bluuebunny/crossref_metadata_2025 huggingface dataset:
A Dissemination Strategy for the Management of Knowledge in Rural Communities
Authors: Stevens Ken
Published: May 2011

Schools in rural communities of the Canadian province of Newfoundland and Labrador have been reorganized in the last decade. Because of rural to urban migration and the consequent challenge to the continued existence of many small schools, new academically and administratively open structures have been established within an Internet-based environment. Accordingly, traditional closed, autonomous schools in this province have increasingly become open sites within Internet-linked teaching and learning environments. What began as a research project linking eight schools in a single Digital Intranet has been extended to include schools across the province managed by a recently established branch of the Department of Education of Newfoundland and Labrador—the Centre for Distance Learning and Innovation. This chapter provides an outline of how information and communication technologies have been used to reshape education in a predominantly rural Canadian province, thereby preparing people for participation in the emerging knowledge-based economy.
Caribbean Companies and the Information Superhighway
Authors: Fraser Simon
Published: May 2011

With the explosion of public awareness of the Internet in the early 1990s, much attention has been focused on ways in which these new technologies can be used in developing nations. Some of the primary proponents of these initiatives include the World Bank, The United Nations Conference on Trade and Development (UNCTAD) and the Inter American Development Bank. The major themes include ways in which the Internet and electronic commerce can be harnessed for development, impediments to rapid diffusion of Internet technologies and success stories in small and medium companies.
The E-Pabelan National ICT4PR Pilot Project
Authors: Robinson Alex
Published: May 2011

The chapter presents a case study of an ICT-based attempt to reduce poverty (ICT4PR) in a rural Indonesian community. Differences between the theoretical approaches adopted by the implementing agencies and the difficulties inherent in achieving these aims in practice are outlined. The chapter is particularly concerned with how issues relating to implementation impact on efforts to move toward greater beneficiary inclusion in socioeconomic networks. Crucially, the chapter stresses the ongoing need in practice to move away from a homogenising digital-divide-style approach to ICT4PR, and to better engage with localized realities and contexts.
Formation of a Knowledge-Based Society through Utilization of Information Networking
Authors: Rahman Hakikur
Published: May 2011

“Information society,” “knowledge network” and “digital divide” are terms becoming increasingly common in many parts of the world over recent years. The key element in these concepts is that of “information,” and its fluidity in the modern world. Information can be viewed as the foundation stone of this new phenomenon and is the collation of raw and un-processed data into meaningful dialogue. Many societies and communities in developed and developing situation have settled on the term “information,” to describe the new economy and be the basis of development in the new millennium.
Transforming the K-12 Classroom with ICT
Authors: Baskin Colin
Published: May 2011

This chapter begins with four very public examples of how K-12 education providers across Australia are attempting to assimilate new teaching and learning technologies into existing teaching and learning structures. The transition as predicted is not altogether smooth, and questions are raised as to where and how the discourses of literacy, education, and technology converge in the information and communication technology classroom. The discussion presents a layered case study that brings together the practical discourse of the teacher, the new discourses of literacy, teaching and learning confronting our students, and the challenge these provide to the management discourse of school administrators. In doing so, it points conclusively to the fact that new configurations of learning are at work in our online classrooms.
E-Learning
Authors: Maherry-Lubbe Solitaire
Published: May 2011

Constructivist theories and modern pedagogical concepts emphasize that an activation of students is one of the most influential factors for learning effectiveness. The implementation of those educational concepts in e-learning, especially in distance learning contexts, is a rather difficult challenge. Systems that assist lectures in this intention are required. In this study, a student’s reaction towards e-learning is observed. The focus is on student’s demographics in order to analyze their reaction towards e-learning. Solving tasks and observing and critiquing this solution process, instead of merely assessing the end product of e-learning processes. A sample of 105 students from the University was drawn and the findings suggest that e-learning investment can help address a need for this type of support.
Group Process and Trust in Group Discussion
Authors: Uden Lorna , Wojnar Linda
Published: May 2011

Successful group discussion plays a crucial role in online learning. Teachers normally assume that students automatically transfer their learning of group process from group to group. Our experience found that for group discussion to be effective, it is important that we consider group process and the role of trust within groups. The paper begins with an introduction to group process and trust followed by a brief review of the benefits of group discussion for online learning. In section three, we describe the role that teachers play in initiating environments that promote trust and group empowerment. Through our experience of the implications of group process and trust, we will discuss how this environment fosters trusting relationships. We will also discuss the value of reviewing trust in the group process for each class before assigning group work. The paper concludes with the outcomes of our experience and suggestions for further work.
Mind the Gap!
Authors: Madden Andrew D. , Baptista Nunes J. Miguel , McPherson M.A. , Ford Nigel , Miller David
Published: May 2011

