bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Biomedical Terminological Resources for Information Retrieval
Authors: Pezik Piotr , Jimeno Yepes Antonio , Rebholz-Schuhmann Dietrich
Published: May 2010

The present chapter discusses the use of terminological resources for Information Retrieval in the biomedical domain. The authors first introduce a number of example resources which can be used to compile terminologies for biomedical IR and explain some of the common problems with such resources including redundancy, term ambiguity, and insufficient coverage of concepts and incomplete Semantic organization of such resources for text mining purposes. They also discuss some techniques used to address each of these deficiencies, such as static polysemy detection as well as adding terms and linguistic annotation from the running text. In the second part of the chapter, the authors show how query expansion based on using synonyms of the original query terms derived from terminological resources potentially increases the recall of IR systems. Special care is needed to prevent a query drift produced by the usage of the added terms and high quality word sense disambiguation algorithms can be used to allow more conservative query expansion. In addition, they present solutions that help focus on the user’s specific information need by navigating and rearranging the retrieved documents. Finally, they explain the advantages of applying terminological and Semantic resources at indexing time. The authors argue that by creating a Semantic index with terms disambiguated for their Semantic types and larger chunks of text denoting entities and relations between them, they can facilitate query expansion, reduce the need for query refinement and increase the overall performance of Information Retrieval. Semantic indexing also provides support for generic queries for concept categories, such as genes or diseases, rather than singular keywords.
Automatic Alignment of Medical Terminologies with General Dictionaries for an Efficient Information Retrieval
Authors: Diosan Laura , Rogozan Alexandrina , Pécuchet Jean-Pierre
Published: May 2010

The automatic alignment between a specialized terminology used by librarians in order to index concepts and a general vocabulary employed by a neophyte user in order to retrieve medical information will certainly improve the performances of the search process, this being one of the purposes of the ANR VODEL project. The authors propose an original automatic alignment of definitions taken from different dictionaries that could be associated to the same concept although they may have different labels. The definitions are represented at different levels (lexical, semantic and syntactic), by using an original and shorter representation, which concatenates more similarities measures between definitions, instead of the classical one (as a vector of word occurrence, whose length equals the number of different words from all the dictionaries). The automatic alignment task is considered as a classification problem and three Machine Learning algorithms are utilised in order to solve it: a k Nearest Neighbour algorithm, an Evolutionary Algorithm and a Support Vector Machine algorithm. Numerical results indicate that the syntactic level of nouns seems to be the most important, determining the best performances of the SVM classifier.
Discourse Processing for Text Mining
Authors: Lucas Nadine
Published: May 2010

This chapter presents the challenge of integrating knowledge at higher levels of discourse than the sentence, to avoid “missing the forest for the trees”. Characterisation tasks aimed at filtering collections are introduced, showing use of the whole set of layout constituents from sentence to text body. Few text descriptors encapsulating knowledge on text properties are used for each granularity level. Text processing differs according to tasks, whether individual document mining or tagging small or large collections prior to information extraction. Very shallow and domain independent techniques are used to tag collections to save costs on sentence parsing and semantic manual annotation. This approach achieves satisfactory characterisation of text types, for example reviews versus clinical reports, or argumentation-type articles versus explanation-type. These collection filtering techniques are fit for a wider domain of biomedical literature than genomics.
A Neural Network Approach Implementing Non-Linear Relevance Feedback to Improve the Performance of Medical Information Retrieval Systems
Authors: Kyriazis Dimosthenis , Doulamis Anastasios , Varvarigou Theodora
Published: May 2010

In this chapter, a non-linear relevance feedback mechanism is proposed for increasing the performance and the reliability of information (medical content) retrieval systems. In greater detail, the user who searches for information is considered to be part of the retrieval process in an interactive framework, who evaluates the results provided by the system so that the user automatically updates its performance based on the users’ feedback. In order to achieve the latter, we propose an adaptively trained neural network (NN) architecture that is able to implement the non- linear feedback. The term “adaptively” refers to the functionality of the neural network to update its weights based on the user’s content selection and optimize its performance.
Extracting Patient Case Profiles with Domain-Specific Semantic Categories
Authors: Zhang Yitao , Patrick Jon
Published: May 2010

