bluuebunny/crossref_metadata_2025 huggingface dataset:
Who's Talking Online? A Descriptive Analysis of Gender & Online Communication
Authors: Hartsell Taralynn
Published: May 2011

This preliminary descriptive study investigated the association between gender and online communication and involved participants from an online graduate course. The study implemented a descriptive model in that “student involvement” was assessed by tabulating and recording the quantity and quality of student activity in the discussion threads. Quantity was recorded by the amount of times students posted online comments and the number of words that women and men used to make their responses. In addition, quality was examined by reviewing the content that women and men made concerning topics under discussion. In the end, a difference between the genders was found in that the amount (quantity) women contributed to the discussions exceeded that contributed by the men. Women were also more inclined to give supportive or encouraging remarks than men, and addressed their classmates by name to promote a sense of online community, all which support previous studies.
New ICTs for Conflict Prevention and Management
Authors: Medina Ángela-Jo
Published: May 2011

This chapter introduces the impact of new information and communication technologies (nICTs), specifically the Internet, on national and international conflict prevention and management. This analysis provides case studies of the use and examples of the prospective use of nICTs to counteract conflict as it undermines social and economic structures and hinders regional development. This study reviews the specific application of nICT-related initiatives at the different phases of the conflict cycle: from addressing the root causes of conflict as a tool for prevention and management, through the reconciliation and reconstruction phase. The author intends this analysis to illustrate and contribute to the discussion of how the social and development-related application of nICTs can compliment existing conflict prevention and management reduction strategies.
Multi-Label Classification
Authors: Tsoumakas Grigorios , Katakis Ioannis
Published: May 2011

Multi-label classification methods are increasingly required by modern applications, such as protein function classification, music categorization, and semantic scene classification. This article introduces the task of multi-label classification, organizes the sparse related literature into a structured presentation and performs comparative experimental results of certain multilabel classification methods. It also contributes the definition of concepts for the quantification of the multi-label nature of a data set.
Pattern Comparison in Data Mining
Authors: Ntoutsi Irene , Pelekis Nikos , Theodoridis Yannis
Published: May 2011

Many patterns are available nowadays due to the widespread use of knowledge discovery in databases (KDD), as a result of the overwhelming amount of data. This “flood” of patterns imposes new challenges regarding their management. Pattern comparison, which aims at evaluating how close to each other two patterns are, is one of these challenges resulting in a variety of applications. In this chapter we investigate issues regarding the pattern comparison problem and present an overview of the work performed so far in this domain. Due to heterogeneity of data mining patterns, we focus on the most popular pattern types, namely frequent itemsets and association rules, clusters and clusterings, and decision trees.
Integration of Data Sources through Data Mining
Authors: Koeller Andreas
Published: May 2011

Integration of data sources refers to the task of developing a common schema as well as data transformation solutions for a number of data sources with related content. The large number and size of modern data sources make manual approaches at integration increasingly impractical. Data mining can help to partially or fully automate the data integration process.
Applying UML for Modeling the Physical Design of Data Warehouses
Authors: Luján-Mora Serg , Trujillo Juan
Published: May 2011

In previous work, we have shown how to use unified modeling language (UML) as the primary representation mechanism to model conceptual design, logical design, modeling of extraction, transformation, loading (ETL) processes, and defining online analytical processing (OLAP) requirements of data warehouses (DW). Continuing our work on using UML throughout the DW development lifecycle, in this chapter, we present our modeling techniques of physical design of DW using component diagrams and deployment diagrams of UML. Our approach allows the DW designer to anticipate important physical design decisions that may reduce the overall development time of a DW such as replicating dimension tables, vertical and horizontal partitioning of a fact table, and the use of particular servers for certain ETL processes. We illustrate our techniques with a case study.
A Java Technology Based Distributed Software Architecture for Web Usage Mining
Authors: Hernansaez Juan M. , Botia Juan A. , Skarmeta Antonio F.G.
Published: May 2011

In this chapter we focus on the three approaches that seem to be the most successful ones in the Web usage mining area: clustering, association rules and sequential patterns. We will discuss some techniques from each one of these approaches, and then we will show the benefits of using METALA (a META-Learning Architecture) as an integrating tool not only for the discussed Web usage mining techniques, but also for inductive learning algorithms. As we will show, this architecture can also be used to generate new theories and models that can be useful to provide new generic applications for several supervised and non-supervised learning paradigms. As a particular example of a Web usage mining application, we will report our work for a medium-sized commercial company, and we will discuss some interesting properties and conclusions that we have obtained from our reporting.
Mining Geo-Referenced Databases
Authors: Santos Maribel Yasmina , Amaral Luís Alfredo
Published: May 2011