The rapid incursion of ICT into the classroom has meant that, within a space of a few years, computers have moved from being peripheral to being an integral part of the learning environment. However, our perceptions of a technology are affected by the age at which we encounter it. This chapter draws on the findings of a number of research projects at the University of Sheffield. These findings are used to explore some of the ’generation gaps’ that arise from differing perceptions of learning technologies. The data discussed provide insights into the ICT-based generation gaps that currently exist between and within groups of students, teachers and parents. It is argued that a fundamental gap may exist between students differing in age by as little as five years. Results from a related project exploring Networked Information and Communication Literacy Skills (NICLS), are used to introduce a discussion on the nature of any skills gap that must be addressed in the light of these generation gaps.
Competent Web Dialogue
Authors: Fåhræus Eva , Döös Marianne
Published: May 2011

Conducting a dialogue on the Web is a matter of linking thoughts in digital conversations. This article is intended to contribute toward learning qualities in such conversations. The term “dialogue” refers to a special kind of conversation, having structure, purpose, and learning qualities. The focus is on learning Web dialogues taking place in a course context using text-based, asynchronous meetings. An overview of factors that influence digital group conversations is presented together with a model for dialogue competence face-to-face. The dialogue potential of Web dialogues is highlighted. Course leaders and teachers wanting to create opportunities for learning Web dialogues, as well as the interlocutors themselves, need to wise up on the digital interchange of thoughts as a form.
A Capacity Building Approach to Health Literacy through ICTs
Authors: Simpson Lyn , Stockwell Melinda , Leggett Susan , Wod Leanne , Penn Danielle
Published: May 2011

There has been substantial interest in delivering ICT training options to rural and remote areas of Queensland, Australia, in order to bridge the rural-urban divide. But there is more than just education and training going on: Participants are being empowered to gain new skills and confidence, form new networks, become active in the community, and be proactive in addressing their own health and well-being needs.
Transforming Democracy through ICT
Authors: Williamson Andy
Published: May 2011

This article explores the potential of ICT to be used to transform the processes of citizen engagement such that a citizen-centred approach to e-democracy becomes both viable and desirable. It will do so by exploring three tensions relating to democracy and civil society: first that participation in traditional democracy is falling, yet new technologies are mobilising citizens on a global and local scale (such as antiglobalisation protests and electoral protests in the Philippines and Spain); second, ICT increases the technocracy of government but also offers citizens a chance to become closer to it; and third, that macro strategies for ICT access are not enough to remove localised exclusion.
Enacting and Interpreting Technology- From Usage to Well-Being
Authors: Gigler Bjöm-Sören
Published: May 2011

Under which conditions can information and communications technologies (ICTs) enhance the well-being of indigenous communities? This chapter investigates this question, focusing on the role of information and communications technology in promoting indigenous peoples’ development. First, the chapter analyzes key factors under which information and knowledge can be instrumental and substantive for the empowerment of marginalized groups. Hereby, it will be argued that improved informational capabilities, similar to the enhancement of a person’s writing and reading skills, can enhance poor people’s capabilities to make strategic life choices and to achieve the lifestyle they value. The chapter develops an alternative evaluation framework for ICT interventions based on Sen’s capability approach. This framework places, in contrast to the current discourse around the digital divide, the human development of the poor and not technology at the center of the analysis. The chapter concludes that a direct and causal relationship between ICTs and enhanced well-being does not exist, but that in fact this relationship is being shaped by a dynamic, multi-dimensional interrelationship between technology and the social context.
ICTs and Educational Benefits in Regional Development
Authors: Rennie James J.
Published: May 2011

ICTs can play an important role in improving public education in rural regions. The effects of ICT use in schools can, in turn, bring unexpected economic benefits to the region. ICT developers interested in building economies can use education as a sustainable, grassroots building block for future growth. While many development programs tend to focus on private models for ICT dissemination in remote regions (such as telecenters), public education embodies a spirit of universal accessibility that can bring global technologies into the daily lives of all world citizens. When ICTs are recognized as pedagogical tools, they serve both the long-term economic and cultural needs of communities.
Digital Divide
Authors: Burtseva Liudmila , Cojocaru Svetlana , Gaindric Constantin , Magariu Galina , Verlan Tatiana
Published: May 2011

In this chapter, we want to state shortly the basic components and manifestations of the digital-divide problem, as well as the ways of its solution in a specific country with its specific regional, social, historical, and political features. Moldova is taken as such a country. The problem is interesting to consider in the example of such a country because it is especially manifested in countries of such type: those that are waking up to development and are limited in means.
The Use of Information and Communication Technology for the Preservation of Aboriginal Culture
Authors: Michael Katina , Dunn Leone
Published: May 2011