The fast growing content of online articles of clinical case studies provides a useful source for extracting domain-specific knowledge for improving healthcare systems. However, current studies are more focused on the abstract of a published case study which contains little information about the detailed case profiles of a patient, such as symptoms and signs, and important laboratory test results of the patient from the diagnostic and treatment procedures. This paper proposes a novel category set to cover a wide variety of semantics in the description of clinical case studies which distinguishes each unique patient case. A manually annotated corpus consisting of over 5000 sentences from 75 journal articles of clinical case studies has been created. A sentence classification system which identifies 13 classes of clinically relevant content has been developed. A golden standard for assessing the automatic classifications has been established by manual annotation. A maximum entropy (MaxEnt) classifier is shown to produce better results than a Support Vector Machine (SVM) classifier on the corpus.
Identification of Sequence Variants of Genes from Biomedical Literature
Authors: Furlong Laura I. , Sanz Ferran
Published: May 2010

SNPs constitute key elements in genetic epidemiology and pharmacogenomics. While data about genetic variation is found at sequence databases, functional and phenotypic information on consequences of the variations resides in literature. Literature mining is mainly hampered by the terminology problem. Thus, automatic systems for the identification of citations of allelic variants of genes in biomedical texts are required. We have reported the development of OSIRIS, aimed at retrieving literature about allelic variants of genes, a system that evolved towards a new version incorporating a new entity recognition module. The new version is based on a terminology of variations and a pattern-based search algorithm for the identification of variation terms and their disambiguation to dbSNP identifiers. OSIRISv1.2 can be used to link literature references to dbSNP database entries with high accuracy, and is suitable for collecting current knowledge on gene sequence variations for supporting the functional annotation of variation databases.
Verification of Uncurated Protein Annotations
Authors: Couto Francisco M. , Silva Mário J. , Lee Vivian , Dimmer Emily , Camon Evelyn , Apweiler Rolf
Published: May 2010

Molecular Biology research projects produced vast amounts of data, part of which has been preserved in a variety of public databases. However, a large portion of the data contains a significant number of errors and therefore requires careful verification by curators, a painful and costly task, before being reliable enough to derive valid conclusions from it. On the other hand, research in biomedical information retrieval and information extraction are nowadays delivering Text Mining solutions that can support curators to improve the efficiency of their work to deliver better data resources. Over the past decades, automatic text processing systems have successfully exploited biomedical scientific literature to reduce the researchers’ efforts to keep up to date, but many of these systems still rely on domain knowledge that is integrated manually leading to unnecessary overheads and restrictions in its use. A more efficient approach would acquire the domain knowledge automatically from publicly available biological sources, such as BioOntologies, rather than using manually inserted domain knowledge. An example of this approach is GOAnnotator, a tool that assists the verification of uncurated protein annotations. It provided correct evidence text at 93% precision to the curators and thus achieved promising results. GOAnnotator was implemented as a web tool that is freely available at http://xldb.di.fc.ul.pt/rebil/tools/goa/.
A Software Tool for Biomedical Information Extraction (And Beyond)
Authors: Settles Burr
Published: May 2010

ABNER (A Biomedical Named Entity Recognizer) is an open-source software tool for text mining in the molecular biology literature. It processes unstructured biomedical documents in order to discover and annotate mentions of genes, proteins, cell types, and other entities of interest. This task, known as named entity recognition (NER), is an important first step for many larger information management goals in biomedicine, namely extraction of biochemical relationships, document classification, information retrieval, and the like. To accomplish this task, ABNER uses state-of-the-art machine learning models for sequence labeling called conditional random fields (CRFs). The software distribution comes bundled with two models that are pre-trained on standard evaluation corpora. ABNER can run as a stand-alone application with a graphical user interface, or be accessed as a Java API allowing it to be re-trained with new labeled corpora and incorporated into other, higher-level applications. This chapter describes the software and its features, presents an overview of the underlying technology, and provides a discussion of some of the more advanced natural language processing systems for which ABNER has been used as a component. ABNER is open-source and freely available from http://pages. cs.wisc.edu/~bsettles/abner/
Problems-Solving Map Extraction with Collective Intelligence Analysis and Language Engineering
Authors: Kawtrakul Asanee , Pechsiri Chaveevarn , Rajbhandari Sachit , Andres Frederic
Published: May 2010

Valuable knowledge has been distributed in heterogeneous formats on many different Web sites and other sources over the Internet. However, finding the needed information is a complex task since there is a lack of semantic relations and organization between them. This chapter presents a problem-solving map framework for extracting and integrating knowledge from unstructured documents on the Internet by exploiting the semantic links between problems, methods for solving them and the people who could solve them. This challenging area of research needs both complex natural language processing, including deep semantic relation interpretation, and the participation of end-users for annotating the answers scattered on the Web. The framework is evaluated by generating problem solving maps for rice and human diseases.
An Objective Registration Method for Mandible Alignment
Authors: Vogel Andreas
Published: May 2010

