking environment. This chapter reports on an empirical study of 381 bank customers in Austria that investigates the role of Internet trust as a specific form of technology trust in the context of Internet banking. Furthermore the impact of propensity to trust as a facet of personality on Internet trust is investigated. The findings stress the importance of Internet trust as a determinant of consumer attitudes toward Internet banking and its adoption. In addition, the results show that propensity to trust is a determinant not only for trust in interpersonal relationships but also for trust in technological systems.
A Presentation Model & Non-Traditional Visualization for OLAP
Authors: Maniatis Andreas , Vassiliadis Panos , Skiadopoulos Spiros , Vassiliou Yannis , Mavrogonatos George , Michalarias Ilias
Published: February 2011

Data visualization is one of the major issues of database research. OLAP a decision support technology, is clearly in the center of this effort. Thus far, visualization has not been incorporated in the abstraction levels of DBMS architecture (conceptual, logical, physical); neither has it been formally treated in this context. In this paper we start by reconsidering the separation of the aforementioned abstraction levels to take visualization into consideration. Then, we present the Cube Presentation Model (CPM), a novel presentational model for OLAP screens. The proposal lies on the fundamental idea of separating the logical part of a data cube computation from the presentational part of the client tool. Then, CPM can be naturally mapped on the Table Lens, which is an advanced visualization technique from the Human-Computer Interaction area, particularly tailored for cross-tab reports. Based on the particularities of Table Lens, we propose automated proactive support to the user for the interaction with an OLAP screen. Finally, we discuss implementation and usage issues in the context of an academic prototype system (CubeView) that we have implemented.
Hybrid Query and Data Ordering for Fast and Progressive Range-Aggregate Query Answering
Authors: Shahabi Cyrus , Jahangiri Mehrdad , Sacharidis Dimitri
Published: February 2011

Data analysis systems require range-aggregate query answering of large multidimensional datasets. We provide the necessary framework to build a retrieval system capable of providing fast answers with progressively increasing accuracy in support of range-aggregate queries. In addition, with error forecasting, we provide estimations on the accuracy of the generated approximate results. Our framework utilizes the wavelet transformation of query and data hypercubes. While prior work focused on the ordering of either the query or the data coefficients, we propose a class of hybrid ordering techniques that exploits both query and data wavelets in answering queries progressively. This work effectively subsumes and extends most of the current work where wavelets are used as a tool for approximate or progressive query evaluation. The results of our experimental studies show that independent of the characteristics of the dataset, the data coefficient ordering, contrary to the common belief, is the inferior approach. Hybrid ordering, on the other hand, performs best for scientific datasets that are inter-correlated. For an entirely random dataset with no inter-correlation, query ordering is the superior approach.
Improving Classification Accuracy of Decision Trees for Different Abstraction Levels of Data
Authors: Jeong Mina , Lee Doheon
Published: February 2011

Classification is an important problem in data mining. Given a database of records, each tagged with a class label, a classifier generates a concise and meaningful description for each class that can be used to classify subsequent records. Since the data is collected from disparate sources in many actual data mining environments, it is common to have data values in different abstraction levels. This article introduces the multiple abstraction level problem in decision tree classification, and proposes a method to deal with it. The proposed method adopts the notion of fuzzy relation for solving the multiple abstraction level problem. The experimental results show that the proposed method reduces classification error rates significantly when multiple abstraction levels of data are involved.
Preference-Based Frequent Pattern Mining
Authors: Cho Moonjung , Pei Jian , Wang Haixun , Wang Wei
Published: February 2011

Frequent pattern mining is an important data-mining problem with broad applications. Although there are many in-depth studies on efficient frequent pattern mining algorithms and constraint pushing techniques, the effectiveness of frequent pattern mining remains a serious concern: It is non-trivial and often tricky to specify appropriate support thresholds and proper constraints. In this paper, we propose a novel theme of preference-based frequent pattern mining. A user simply can specify a preference instead of setting detailed parameters in constraints. We identify the problem of preference-based frequent pattern mining and formulate the preferences for mining. We develop an efficient framework to mine frequent patterns with preferences. Interestingly, many preferences can be pushed deep into the mining by properly employing the existing efficient frequent pattern mining techniques. We conduct an extensive performance study to examine our method. The results indicate that preference-based frequent pattern mining is effective and efficient. Furthermore, we extend our discussion from pattern-based frequent pattern mining to preference-based data mining in principle and draw a general framework.
Kernal Width Selection for SVM Classification
Authors: Ali Shawkat , Smith Kate A.
Published: February 2011