Information and communication technology (ICT) has been applied successfully to numerous remote indigenous communities around the world. The greatest gains have been made when requirements are first defined by indigenous members of the community then pattern matched to an ICT solution.
Urban Information Systems in Turkish Local Governments
Authors: Velibeyoglu Koray
Published: May 2011

Since the end of 1980s, different sectors have implemented geographical information systems (GIS) in Turkey. A study on GIS market in Turkey indicates that municipalities are the primary customers (Gülersoy & Yigiter, 1999). One of the earliest GIS projects in Turkey began with the production of digital maps covering the boundaries of Istanbul Metropolitan Municipality in 1987. Since 1994, a rapid development process has occurred with the widespread diffusion of GIS especially in universities and large public sector organizations respectively. However, the early city-wide municipal GIS projects were initiated only after 1996 (Ucuzal, 1999).
E-Government Practices in Regional Context
Authors: Altunbas Derya , Tosun Elif
Published: May 2011

This chapter introduces the importance of the Information and Communication Technologies on the regional development in Turkey. Socioeconomic transformation can be done with the efficient service opportunities in regions that have different growth rates. Specially, some regions have migration problems for economic and employment reasons in Turkey. Growth poles are a typical development style for Turkey. Therefore, less developed regions should have more advantage from national economic programs. In this chapter, included in Regional development programs of Turkey in the context of Information and Communication Technologies. The objective of this chapter is to point out importance of improvements of Information and Communication Technologies and e-government programs in Turkey. At this time, it is defined the role of e-government programs on social, economic and political structures of the regions in Turkey.
Managing Socio-Technical Integration in Iterative Information System Development Projects
Authors: Bygstad Bendik
Published: May 2011

The challenges of information systems (IS) development have changed significantly in the past 15 years. From a situation where the main problem was to build stable systems based on a requirements specification, the IS project manager now faces challenges of integration; for example: how to integrate a new information system into large existing information infrastructures and unstable business processes? Building on a socio-technical perspective, four types of integration were identified and analyzed: external and internal stakeholder integration, and internal and external technical integration. A longitudinal case study of an e-business development project in the airline industry identified and highlighted some managerial challenges of integration. Findings include: Internal technical and (to some extent) stakeholder integration is well supported by traditional project management techniques and software engineering frameworks, such as the Rational Unified Process (RUP). However, the challenges of external stakeholder and technical integration is underrated in IS development research, and not well supported in RUP.
Integrating Real Option and Dynamic Capability Theories of Firm Boundaries
Authors: Warener Alfred G. , Fairbank James F.
Published: May 2011

Firms often acquire other firms to source technology but it is unclear why they might assume such risk by buying before a product standard is established in their industry. We draw upon real options and dynamic capability theories of firm organization to develop an integrated framework that explains why firms might acquire early and which firms are more likely to do so. We develop propositions regarding certain firm attributes as predictors of acquisition timing relative to passage of a technology standard. We argue that from a real options perspective, the primary reason firms acquire early is related to the firm’s knowledge of the technology. However, attributes such as political influence in the standardization process, prior experience making acquisitions, and how the firm resolves uncertainty about the technical expertise of potential acquisition targets are capabilities that also enter the acquisition timing decision. We provide a model based on those propositions and address how it can be empirically tested.
MNE Knowledge Management Across Borders and ICT
Authors: Brock Jürgen Kai-Uwe , Zhou Yu Josephine
Published: May 2011

Firms are consumers, producers, managers, and distributors of information (Egelhoff, 1991; Casson, 1996) and as such a repository of productive knowledge (Winter, 1988). Consequently the ability to generate, access, and utilize relevant knowledge is an essential organizational activity in order both to reduce uncertainty about the firm’s external environment and improve the efficiency of its internal operations.
Optimality-Theoretic Lexical Mapping Theory
Authors: Her One-Soon
Published: May 2011

Locative inversion verbs seem to share the same argument structure and grammatical function assignment (i.e., ) cross-linguistically. This article discusses the nature of argument-function linking in LFG and demonstrates how the Lexical Mapping Theory (LMT) rendered in Optimality-Theoretic (OT) terms, where argument-function linking is governed by universal violable constraints that consistently favor the unmarked function, accounts for locative inversion straightforwardly. Within this OT-LMT, locative inversion is due to a universal morphosyntactic constraint, and language variation in locative inversion is due to the difference in its relative ranking. This account also offers a potential explanation for the markedness of the locative inversion construction.
A De-Construction of Wireless Device Usage
Authors: Lind Mary R.
Published: May 2011