This chapter introduces a computer-controlled method for mandible alignment. The exact positioning of the mandible in relation to the maxilla is still one of the great daily challenges in restorative dentistry. Between 1980 and 1991 long-term animal experimentation series about the performance of jaw muscles as well as temporomandibular joints were made at the University of Leipzig, Germany. Until today other studies of similar scale or approach can not be found in international literature. Miniature pigs were exposed to stress under unilateral disturbance of occlusion. Based on that morphological, histochemical and biochemical processings and some other functions were then analyzed. The studies proved that masticatory muscles play a vital role in the positioning of the mandible. Combining these findings with knowledge about support pin registration and the influence of masticatory force on the results of this method a computer-controlled registration method was developed. With the DIR®System exists a final method of measurement which gives objective, reproducible and documentable results.
3D Reconstructions from Few Projections in Oral Radiology
Authors: Schulze Ralf K.W.
Published: May 2010

Established techniques for three-dimensional radiographic reconstruction such as computed tomography (CT) or, more recently cone beam computed tomography (CBCT) require an extensive set of measurements/ projections from all around an object under study. The x-ray dose for the patient is rather high. Cutting down the number of projections drastically yields a mathematically challenging reconstruction problem. Few-view 3D reconstruction techniques commonly known as “tomosynthetic reconstructions” have gained increasing interest with recent advances in detector and information technology.
Rapid Prototyping and Dental Applications
Authors: Koidis Petros , Manda Marianthi
Published: May 2010

The present chapter deals with the introduction and implementation of rapid prototyping technologies in medical and dental field. Its purpose is to overview the advantages and limitations derived, to discuss the current status and to present the future directions, especially in dental sector. Furthermore, a flowchart is outlined describing the procedure from the patient to the final 3-D object, presenting the possible alternatives in the process. Finally, an example is presented, decribing the process of the construction of high accurate surgical guided templates in dental implantology, through rapid prototyping.
DemonD
Authors: Delalonde Charles , Soulier Eddie
Published: May 2010

This research leverages information retrieval activity in order to build a network of organizational expertise in a distributed R&D laboratory. The authors describe traditional knowledge management practices and review post-cognitivists theories in order to define social creation in collaborative information retrieval activity. The Actor-Network theory accurately describes association processes and includes both human and non-human entities. This chapter compares this theory with the emergence of Social Search services online and Experts’ Retrieval Systems. The chapter authors suggest afterward, a social search engine named DemonD that identifies documents but more specifically users relevant to a query. DemonD relies on transparent profile construction based upon user activity, community participation, and shared documents. Individuals are invited to participate in a dedicated newsgroup and the information exchanged is capitalized. The evaluation of our service both ergonomic and through a simulation provides encouraging data.
Improving OLAP Analysis of Multidimensional Data Streams via Efficient Compression Techniques
Authors: Cuzzocrea Alfredo , Furfaro Filippo , Masciari Elio , Saccà Domenico
Published: May 2010

Sensor networks represent a leading case of data stream sources coming from real-life application scenarios. Sensors are non-reactive elements which are used to monitor real-life phenomena, such as live weather conditions, network traffic etc. They are usually organized into networks where their readings are transmitted using low level protocols. A relevant problem in dealing with data streams consists in the fact that they are intrinsically multi-level and multidimensional in nature, so that they require to be analyzed by means of a multi-level and a multi-resolution (analysis) model accordingly, like OLAP, beyond traditional solutions provided by primitive SQL-based DBMS interfaces. Despite this, a significant issue in dealing with OLAP is represented by the so-called curse of dimensionality problem, which consists in the fact that, when the number of dimensions of the target data cube increases, multidimensional data cannot be accessed and queried efficiently, due to their enormous size. Starting from this practical evidence, several data cube compression techniques have been proposed during the last years, with alternate fortune. Briefly, the main idea of these techniques consists in computing compressed representations of input data cubes in order to evaluate time-consuming OLAP queries against them, thus supobtaining approximate answers. Similarly to static data, approximate query answering techniques can be applied to streaming data, in order to improve OLAP analysis of such kind of data. Unfortunately, the data cube compression computational paradigm gets worse when OLAP aggregations are computed on top of a continuously flooding multidimensional data stream. In order to efficiently deal with the curse of dimensionality problem and achieve high efficiency in processing and querying multidimensional data streams, thus efficiently supporting OLAP analysis of such kind of data, in this chapter we propose novel compression techniques over data stream readings that are materialized for OLAP purposes. This allows us to tame the unbounded nature of streaming data, thus dealing with bounded memory issues exposed by conventional DBMS tools. Overall, in this chapter we introduce an innovative, complex technique for efficiently supporting OLAP analysis of multidimensional data streams.
Warehousing and Mining Streams of Mobile Object Observations
Authors: Orlando S. , Raffaetà A. , Roncato A. , Silvestri C.
Published: May 2010