Knowledge discovery in databases is a process that aims at the discovery of associations within data sets. The analysis of geo-referenced data demands a particular approach in this process. This chapter presents a new approach to the process of knowledge discovery, in which qualitative geographic identifiers give the positional aspects of geographic data. Those identifiers are manipulated using qualitative reasoning principles, which allows for the inference of new spatial relations required for the data mining step of the knowledge discovery process. The efficacy and usefulness of the implemented system — Padrão — has been tested with a bank dataset. The results support that traditional knowledge discovery systems, developed for relational databases and not having semantic knowledge linked to spatial data, can be used in the process of knowledge discovery in geo-referenced databases, since some of this semantic knowledge and the principles of qualitative spatial reasoning are available as spatial domain knowledge.
Two Rough Set Approaches to Mining Hop Extraction Data
Authors: Grzymala-Busse Jerzy W. , Hippe Zdzislaw S. , Mroczek Teresa , Roj Edward , Skowronski Boleslaw
Published: May 2011

Results of our research on using two approaches, both based on rough sets, to mining three data sets describing bed caking during the hop extraction process are presented. For data mining we used two methods: direct rule induction by the MLEM2 algorithm and generation of belief networks associated with conversion belief networks into rule sets by the BeliefSEEKER system. Statistics for rule sets are presented, including an error rate. Finally, six rule sets were ranked by an expert. Our results show that both our approaches to data mining are of approximately the same quality.
Periodic Streaming Data Reduction Using Flexible Adjustment of Time Section Size
Authors: Kim Jaehoon , Park Seong
Published: May 2011

Much of the research regarding streaming data has focused only on real time querying and analysis of recent data stream allowable in memory. However, as data stream mining, or tracking of past data streams, is often required, it becomes necessary to store large volumes of streaming data in stable storage. Moreover, as stable storage has restricted capacity, past data stream must be summarized. The summarization must be performed periodically because streaming data flows continuously, quickly, and endlessly. Therefore, in this paper, we propose an efficient periodic summarization method with a flexible storage allocation. It improves the overall estimation error by flexibly adjusting the size of the summarized data of each local time section. Additionally, as the processing overhead of compression and the disk I/O cost of decompression can be an important factor for quick summarization, we also consider setting the proper size of data stream to be summarized at a time. Some experimental results with artificial data sets as well as real life data show that our flexible approach is more efficient than the existing fixed approach.
Exploiting Captions for Web Data Mining
Authors: Rowe Neil C.
Published: May 2011

We survey research on using captions in data mining from the Web. Captions are text that describes some other information (typically, multimedia). Since text is considerably easier to analyze than non-text, a good way to support access to non-text is to index the words of its captions. However, captions vary considerably in form and content on the Web. We discuss the range of syntactic clues (such as HTML tags) and semantic clues (such as particular words). We discuss how to quantify clue strength and combine clues for a consensus. We then discuss the problem of mapping information in captions to information in media objects. While it is hard, classes of mapping schemes are distinguishable, and a segmentation of the media can be matched to a parse of the caption.
Indexing in Data Warhousing
Authors: Davis Karen C. , Gupta Ashima
Published: May 2011

Bitmap Indexes (BIs) allow fast access to individual attribute values that are needed to answer a query by storing a bit for each distinct value and tuple. A BI is defined for a single attribute and the encodings are based solely on data values; the Property Map (PMap) is a multidimensional indexing technique that precomputes attribute expressions for each tuple and stores the results as bit strings. In order to determine whether the PMap is competitive with BIs, we conduct a performance study of the PMap with the Range Encoded Bit Sliced Index (REBSI) using cost models to simulate storage and query processing costs for different kinds of query types. We identify parameters that have significant effect on index performance and determine situations in which either index is more suitable. These results could be useful for improving the performance of an analytical decision making system.
Interactive Visual Data Mining
Authors: Wang Shouhong , Wang Hai
Published: May 2011

In the data mining field, people have no doubt that high level information (or knowledge) can be extracted from the database through the use of algorithms. However, a one-shot knowledge deduction is based on the assumption that the model developer knows the structure of knowledge to be deducted. This assumption may not be invalid in general. Hence, a general proposition for data mining is that, without human-computer interaction, any knowledge discovery algorithm (or program) will fail to meet the needs from a data miner who has a novel goal (Wang, S. & Wang, H., 2002). Recently, interactive visual data mining techniques have opened new avenues in the data mining field (Chen, Zhu, & Chen, 2001; de Oliveira & Levkowitz, 2003; Han, Hu & Cercone, 2003; Shneiderman, 2002; Yang, 2003).
Deterministic Motif Mining in Protein Databases
Authors: Ferreira Pedro Gabriel , Azevedo Paulo Jorge
Published: May 2011