In this article, wireless technology use is addressed with a focus on the factors that underlie wireless interaction. A de-construction of the information processing theories of user/technol-ogy interaction is presented. While commercial and useful applications of wireless devices are numerous, wireless interaction is emerging as a means of social interaction—an extension of the user’s personal image—and as an object of amusement and play. The technology/user in-teraction theories that have driven the discussions of computer assisted communication media are information richness, communicative action, and social influence modeling. This article will extend this theoretical view of wireless devices by using flow theory to address elements of fun, control, and focus. Then, these technology/user interaction theories are used with respect to wireless devices to propose areas for future research.
Creative London? Investigating New Modalities of Work in the Cultural Industries
Authors: Lee David
Published: May 2011

This chapter considers the emergence of the discourse of creativity in contemporary economic, political, and social life, and the characteristics of emerging labour markets in the cultural industries. In particular it is concerned with analysing the working experiences of a number of individuals working in the cultural industries in London. Using a critical theoretical framework of understanding, it examines the importance of cultural capital, subjectivisation, governmentality, network sociality, and individualization as key concepts for understanding the experience of labour in the creative economy. This chapter considers how creative individuals negotiate the precarious, largely freelance, deregulated and de-unionised terrain of contemporary work. As the economic becomes increasingly inflected by the cultural in contemporary social life, the terrain of experience of individuals working in these expanding sectors has been neglected in cultural studies. This chapter seeks to critically intervene in this area, arguing that the “creative” turn in contemporary discourse can be seen to mask emergent inequalities and exploitative practices in the post-industrial employment landscape.
Conceptual Data Modeling Patterns
Authors: Batra Dinesh
Published: May 2011

The tremendous demand for software productivity has led to the idea of reuse of solutions that have worked successfully in the past. The notion of a design pattern is now well accepted in software design, and research in the area of data modeling has also begun. Although two books have explicitly attempted to cover this area, the representations provided in the books seem to be focused on specific applications and do not provide a generic and comprehensive set of templates. Another book attempts to address the problem but provides patterns at a level of granularity too small to be useful. This paper teases out underlying structures that tend to occur frequently in these books and provides patterns at an abstract and more useful level of granularity. It describes 11 data modeling patterns commonly found in business scenarios. The patterns are then validated by checking the frequency of occurrence of each pattern in the data representations included in three comprehensive texts of reference models. Two of these sources are targeted mainly at practitioners, and the third is academic oriented and targeted at students learning data modeling. Results indicate that although certain patterns are used more frequently than others, most of the 11 structures occur with adequate frequency to qualify as patterns. A comparison reveals that the frequency distribution of patterns is different among these sources. Further, the academic-oriented source distinctly focuses on different patterns as compared to the other two sources. The paper discusses the differences and provides specific recommendations on improving pedagogy in conceptual data modeling.
Process-Based Data Mining
Authors: Hirji Karim K.
Published: May 2011

In contrast to the Industrial Revolution, the Digital Revolution is happening much more quickly. For example, in 1946, the world’s first programmable computer, the Electronic Numerical Integrator and Computer (ENIAC), stood 10 feet tall, stretched 150 feet wide, cost millions of dollars, and could execute up to 5,000 operations per second. Twenty-five years later, Intel packed 12 times ENIAC’s processing power into a 12–square-millimeter chip. Today’s personal computers with Pentium processors perform in excess of 400 million instructions per second. Database systems, a subfield of computer science, has also met with notable accelerated advances. A major strength of database systems is their ability to store volumes of complex, hierarchical, heterogeneous, and time-variant data and to provide rapid access to information while correctly capturing and reflecting database updates.
Spatial Data Warehouse Modelling
Authors: Damiani Maria Luisa , Spaccapietra Stefano
Published: May 2011

This chapter is concerned with multidimensional data models for spatial data warehouses. Over the last few years different approaches have been proposed in the literature for modelling multidimensional data with geometric extent. Nevertheless, the definition of a comprehensive and formal data model is still a major research issue. The main contributions of the chapter are twofold: First, it draws a picture of the research area; second it introduces a novel spatial multidimensional data model for spatial objects with geometry (MuSD – multigranular spatial data warehouse). MuSD complies with current standards for spatial data modelling, augmented by data warehousing concepts such as spatial fact, spatial dimension and spatial measure. The novelty of the model is the representation of spatial measures at multiple levels of geometric granularity. Besides the representation concepts, the model includes a set of OLAP operators supporting the navigation across dimension and measure levels.
Designing Secure Data Warehouses
Authors: Villarroel Rodolfo , Fernandez-Medina Eduardo , Trujillo Juan , Piattini Mario
Published: May 2011