The most critical component of kernel-based learning algorithms is the choice of an appropriate kernel and its optimal parameters. In this paper, we propose a rule-based meta-learning approach for automatic radial basis function (RBF) kernel and its parameter selection for Support Vector Machine (SVM) classification. First, the best parameter selection is considered on the basis of prior information of the data with the help of Maximum Likelihood (ML) method and Nelder-Mead (N-M) simplex method. Then, the new rule-based meta-learning approach is constructed and tested on different sizes of 112 datasets with binary class as well as multi-class classification problems. We observe that our rule-based methodology provides significant improvement of computational time as well as accuracy in some specific cases.
Improving Similarity Search in Time Series Using Wavelets
Authors: Liabotis Ioannis , Theodoulidis Babis , Saraaee Mohamad
Published: February 2011

Sequences constitute a large portion of data stored in databases. Data mining applications require the ability to process similarity queries over a large amount of time series data. The query processing performance is an important factor that needs to be taken into consideration. This article proposes a similarity retrieval algorithm for time series. The proposed approach utilizes wavelet transformation in order to reduce the dimensionality of the time series. The transformed series are indexed using X-Trees, which is a spatial indexing technique able to efficiently index high-dimensional data. The article proves that this technique outperforms the usage of the Fourier transformation, since the wavelet transformation provides better approximation of the time series. Through the experiments, it can be concluded that the optimum performance is obtained using 16 to 20 wavelet coefficients. Furthermore, a novel mechanism for reducing the complexity of the calculation for the false alarms removal is proposed. Storing the approximation coefficients of the penultimate level of the decomposition tree, the Euclidean distance between the two sequences is calculated, thus reducing further the number of false alarms before calculating the actual Euclidean distance using the complete time series. The article concludes with a detailed performance evaluation of the proposed similarity retrieval algorithm using data from the Greek stock market and the temperature measurements from Athens. The comparison is done with techniques that use the Haar transform and the R*-Tree, and the proposed algorithm is shown to outperform them.
A Data Mining-Based OLAP Aggregation of Complex Data
Authors: Messaoud Riadh Ben , Boussaid Omar , Rabaséda Sabine Loudcher
Published: February 2011

Nowadays, most organizations deal with complex data that have different formats and come from different sources. The XML formalism is evolving and becoming a promising solution for modeling and warehousing these data in decision support systems. Nevertheless, classical OLAP tools still are not capable of analyzing such data. In this article, we associate OLAP and data mining to cope with advanced analysis on complex data. We provide a generalized OLAP operator, called OpAC, based on the AHC. OpAC is adapted for all types of data, since it deals with data cubes modeled within XML. Our operator enables significant aggregates of facts expressing semantic similarities. Evaluation criteria of aggregates’ partitions are proposed in order to assist the choice of the best partition. Furthermore, we developed a Web application for our operator. We also provide performance experiments and drive a case study on XML documents dealing with the breast cancer research domain.
Evolutionary Induction of Mixed Decision Trees
Authors: Kretowski Marek , Grzes Marek
Published: February 2011

This article presents a new evolutionary algorithm (EA) for induction of mixed decision trees. In nonterminal nodes of a mixed tree, different types of tests can be placed, ranging from a typical inequality test up to an oblique test based on a splitting hyper-plane. In contrast to classical top-down methods, the proposed system searches for an optimal tree in a global manner, that is it learns a tree structure and finds tests in one run of the EA. Specialized genetic operators are developed, which allow the system to exchange parts of trees, generating new sub-trees, pruning existing ones as well as changing the node type and the tests. An informed mutation application scheme is introduced and the number of unprofitable modifications is reduced. The proposed approach is experimentally verified on both artificial and real-life data and the results are promising. Scaling of system performance with increasing training data size was also investigated.