Protein sequence motifs describe, through means of enhanced regular expression syntax, regions of amino-acids that have been conserved across several functionally related proteins. These regions may have an implication at the structural and functional level of the proteins. Sequence motif analysis can bring significant improvements towards a better understanding of the protein sequence-structure-function relation. In this chapter we review the subject of mining deterministic motifs from protein sequence databases. We start by giving a formal definition of the different types of motifs and the respective specificities. Then, we explore the methods available to evaluate the quality and interest of such patterns. Examples of applications and motif repositories are described. We discuss the algorithmic aspects and different methodologies for motif extraction. A briefly description on how sequence motifs can be used to extract structural level information patterns is also provided.
Differential Association Rules
Authors: Besemann Christopher , Denton Anne , Yekkirala Ajay , Hutchison Ron , Anderson Marc
Published: May 2011

In this chapter, we discuss the use of differential association rules to study the annotations of proteins in one or more interaction networks. Using this technique, we find the differences in the annotations of interacting proteins in a network. We extend the concept to compare annotations of interacting proteins across different definitions of interaction networks. Both cases reveal instances of rules that explain known and unknown characteristics of the network(s). By taking advantage of such data mining techniques, a large number of interesting patterns can be effectively explored that otherwise would not be.
A Study on Web Searching
Authors: Chu Shanfeng , Deng Xiaotie , Fang Qizhi , Zhang Weimin
Published: May 2011

Web search engines are one of the most popular services to help users find useful information on the Web. Although many studies have been carried out to estimate the size and overlap of the general web search engines, it may not benefit the ordinary web searching users, since they care more about the overlap of the top N (N=10, 20 or 50) search results on concrete queries, but not the overlap of the total index database. In this study, we present experimental results on the comparison of the overlap of the top N (N=10, 20 or 50) search results from AlltheWeb, Google, AltaVista and WiseNut for the 58 most popular queries, as well as for the distance of the overlapped results. These 58 queries are chosen from WordTracker service, which records the most popular queries submitted to some famous metasearch engines, such as MetaCrawler and Dogpile. We divide these 58 queries into three categories for further investigation. Through in-depth study, we observe a number of interesting results: the overlap of the top N results retrieved by different search engines is very small; the search results of the queries in different categories behave in dramatically different ways; Google, on average, has the highest overlap among these four search engines; each search engine tends to adopt a different rank algorithm independently.
A Data Mining Driven Approach for Web Classification and Filtering Based on Multimodal Content Analysis
Authors: Hammami Mohamed , Chahir Youssef , Chen Liming
Published: May 2011

Along with the ever growing Web is the proliferation of objectionable content, such as sex, violence, racism, and so forth. We need efficient tools for classifying and filtering undesirable Web content. In this chapter, we investigate this problem through WebGuard, our automatic machine-learning-based pornographic Web site classification and filtering system. Facing the Internet more and more visual and multimedia as exemplified by pornographic Web sites, we focus here our attention on the use of skin color-related visual content-based analysis along with textual and structural content based analysis for improving pornographic Web site filtering. While the most commercial filtering products on the marketplace are mainly based on textual content-based analysis such as indicative keywords detection or manually collected black list checking, the originality of our work resides on the addition of structural and visual content-based analysis to the classical textual content-based analysis along with several major-data mining techniques for learning and classifying. Experimented on a test bed of 400 Web sites including 200 adult sites and 200 nonpornographic ones, WebGuard, our Web filtering engine scored a 96.1% classification accuracy rate when only textual and structural content based analysis are used, and 97.4% classification accuracy rate when skin color-related visual content-based analysis is driven in addition. Further experiments on a black list of 12,311 adult Web sites manually collected and classified by the French Ministry of Education showed that WebGuard scored 87.82% classification accuracy rate when using only textual and structural content-based analysis, and 95.62% classification accuracy rate when the visual content-based analysis is driven in addition. The basic framework of WebGuard can apply to other categorization problems of Web sites which combine, as most of them do today, textual and visual content.
Advanced Data Mining and Visualization Techniques with Probabilistic Principal Surfaces
Authors: Staiano Antonino , De Vinco Lara , Longo Giuseppe , Tagliaferri Roberto
Published: May 2011