Organizations depend increasingly on information systems, which rely upon databases and data warehouses (DWs), which need increasingly more quality and security. Generally, we have to deal with sensitive information such as the diagnosis made on a patient or even personal beliefs or other sensitive data. Therefore, a final DW solution should consider the final users that can have access to certain specific information. Unfortunately, methodologies that incorporate security are based on an operational environment and not on an analytical one. Therefore, they do not include security into the multidimensional approaches to work with DWs. In this chapter, we present a comparison of six secure-systems design methodologies. Next, an extension of the UML that allows us to specify main security aspects in the multidimensional conceptual modeling is proposed, thereby allowing us to design secure DWs. Finally, we present how the conceptual model can be implemented with Oracle Label Security (OLS10g).
Data Warehouse Design to Support Customer Relationship Management Analysis
Authors: Cunningham Colleen , Song Il-Yeol , Chen Peter P.
Published: May 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.
An Information-Theoretic Framework for Process Structure and Data Mining
Authors: Greco Gianluigi , Guzzo Antonella , Pontieri Luigi
Published: May 2011

Mining process logs has been increasingly attracting the data mining community, due to the chances the development of process mining techniques can offer to the analysis and design of complex processes. Currently, these techniques focus on “structural” aspects by only considering which activities were executed and in which order, and disregard any other kind of data usually kept by real systems (e.g., activity executors, parameter values, and time-stamps). In this article, we aim at discovering different process variants by clustering process logs. To this purpose, an information-theoretic framework is used to simultaneously cluster the logged process traces, encoding structural information, as well as a number of performance metrics associated with them. Each cluster is equipped with a specific model, so providing the analyst with a compact and handy description of major execution scenarios for the process.
Metric Methods in Data Mining
Authors: Simovici Dan A.
Published: May 2011

This chapter presents data mining techniques that make use of metrics defined on the set of partitions of finite sets. Partitions are naturally associated with object attributes and major data mining problem such as classification, clustering, and data preparation benefit from an algebraic and geometric study of the metric space of partitions. The metrics we find most useful are derived from a generalization of the entropic metric. We discuss techniques that produce smaller classifiers, allow incremental clustering of categorical data and help user to better prepare training data for constructing classifiers. Finally, we discuss open problems and future research directions.
Ontology-Based Construction of Grid Data Mining Workflows
Authors: Brezany Peter , Janciak Ivan , Tjoa A. Min
Published: May 2011

This chapter introduces an ontology-based framework for automated construction of complex interactive data mining workflows as a means of improving productivity of Grid-enabled data exploration systems. The authors first characterize existing manual and automated workflow composition approaches and then present their solution called GridMiner Assistant (GMA), which addresses the whole life cycle of the knowledge discovery process. GMA is specified in the OWL language and is being developed around a novel data mining ontology, which is based on concepts of industry standards like the Predictive Model Markup Language, Cross Industry Standard Process for Data Mining and Java Data Mining API. The ontology introduces basic data mining concepts like data mining elements, tasks, services, etc. In addition, conceptual and implementation architectures of the framework are presented and its application to an example taken from the medical domain is illustrated. The authors hope that the further research and development of this framework can lead to productivity improvements, which can have significant impact on many real-life spheres. For example, it can be a crucial factor in achievement of scientific discoveries, optimal treatment of patients, productive decision making, cutting costs, etc.
An Ontology-Based Data Mediation Framework for Semantic Environments
Authors: Mocan Adrian , Cimpian Emilia
Published: May 2011

n a semantic environment data is described by ontologies and ontology mapping has become a crucial aspect in solving the heterogeneity problems of semantically described data. This means that alignments between ontologies have to be created, most probably during design-time, and used in various run-time processes. Such alignments describe a set of mappings between the source and target ontologies, where the mappings show how instance data from one ontology can be expressed in terms of another ontology. In this article we propose a formal model for creation of mappings and we explore how such a model maps onto a design-time graphical tool that can be used in creating alignments between ontologies. In the other direction, we investigate how such a model helps in expressing the mappings in a logical language, based on the semantic relationships identified using the graphical tool.
Combinatorial Fusion Analysis
Authors: Hsu D. Frank , Chung Yun-Sheng , Kristal Bruce S.
Published: May 2011