In this chapter, the authors discuss how data warehousing technology can be used to store aggregate information about trajectories of mobile objects, and to perform OLAP operations over them. To this end, the authors define a data cube with spatial and temporal dimensions, discretized according to a hierarchy of regular grids. This chapter analyses some measures of interest related to trajectories, such as the number of distinct trajectories in a cell or starting from a cell, the distance covered by the trajectories in a cell, the average and maximum speed and the average acceleration of the trajectories in the cell, and the frequent patterns obtained by a data mining process on trajectories. The authors focus on some specialised algorithms to transform data, and load the measures in the base cells. Such stored values are used, along with suitable aggregate functions, to compute the roll-up operations. The main issues derive, in this case, from the characteristics of input data (i.e., trajectory observations of mobile objects), which are usually produced at different rates, and arrive in streams in an unpredictable and unbounded way. Finally, the authors also discuss some use cases that would benefit from such a framework, in particular in the domain of supervision systems to monitor road traffic (or movements of individuals) in a given geographical area.
Anomaly Detection in Streaming Sensor Data
Authors: Pawling Alec , Yan Ping , Candia Julián , Schoenharl Tim , Madey Greg
Published: May 2010

This chapter considers a cell phone network as a set of automatically deployed sensors that records movement and interaction patterns of the population. The authors discuss methods for detecting anomalies in the streaming data produced by the cell phone network. The authors motivate this discussion by describing the Wireless Phone Based Emergency Response (WIPER) system, a proof-of-concept decision support system for emergency response managers. This chapter also discusses some of the scientific work enabled by this type of sensor data and the related privacy issues. The authors describe scientific studies that use the cell phone data set and steps we have taken to ensure the security of the data. The authors also describe the overall decision support system and discuss three methods of anomaly detection that they have applied to the data.
Intelligent Acquisition Techniques for Sensor Network Data
Authors: Baralis Elena , Cerquitelli Tania , D’Elia Vincenzo
Published: May 2010

After the metaphor “the sensor network is a database,” wireless sensor networks have become an important research topic in the database research community. Sensing technologies have developed new smart wireless devices which integrate sensing, processing, storage and communication capabilities. Smart sensors can programmatically measure physical quantities, perform simple computations, store, receive and transmit data. Querying the network entails the (frequent) acquisition of the appropriate sensor measurements. Since sensors are battery-powered and communication is the main source of power consumption, an important issue in this context is energy saving during data collection. This chapter thoroughly describes different clustering algorithms to efficiently discover spatial and temporal correlation among sensors and sensor readings. Discovered correlations allow the selection of a subset of good quality representatives of the whole network. Rather than directly querying all network nodes, only the representative sensors are queried to reduce the communication, computation and power consumption costs. Experiments with different clustering algorithms show the adaptability and the effectiveness of the proposed approach.
Intelligent Querying Techniques for Sensor Data Fusion
Authors: Chang Shi-Kuo , Costagliola Gennaro , Jungert Erland , Camara Karin
Published: May 2010

Sensor data fusion imposes a number of novel requirements on query languages and query processing techniques. A spatial/temporal query language called SQL has been proposed to support the retrieval of multimedia information from multiple sources and databases. This chapter investigates intelligent querying techniques including fusion techniques, multimedia data transformations, interactive progressive query building and SQL query processing techniques using sensor data fusion. The authors illustrate and discuss tasks and query patterns for information fusion, provide a number of examples of iterative queries and show the effectiveness of SQL in a command-action scenario.
Query Optimisation for Data Mining in Peer-to-Peer Sensor Networks
Authors: Roantree Mark , Smeaton Alan F. , O’Connor Noel E. , Andrieu Vincent , Legeay Nicolas , Camous Fabrice
Published: May 2010