Probabilistic Principal Surfaces (PPS) is a non linear latent variable model with very powerful visualization and classification capabilities which seem to be able to overcome most of the shortcomings of other neural tools. PPS builds a probability density function of a given set of patterns lying in a high-dimensional space which can be expressed in terms of a fixed number of latent variables lying in a latent Q-dimensional space. Usually, the Q-space is either two or three dimensional and thus the density function can be used to visualize the data within it. The case in which Q = 3 allows to project the patterns on a spherical manifold which turns out to be optimal when dealing with sparse data. PPS may also be arranged in ensembles to tackle complex classification tasks. As template cases we discuss the application of PPS to two real- world data sets from astronomy and genetics.
Statistical Sampling to Instantiate Materialized View Selection Problems in Data Warehouses
Authors: Ahmed Mesbah U. , Agrawal Vikas , Nandkeolyar Udayan , Sundararaghavan P. S.
Published: May 2011

In any online decision support system, the backbone is a data warehouse. In order to facilitate rapid response to complex business decision support queries, it is a common practice to materialize an appropriate set of the views at the data warehouse. However, it typically requires the solution of the Materialized View Selection (MVS) problem to select the right set of views to materialize in order to achieve a certain level of service given a limited amount of resource such as materialization time, storage space, or view maintenance time. Dynamic changes in the source data and the end users requirement necessitate rapid and repetitive instantiation and solution of the MVS problem. In an online decision support context, time is of the essence in finding acceptable solutions to this problem. In this chapter, we have used a novel approach to instantiate and solve four versions of the MVS problem using three sampling techniques and two databases. We compared these solutions with the optimal solutions corresponding to the actual problems. In our experimentation, we found that the sampling approach resulted in substantial savings in time while producing good solutions.
Data Mining for Supply Chain Management in Complex Networks
Authors: Raisinghani Mahesh S. , Singh Manoj K.
Published: May 2011

Supply chain comprises the flow of products, information, and money. In traditional supply chain management, business processes are disconnected from stock control and, as a result, inventory is the direct output of incomplete information. The focus of contemporary supply chain management is to organize, plan, and implement these flows. First, at the organizational level, products are manufactured, transported, and stored based on the customers’ needs. Second, planning and control of component production, storage, and transport are managed using central supply management and replenished through centralized procurement. Third, the implementation of the supply chain involves the entire cycle from the order-entry process to order fulfillment and delivery. Data mining can create a better match between supply and demand, reducing or sometimes even eliminating the stocks.
An Approach to Mining Crime Patterns
Authors: Bagui Sikha
Published: May 2011

This paper presents a knowledge discovery effort to retrieve meaningful information about crime from a U.S. state database. The raw data were preprocessed, and data cubes were created using Structured Query Language (SQL). The data cubes then were used in deriving quantitative generalizations and for further analysis of the data. An entropy-based attribute relevance study was undertaken to determine the relevant attributes. A machine learning software called WEKA was used for mining association rules, developing a decision tree, and clustering. SOM was used to view multidimensional clusters on a regular two-dimensional grid.
Expanding Data Mining Power with System Dynamics
Authors: Casado Edilberto
Published: May 2011

Business intelligence (BI) is a key topic in business today, since it is focused on strategic decision making and on the search of value from business activities through empowering a “forward-thinking” view of the world. From this perspective, one of the most valuable concepts within BI is the “knowledge discovery in databases” or “data mining,” defined as “the process of discovering meaningful new correlations, patterns, and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques” (SPSS, 1997).
Privacy in Data Mining Textbooks
Authors: Lawler James , Molluzzo John C.
Published: May 2011

Many companies, such as Wal-Mart, store much of their business and customer data in large databases called data warehouses. Their customers are not told the extent of the information accumulated on them, how long it will be kept, nor the uses to which it will be put (Hays, 2004). This data is subsequently analyzed to produce new information to help the companies evaluate business processes and customer behavior. Data mining is usually used to do the analysis. Much of the mined data is public or semi-public what we purchase at the supermarket, where we surf the Web, where we work, our salary.
Effective Intelligent Data Mining Using Dempster-Shafer Theory
Authors: Beynon Malcolm J.
Published: May 2011

The efficacy of data mining lies in its ability to identify relationships amongst data. This chapter investigates that constraining this efficacy is the quality of the data analysed, including whether the data is imprecise or in the worst case incomplete. Through the description of Dempster-Shafer theory (DST), a general methodology based on uncertain reasoning, it argues that traditional data mining techniques are not structured to handle such imperfect data, instead requiring the external management of missing values, and so forth. One DST based technique is classification and ranking belief simplex (CaRBS), which allows intelligent data mining through the acceptance of missing values in the data analysed, considering them a factor of ignorance, and not requiring their external management. Results presented here, using CaRBS and a number of simplex plots, show the effect of managing and not managing of imperfect data.
A Successive Decision Tree Approach to Mining Remotely Sensed Image Data
Authors: Zhang Jianting , Liu Wieguo , Gruenwald Le
Published: May 2011