Combination methods have been investigated as a possible means to improve performance in multi-variable (multi-criterion or multi-objective) classification, prediction, learning, and optimization problems. In addition, information collected from multi-sensor or multi-source environment also often needs to be combined to produce more accurate information, to derive better estimation, or to make more knowledgeable decisions. In this chapter, we present a method, called Combinatorial Fusion Analysis (CFA), for analyzing combination and fusion of multiple scoring. CFA characterizes each Scoring system as having included a Score function, a Rank function, and a Rank/score function. Both rank combination and score combination are explored as to their combinatorial complexity and computational efficiency. Information derived from the scoring characteristics of each scoring system is used to perform system selection and to decide method combination. In particular, the rank/score graph defined by Hsu, Shapiro and Taksa (Hsu et al., 2002; Hsu & Taksa, 2005) is used to measure the diversity between scoring systems. We illustrate various applications of the framework using examples in information retrieval and biomedical informatics.
Algorithms for Data Mining
Authors: Takaoka Tadao , Pope Nigel K.L. , Voges Kevin E.
Published: May 2011

In this chapter, we present an overview of some common data mining algorithms. Two techniques are considered in detail. The first is association rules, a fundamental approach that is one of the oldest and most widely used techniques in data mining. It is used, for example, in supermarket basket analysis to identify relationships between purchased items. The second is the maximum sub-array problem, which is an emerging area that is yet to produce a textbook description. This area is becoming important as a new tool for data mining, particularly in the analysis of image data. For both of these techniques, algorithms are presented in pseudo-code to demonstrate the logic of the approaches. We also briefly consider decision and regression trees and clustering techniques.
Super Computer Heterogeneous Classifier Meta-Ensembles
Authors: Bagnall Anthony , Cawley Gavin , Whittley Ian , Bull Larry , Studley Matthew , Pettipher Mike , Tekiner Firat
Published: May 2011

This article describes the entry of the Super Computer Data Mining (SCDM) Project to the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2006 Data Mining Competition. The SCDM project is developing data mining tools for parallel execution on Linux clusters. The code is freely available; please contact the first author for a copy. We combine several classifiers, some of them ensemble techniques, into a heterogeneous meta-ensemble, to produce a probability estimate for each test case. We then use a simple decision theoretic framework to form a classification. The meta-ensemble contains a Bayesian neural network, a learning classifier system (LCS), attribute selection based-ensemble algorithms (Filtered At-tribute Subspace based Bagging with Injected Randomness [FASBIR]), and more well-known classifiers such as logistic regression, Naive Bayes (NB), and C4.5.
Navigation Rules for Exploring Large Multidimensional Data Cubes
Authors: Kumar Navin , Gangopadhyay Aryya , Karabatis George , Bapna Sanjay , Chen Zhiyuan
Published: May 2011

Navigating through multidimensional data cubes is a nontrivial task. Although On-Line Analytical Processing (OLAP) provides the capability to view multidimensional data through rollup, drill-down, and slicing-dicing, it offers minimal guidance to end users in the actual knowledge discovery process. In this article, we address this knowledge discovery problem by identifying novel and useful patterns concealed in multidimensional data that are used for effective exploration of data cubes. We present an algorithm for the DIscovery of Sk-NAvigation Rules (DISNAR), which discovers the hidden interesting patterns in the form of Sk-navigation rules using a test of skewness on the pairs of the current and its candidate drill-down lattice nodes. The rules then are used to enhance navigational capabilities, as illustrated by our rule-driven system. Extensive experimental analysis shows that the DISNAR algorithm discovers the interesting patterns with a high recall and precision with small execution time and low space overhead.
Data Mining Using Qualitative Information on the Web
Authors: Hong Taeho , Suh Woojong
Published: May 2011

Data mining has drawn much attention in generating the useful information from Web data. Data mining techniques have typically considered quantitative information rather than qualitative, though the qualitative information can often be used to improve the quality of a result. This chapter provides a hybrid data mining application, KBNMiner (Knowledge-Based News Miner), to predict interest rates on the basis of qualitative information on the Web as well as quantitative information stored in a database. The KBNMiner is developed through the integration of cognitive maps and neural networks. To validate the effectiveness of the KBNMiner, an experiment with Web news information is conducted and its results are discussed.
VRMiner
Authors: Azzag H. , Picarougne F. , Guinot C. , Venturini G.
Published: May 2011

We present in this chapter a new 3D interactive method for visualizing multimedia data with virtual reality named VRMiner. We consider that an expert in a specific domain has collected a set of examples described with numeric and symbolic attributes but also with sounds, images, videos and Web sites or 3D models, and that this expert wishes to explore these data to understand their structure. We use a 3D stereoscopic display in order to let the expert easily visualize and observe the data. We add to this display contextual information such as texts and small images, voice synthesis and sound. Larger images, videos and Web sites are displayed on a second computer in order to ensure real time display. Navigating through the data is done in a very intuitive and precise way with a 3D sensor that simulates a virtual camera. Interactive requests can be formulated by the expert with a data glove that recognizes the hand gestures. We show how this tool has been successfully applied to several real world applications.
Data Mining in Diabetes Diagnosis and Detection
Authors: Bose Indranil
Published: May 2011