Decision trees (DT) has been widely used for training and classification of remotely sensed image data due to its capability to generate human interpretable decision rules and its relatively fast speed in training and classification. This chapter proposes a successive decision tree (SDT) approach where the samples in the ill-classified branches of a previous resulting decision tree are used to construct a successive decision tree. The decision trees are chained together through pointers and used for classification. SDT aims at constructing more interpretable decision trees while attempting to improve classification accuracies. The proposed approach is applied to two real remotely sensed image datasets for evaluations in terms of classification accuracy and interpretability of the resulting decision rules.
Re-Sampling Based Data Mining Using Rough Set Theory
Authors: Griffiths Benjamin , Beynon Malcolm J.
Published: May 2011

Predictive accuracy, as an estimation of a classifier’s future performance, has been studied for at least seventy years. With the advent of the modern computer era, techniques that may have been previously impractical are now calculable within a reasonable time frame. Within this chapter, three techniques of resampling, namely, leave-one-out, k-fold cross validation and bootstrapping; are investigated as methods of error rate estimation with application to variable precision rough set theory (VPRS). A prototype expert system is utilised to explore the nature of each resampling technique when VPRS is applied to an example dataset. The software produces a series of graphs and descriptive statistics, which are used to illustrate the characteristics of each technique with regards to VPRS, and comparisons are drawn between the results.
Improved Data Partitioning for Building Large ROLAP Data Cubes in Parallel
Authors: Chen Ying , Dehne Frank , Eavis Todd , Rau-Chaplin A.
Published: May 2011

This paper presents an improved parallel method for generating ROLAP data cubes on a shared-nothing multiprocessor based on a novel optimized data partitioning technique. Since no shared disk is required, our method can be used for highly scalable processor clusters consisting of standard PCs with local disks only, connected via a data switch. Experiments show that our improved parallel method provides optimal, linear, speedup for at least 32 processors. The approach taken, which uses a ROLAP representation of the data cube, is well suited for large data warehouses and high dimensional data, and supports the generation of both fully materialized and partially materialized data cubes.
An Immune Systems Approach for Classifying Mobile Phone Usage
Authors: Limanto Hanny Yulius , Cing Tay Joc , Watkins Andrew
Published: May 2011

With the recent introduction of third generation (3G) technology in the field of mobile commu-nications, mobile phone service providers will have to find an effective strategy to market this new technology. One approach is to analyze the current profile of existing 3G subscribers to discover common patterns in their usage of mobile phones. With these usage patterns, the service provider can effectively target certain classes of customers who are more likely to purchase their subscription plans. To discover these patterns, we use a novel algorithm called Artificial Immune Recognition System (AIRS) that is based on the specificity of the human immune system. In our experiment, the algorithm performs well, achieving an accuracy rate in the range of 80% to 90%, depending on the set of parameter values used.
Mining Clinical Trial Data
Authors: Alvir Jose Ma. J. , Cabrera Javier , Caridi Frank , Nguyen Ha
Published: May 2011

Mining clinical trails is becoming an important tool for extracting information that might help design better clinical trials. One important objective is to identify characteristics of a subset of cases that responds substantially differently than the rest. For example, what are the characteristics of placebo respondents? Who have the best or worst response to a particular treatment? Are there subsets among the treated group who perform particularly well? In this chapter we give an overview of the processes of conducting clinical trials and the places where data mining might be of interest. We also introduce an algorithm for constructing data mining trees that are very useful for answering the above questions by detecting interesting features of the data. We illustrate the ARF method with an analysis of data from four placebo-controlled trials of ziprasidone in schizophrenia.
Vertical Database Design for Scalable Data Mining
Authors: Perrizo William , Ding Qiang , Serazi Masum , Abidin Taufik , Wang Baoying
Published: May 2011

For several decades and especially with the preeminence of relational database systems, data is almost always formed into horizontal record structures and then processed vertically (vertical scans of files of horizontal records). This makes good sense when the requested result is a set of horizontal records. In knowledge discovery and data mining, however, researchers are typically interested in collective properties or predictions that can be expressed very briefly. Therefore, the approaches for scan-based processing of horizontal records are known to be inadequate for data mining in very large data repositories (Han & Kamber, 2001; Han, Pei, & Yin, 2000; Shafer, Agrawal, & Mehta, 1996).
Emergent Semantics
Authors: Ratnaike Viranga , Srinivasan Bala , Nepal Surya
Published: May 2011

The semantic gap is recognized as one of the major problems in managing multimedia semantics. It is the gap between sensory data and semantic models. Often the sensory data and associated context compose situations which have not been anticipated by system architects. Emergence is a phenomenon that can be employed to deal with such unanticipated situations. In the past, researchers and practitioners paid little attention to applying the concepts of emergence to multimedia information retrieval. Recently, there have been attempts to use emergent semantics as a way of dealing with the semantic gap. This chapter aims to provide an overview of the field as it applies to multimedia. We begin with the concepts behind emergence, cover the requirements of emergent systems, and survey the existing body of research.
EMMO
Authors: Westermann U. , Zillner Sonja , Schellner Karin , Klas Wolfgang
Published: May 2011

Current semantic approaches to multimedia content modeling treat the content’s media, the semantic description of the content, and the functionality performed on the content, such as rendering, as separate entities, usually kept on separate servers in separate files or databases and typically under the control of different authorities. This separation of content from its description and functionality hinders the exchange and sharing of content in collaborative multimedia application scenarios. In this chapter, we propose Enhanced Multimedia MetaObjects (Emmos) as a new content modeling formalism that combines multimedia content with its description and functionality. Emmos can be serialized and exchanged in their entirety — covering media, description, and functionality — and are versionable, thereby establishing a suitable foundation for collaborative multimedia applications. We outline a distributed infrastructure for Emmo management and illustrate the benefits and usefulness of Emmos and this infrastructure by means of two practical applications.
Digital Watermarking Schemes for Multimedia Authentication
Authors: Li C. T.
Published: May 2011

As the interconnected networks for instant transaction prevail and the power of digital multimedia processing tools for perfect duplication and manipulation increases, forgery and impersonation become major concerns of the information era. This chapter is intended to disseminate the concept of digital watermarking for multimedia authentication. Issues and challenges, such as security, resolution of tamper localization, and embedding distortion, of this technical area are explained first. Three main categories of watermarking approaches, namely fragile, semi-fragile, and reversible schemes, to the issues and challenges are then presented. Merits and limitations of specific schemes of each category are also reviewed and compared.
Integrated-Services Architecture for Internet Multimedia Applications
Authors: Yang Z. , Yang Y. , Gu Y. , Gay Robert
Published: May 2011

The Internet has gone from near invisibility to near ubiquity and penetrated into every aspect of society in the past few years (Department of Commerce, 1998). The application scenarios have also changed dramatically and now demand a more sophisticated service model from the network. In the early 1990s, there was a large-scale experiment in sending digitized voice and video across the Internet through a packet-switched infrastructure (Braden, Clark, & Shenker, 1994). These highly visible experiments have depended upon three enabling technologies: (a) Many modern workstations now come equipped with built-in multimedia hardware, (b) IP multicasting, which was not yet generally available in commercial routers, is available, and (c) highly sophisticated digital audio and video applications have been developed. It became clear from these experiments that an important technical element of the Internet is still missing: Real-time applications often do not work well across the Internet. The Internet, as originally conceived, offers only a very simple quality-of-service (QoS), point-to-point, best-effort data delivery. However, for a real-time application, there are two aspects of the problem with using this service model. If the sender and/or receiver are humans, they simply cannot tolerate arbitrary delays; on the other hand, if the rate at which video and audio arrive is too low, the signal becomes incomprehensible. To support real-time Internet applications, the service model must address those services that relate most directly to the time of delivery of data. Real-time applications like video and audio conferencing typically require stricter guarantees on throughput and delay. The essence of real-time service is the requirement for some service guarantees in terms of timing. In response to these demands of real-time multimedia applications, the Internet Engineering Task Force (IETF) has significantly augmented the Internet protocol stack based on the Internet integrated-services model, which is the focus of this article.
Location-Based Multimedia Content Delivery System for Monitoring Purposes
Authors: Sotiriou A. , Kalliaras Panagiotis
Published: May 2011

This article presents a location-based multimedia content delivery system (LMCDS) for monitoring purposes, which incorporates media processing with a decision support system and positioning techniques for providing the appropriate content to the most suitable users, in respect to user profile and location, for monitoring purposes. This system is based on agent technology (Hagen & Magendanz, 1998) and aims to promote the social welfare, by increasing the overall situation awareness and efficiency in emergency cases and in areas of high importance. Such a system can be exploited in many operational (public or commercial) environments and offers increased security at a low cost.
Interactive Systems for Multimedia Opera
Authors: Olivia M
Published: May 2011