Diabetes is a disease worrying hundreds of millions of people around the world. In the USA, the population of diabetic patients is about 15.7 million (Breault et al., 2002). It is reported that the direct and indirect cost of diabetes in the USA is $132 billion (Diabetes Facts, 2004). Since there is no method that is able to eradicate diabetes, doctors are striving for ways to fight this doom. Researchers are trying to link the cause of diabetes with patients’ lifestyles, inheritance information, age, and so forth in order to get to the root of the problem. Due to the prevalence of a large number of responsible factors and the availability of historical data, data mining tools have been used to generate inference rules on the cause and effect of diabetes as well as to help in knowledge discovery in this area. The goal of this chapter is to explain the different steps involved in mining diabetes data and to show, using case studies, how data mining has been carried out for detection and diagnosis of diabetes in Hong Kong, USA, Poland, and Singapore.
Acquiring Semantic Sibling Associations from Web Documents
Authors: Brunzel Marko , Spiliopoulou Myra
Published: May 2011

The automated discovery of relationships among terms contributes to the automation of the ontology engineering process and allows for sophisticated query expansion in information retrieval. While there are many findings on the identification of direct hierarchical relations among concepts, less attention has been paid on the discovery sibling terms. These are terms that share a common, a priori unknown parent such as co-hyponyms and co-meronyms. In this study, we present our results on the discovery of pairs or groups of sibling terms with XTREEM-SA (Xhtml TREE mining for sibling associations), an algorithm that extracts semantics from Web documents. While conventional methods process an appropriately prepared corpus, XTREEM-SA takes as input an arbitrary collection of Web documents on a given topic and finds sibling relations between terms in this corpus. It is thus independent of domain and language, does not require linguistic preprocessing, and does not rely on syntactic or other rules on text formation. We describe XTREEM-SA and evaluate it toward two reference ontologies. In this context, we also elaborate on the challenges of evaluating semantics extracted from the Web against handcrafted ontologies of high quality but possibly low coverage.
Traversal Pattern Mining in Web Usage Data
Authors: Yao Jenq-Foung , Xiao Yongqiao
Published: May 2011

Web usage mining is to discover useful patterns in the web usage data, and the patterns provide useful information about the user’s browsing behavior. This chapter examines different types of web usage traversal patterns and the related techniques used to uncover them, including Association Rules, Sequential Patterns, Frequent Episodes, Maximal Frequent Forward Sequences, and Maximal Frequent Sequences. As a necessary step for pattern discovery, the preprocessing of the web logs is described. Some important issues, such as privacy, sessionization, are raised, and the possible solutions are also discussed.
Facilitating and Improving the Use of Web Services with Data Mining
Authors: Nayak Richi
Published: May 2011

Web services have recently received much attention in businesses. However, a number of challenges such as lack of experience in estimating the costs, lack of service innovation and monitoring, and lack of methods for locating appropriate services are to be resolved. One possible approach is by learning from the experiences in Web services and from other similar situations. Such a task requires the use of data mining to represent generalizations on common situations. This chapter examines how some of the issues of Web services can be addressed through data mining.
E-Mail Worm Detection Using Data Mining
Authors: Masud Mohammad M. , Khan Latifur , Thuraisingham Bhavani
Published: May 2011

This work applies data mining techniques to detect e-mail worms. E-mail messages contain a number of different features such as the total number of words in message body/subject, presence/absence of binary attachments, type of attachments, and so on. The goal is to obtain an efficient classification model based on these features. The solution consists of several steps. First, the number of features is reduced using two different approaches: feature-selection and dimension-reduction. This step is necessary to reduce noise and redundancy from the data. The feature-selection technique is called Two-phase Selection (TPS), which is a novel combination of decision tree and greedy selection algorithm. The dimension-reduction is performed by Principal Component Analysis. Second, the reduced data is used to train a classifier. Different classification techniques have been used, such as Support Vector Machine (SVM), Naïve Bayes, and their combination. Finally, the trained classifiers are tested on a dataset containing both known and unknown types of worms. These results have been compared with published results. It is found that the proposed TPS selection along with SVM classification achieves the best accuracy in detecting both known and unknown types of worms.
Fuzzy Miner
Authors: Pelekis Nikos , Theodoulikis Babis , Kopanakis Ioannis , Theodoridis Yannis
Published: May 2011

We study the problem of classification as this is presented in the context of data mining. Among the various approaches that are investigated, we focus on the use of Fuzzy Logic for pattern classification, due to its close relation to human thinking. More specifically, this paper presents a heuristic fuzzy method for the classification of numerical data, followed by the design and the implementation of its corresponding tool (Fuzzy Miner). The initial idea comes from the fact that fuzzy systems are universal approximators of any real continuous function. Such an approximation method coming from the domain of fuzzy control is appropriately adjusted into pattern classification and an “adaptive” procedure is proposed for deriving highly accurate linguistic if-then rules. Extensive simulation tests are performed to demonstrate the performance of Fuzzy Miner, while a comparison with a neuro-fuzzy classifier of the area is taking place in order to contradict the methodologies and the corresponding outcomes. Finally, new research directions in the context of Fuzzy Miner are identified, and ideas for its improvement are formulated.
Development of Control Signatures with a Hybrid Data Mining and Genetic Algorithm
Authors: Burns Alex , Shah Shital , Kusiak Andrew
Published: May 2011

This paper presents a hybrid approach that integrates a genetic algorithm (GA) and data mining to produce control signatures. The control signatures define the best parameter intervals leading to a desired outcome. This hybrid method integrates multiple rule sets generated by a data mining algorithm with the fitness function of a GA. The solutions of the GA represent intersections among rules providing tight parameter bounds. The integration of intuitive rules provides an explanation for each generated control setting and it provides insights into the decision making process. The ability to analyze parameter trends and the feasible solutions generated by the GA with respect to the outcomes is another benefit of the proposed hybrid method. The presented approach for deriving control signatures is applicable to various domains, such as energy, medical protocols, manufacturing, airline operations, customer service, and so on. Control signatures were developed and tested for control of a power plant boiler. These signatures discovered insightful relationships among parameters. The results and benefits of the proposed method for the power plant boiler are discussed in the paper.
Data Warehousing Search Engine
Authors: Peter Hadrian , Greenidge Charles
Published: May 2011

Modern database systems have incorporated the use of DSS (Decision Support Systems) to augment their decision-making business function and to allow detailed analysis of off-line data by higher-level business managers (Agosta, 2000; Kimball, 1996).
Humanitites Data Warehousing
Authors: Delve Janet
Published: May 2011

Data Warehousing is now a well-established part of the business and scientific worlds. However, up until recently, data warehouses were restricted to modeling essentially numerical data – examples being sales figures in the business arena (e.g. Wal-Mart’s data warehouse) and astronomical data (e.g. SKICAT) in scientific research, with textual data providing a descriptive rather than a central role. The lack of ability of data warehouses to cope with mainly non-numeric data is particularly problematic for humanities1 research utilizing material such as memoirs and trade directories. Recent innovations have opened up possibilities for non-numeric data warehouses, making them widely accessible to humanities research for the first time. Due to its irregular and complex nature, humanities research data is often difficult to model and manipulating time shifts in a relational database is problematic as is fitting such data into a normalized data model. History and linguistics are exemplars of areas where relational databases are cumbersome and which would benefit from the greater freedom afforded by data warehouse dimensional modeling.
Data Mining In the Federal Government
Authors: Pang Les
Published: May 2011

Data mining has been a successful approach for improving the level of business intelligence and knowledge management throughout an organization. This article identifies lessons learned from data mining projects within the federal government including military services. These lessons learned were derived from the following project experiences: • Defense Medical Logistics Support System Data Warehouse Program • Department of Defense (DoD) Defense Financial and Accounting Service (DFAS) “Operation Mongoose” • DoD Computerized Executive Information System (CEIS) • Department of Transportation (DOT) Executive Reporting Framework System • Federal Aviation Administration (FAA) Aircraft Accident Data Mining Project • General Accounting Office (GAO) Data Mining of DoD Purchase and Travel Card Programs • U.S. Coast Guard Executive Information System • Veteran Administrations (VA) Demographics System
Classification Of 3G Mobile Phone Customers
Authors: Jain Ankur , Wangikar Lalit , Ahrens Martin , Rao Ranjan , Kundu Suddha Sattwa , Ghosh Sutirtha
Published: May 2011

In this article we discuss how we have predicted the third generation (3G) customers using lo-gistic regression analysis and statistical tools like Classification and Regression Tree (CART), Multivariate Adaptive Regression Splines (MARS), and other variables derived from the raw variables. The basic idea reflected in this paper is that the performance of logistic regression using raw variables standalone can be improved upon, by the use for various functions of the raw variables and dummies representing potential segments of the population.