This chapter considers the development of systems to deliver multimedia content for new opera. After a short overview of the history of multimedia in opera, the specific requirements of opera are analysed, with emphasis of the fundamental musicality of operatic performance. Having considered the place of multimedia elements in the narrative and acting space, the relevance of previous practice in electroacoustic music and Vjing is considered as a model for a working approach. Several software and hardware configurations explored, including the use of gestural control by the actors themselves. The creation of a keyboard based “video instrument” with a dedicated performer, capable of integration into the pre- existing musical ensemble, is recommended as the most effective and practical solution.
Software Engineer for Mobile Multimedia
Authors: Mostefaoui G. K.
Published: May 2011

The abstract should be changed to this new abstract: Research on mobile multimedia mainly focuses on improving wireless protocols in order to improve the quality of services. In this chapter, we argue that another perspective should be investigated in more depth in order to boost the mobile multimedia industry. This perspective is software engineering which we believe it will speed up the development of mobile multimedia applications by enforcing reusability, maintenance, and testability. Without any pretense of being comprehensive in its coverage, this chapter identifies important software engineering implications of this technological wave and puts forth the main challenges and opportunities for the software engineering community.
Multimedia as a Cross-Channel for Cultures and Languages
Authors: Sharma R. C. , Mishra S.
Published: May 2011

Around the world many communities have been constantly struggling to maintain their customs, traditions and language. Many communities have been on the move from place to place due to various factors of social change, such as war, search of food, land, and climatic calamities. Such forces have given rise to different cultures and languages through fusion or the creation of new cultures. The cultures not only exist within nationalities and ethnic groups, but also within communities, organizations and other systems. A language is an integral component of cultural identification (Rogers & Steinfatt, 1999). Matsumoto (1996, p. 16) defined culture as, “the set of attitudes, values, beliefs, and behaviours shared by a group of people, but different for each individual, communicated from one generation to the next.” A culture is dynamic in nature; if static, it will cease or lose its identity in due course of time. Cultural values are affected and reinforced by languages. A language is a representation of a different way of thinking as well as a different way of speaking. Languages have significant influence on the cognition (Gudykunst & Asante, 1989; Pincas, 2001).
Developing Culturally Inclusive Educational Multimedia in the South Pacific
Authors: Robbins C.
Published: May 2011

This chapter explores how educational technology can be developed according to indigenous learning approaches of the South Pacific. It is based on an expansive research and development project conducted 2003-2004 at The University of the South Pacific (USP). After an introduction to several aspects of indigenous South Pacific learning approaches and their usage in the formal learning sector, I make several recommendations for instructional technology design based on these principles, illustrated with examples of educational technology projects that apply these recommendations. Specifically, we follow educational multimedia efforts at USP that enable learning in wholes, encourage observation and imitation and utilize vernacular metaphors and languages. This includes recommendations for interface design, interaction design and decentralized content localization.
Using an Interactive Feedback Tool to Enhance Pronunciation in Language Learning
Authors: Zhang F.
Published: May 2011

This chapter focuses on the effect of a learning environment in which biological, physical and technological ways of perceiving Mandarin Chinese sounds have been used. One of the most important tools of this environment is the use of a speech analysis tool for audio and visual feedback. This is done by way of incorporating a visual representation of student’s production that can be easily compared to the speech of a native speaker. It is the contention of this chapter that such an interactive feedback tool in conjunction with other feedback mechanisms can provide opportunities for increasing the effectiveness of feedback in language learning.
Interactive Multimedia for Learning and Performance
Authors: Banerji Ashok , Scales Glenda Rose
Published: May 2011

Developments in information and communication technologies (ICT) are rapidly transforming our work environments and methods. Amongst these changes, the advent of interactive multimedia technology has meant new approaches to instruction, information and performance support implementations. The available resources can be amalgamated in a suitable way to create an enabling environment for learning, training and performing. Concise descriptions of the salient aspects are presented along with basic design principles for communication and performance support. Guidelines for design and suggestions for implementation are provided for the benefit of the practitioners.
Integrating Multimedia Cues in E-Learning Documents for Enhanced Learning
Authors: Mittal Ankush , Pagalthivarthi Krishnan V. , Altman Edward
Published: May 2011

The digitization of educational content is radically transforming the learning environment of the student. A single lecture, as well as supporting reference material, textbook chapters, simulations, and threaded chat system archives, may be captured on one hour of video, a set of 20 or more slides, and ancillary text resources. A single course may contain 25 such lectures and a single department may have 30 distinct courses that have been digitized in a single year. If, while taking one course, a student wants to find a relevant definition, example, discussion, or illustration of a concept, then the student would potentially need to search as much as 750 hours of video, 15,000 slides, and a huge volume of text in order to find the desired information. Thus the online student is overwhelmed by a flood of multimedia data which inhibits the development of insight.
Learning through Business Games
Authors: Proserpio Luigi , Magni Massimo
Published: May 2011

Managerial business games, defined as interactive computer-based simulations for managerial education, can be considered as a relatively new tool for adults’ learning. If compared with paper-based case histories, they could be less consolidated in terms of design methodologies, usage suggestions, and results measurement.
Planning Effective Multimedia Instruction
Authors: Yu Chien , Williams Angela , Lin Chun Fu , Yu Wei-Chieh
Published: May 2011

Multimedia benefits students learning in many different ways. There are so many things that students can do and learn because of the variety of instructional media that is available for their use. The use of instructional multimedia increases an instructor’s ability to propose and execute teaching strategies that come with a multiplicity of learning styles. Therefore, there are a myriad of reasons why teachers use these resources both as a teaching tool and a teaching resource. Several strategies can be implemented so that teachers have opportunities to become skillful in attaining technological fluency. This chapter reviews the trends and issues of today’s multimedia education, and attempts to provide strategies and guidelines for planning multimedia instruction. The effective use of pedagogical design principles with appropriate multimedia can permit greater individualization, which in turn fosters improved learning, greater learner satisfaction, and higher retention rates.
The Importance of Interface Agent Characteristics from the End-User Perspective
Authors: Serenko Alexander
Published: May 2011

This chapter reports on an empirical investigation of user perceptions of the importance of several characteristics of interface agents. Interface agents are software entities that are incorporated in various computer applications including electronic mail systems. As evidenced by the growing body of empirical studies and the increasing number of interface agent-based applications on the software market, there is a strong need for the development of this technology. According to a meta-review of agent-related literature by Dehn and van Mulken (2000), there are several characteristics of interface agents that require special attention from agent developers. However, prior to this study, the importance of these characteristics from the end-user perspective remained unclear. In order to identify the significance of these characteristics, a group of the actual users of an email interface agent was surveyed. The results indicate that information accuracy and the degree of the usefulness of an agent are the most salient factors, followed by user comfortability with an agent, the extent of user enjoyment, and visual attractiveness of an agent. The implications of the findings for both theory and practice are discussed.
A Service Discovery Model for Mobile Agent Based Distributed Data Mining
Authors: Li Xining , Song Lei
Published: May 2011

Mining information from distributed data sources over the Internet is a growing research area. The introduction of mobile agent paradigm opens a new door for distributed data mining and knowledge discovery applications. One of the main challenges of mobile agent technology is how to locate hosts that provide services requested by mobile agents. Traditional Service Location Protocols can be applied to mobile agent systems to explore the service discovery issue. However, because of their architecture deficiencies, they do not adequately solve all the problems that arise in a dynamic domain such as database location discovery. From this point of view, we need some enhanced service discovery techniques for the mobile agent community. This paper proposes a new model for solving the database service location problem in the domain of mobile agents by implementing a Service Discovery Module based on Search Engine techniques. As a typical interface provided by a mobile agent server, the Service Discovery Module improves the decision ability of mobile agents with respect to information retrieval. This research is part of the IMAGO system - an infrastructure for mobile agent based data mining applications. This paper focuses on the design of an independent search engine, IMAGOSearch and discusses how to integrate service discovery into the IMAGO system, thus providing a global scope service location tool for intelligent mobile agents.
Interestingness Measures for Association Rules
Authors: Koh Yun Sing , O’Keefe Richard , Rountree Nathan
Published: May 2011

Association rules are patterns that offer useful information on dependencies that exist between the sets of items. Current association rule mining techniques such as apriori often extract a very large number of rules. To make sense of these rules we need to order or group the rules in some fashion such that the useful patterns are highlighted. The study of this process involves the investigation of an “interestingness” in the rules. To date, various measures have been proposed but unfortunately, these measures present inconsistent information about the interestingness of a rule. In this chapter, we show that different metrics try to capture different dependencies among variables. Each measure has its own selection bias that justifies the rationale for preferring it compared to other measures. We present an experimental study of the behaviour of the interestingness measures such as lift, rule interest, Laplace, and information gain. Our experimental results verify that many of these measures are very similar in nature. From the findings, we introduce a classification of the current interestingness measures.
Mining Association Rules from XML Data
Authors: Ding Qin , Sundarraj Gnanasekaran
Published: May 2011

With the growing usage of XML in the World Wide Web and elsewhere as a standard for the exchange of data and to represent semi-structured data, there is an imminent need for tools and techniques to perform data mining on XML documents and XML repositories. In this chapter, we propose a framework for association rule mining on XML data. We present a Java-based implementation of the Apriori and the FP-Growth algorithms for this task and compare their performances. We also compare the performance of our implementation with an XQuery-based implementation.