One of the more recent sources of large volumes of generated data is sensor devices, where dedicated sensing equipment is used to monitor events and happenings in a wide range of domains, including monitoring human biometrics and behaviour. This chapter proposes an approach and an implementation of semi-automated enrichment of raw sensor data, where the sensor data can come from a wide variety of sources. The authors extract semantics from the sensor data using their XSENSE processing architecture in a multi-stage analysis. The net result is that sensor data values are transformed into XML data so that well-established XML querying via XPATH and similar techniques can be followed. The authors then propose to distribute the XML data on a peer-to-peer configuration and show, through simulations, what the computational costs of executing queries on this P2P network, will be. This approach is validated approach through the use of an array of sensor data readings taken from a range of biometric sensor devices, fitted to movie-watchers as they watched Hollywood movies. These readings were synchronised with video and audio analysis of the actual movies themselves, where we automatically detect movie highlights, which the authors try to correlate with observed human reactions. The XSENSE architecture is used to semantically enrich both the biometric sensor readings and the outputs of video analysis, into one large sensor database. This chapter thus presents and validates a scalable means of semi-automating the semantic enrichment of sensor data, thereby providing a means of large-scale sensor data management which is a necessary step in supporting data mining from sensor networks.
Geographic Routing of Sensor Data around Voids and Obstacles
Authors: Nikoletseas Sotiris , Powell Olivier , Rolim Jose
Published: May 2010

Geographic routing is becoming the protocol of choice for many sensor network applications. Some very efficient geographic routing algorithms exist, however they require a preliminary planarization of the communication graph. Planarization induces overhead which makes this approach not optimal when lightweight protocols are required. On the other hand, georouting algorithms which do not rely on planarization have fairly low success rates and either fail to route messages around all but the simplest obstacles or have a high topology control overhead (e.g. contour detection algorithms). This chapter describes the GRIC algorithm which was designed to overcome some of those limitations. The GRIC algorithm was proposed in (Powell & Nikoletseas, 2007a). It is the first lightweight and efficient on demand (i.e. all-to-all) geographic routing algorithm which does not require planarization, has almost 100% delivery rates (when no obstacles are added), and behaves well in the presence of large communication blocking obstacles.
Driver or Drifter? Two Case Studies of the Blended Learning Practices in Higher Education
Authors: Chew Esyin , Jones Norah
Published: May 2010

The emergence of blended learning has played a role as either driver or drifter to higher education (HE) in the modern world. This chapter explores the blended learning practices by investigating two higher educational institutions in the UK and Malaysia. First, the strategies and practices related to blended learning are clearly analysed and compared. A large amount of qualitative data extracted from academics’ experience is discussed. Primarily, the findings firmly show that blended learning enables educators to revisit and to rethink their professional ethos and values, and redesign their learning and teaching where necessary. Such revisiting and rethinking facilitate the awareness and praxis of blended learning (or vice-versa: blended learning facilitates the revisit and redesign). The in-depth discussions based on academics’ voices, and reflective matrix summary from the case studies described in this chapter will act as evidence of the blueprint for blended learning policy makers and practitioners.
Discourse Analysis on Hybrid Learning and Teaching and the Changing Roles of Teachers and Students in Hong Kong
Authors: Zhichang Xu , Lixun Wang
Published: May 2010

This chapter is based on a research project on hybrid teaching and learning. This emerging hybrid mode is gaining popularity in tertiary institutions because the new technologies have integrated the classroom and online teaching and learning into an organic productive environment. The research project adopts a discourse analysis approach and intends to investigate issues arising regarding the hybrid mode in a higher education institute in Hong Kong. These issues include 1) the discourse features of teaching and learning in the classroom face-to-face (FTF) and online computer-mediated communication (CMC); 2) the changing roles of teachers and students in the emerging hybrid environment; and 3) the implications of the hybrid mode on the effectiveness of teaching and learning. In addition, this research project also adopts questionnaire surveys among the teaching staff of a language education faculty and students of three courses offered in the hybrid mode to discover their attitudes towards the hybrid teaching and learning mode. The research findings suggest that in the hybrid environments, the traditional roles of the teachers as information providers, knowledge transmitters, supervisors and assessors, and the students as learners, participants, and respondents are still dominant. However, the teachers are also increasingly putting on new ‘hats’ as expert learners, facilitators, course designers and organizers. Apart from being learners, the students are also taking on new roles as topic contributors, meaning negotiators, information providers, strategic communicators and monitors.
Pedagogy Reconsidered in a Multimodal Blended Environment
Authors: O'Byrne Barbara
Published: May 2010

Blended course delivery has wide applications across diverse educational settings. By definition, it is multimodal and involves multiple delivery formats. However, scant research has examined the impact of multimodal, blended delivery on university pedagogy. This chapter makes the case for close examination of the theoretical and pedagogical foundation of blended learning and proposes that research is needed to establish and validate the constructivist principles associated with blended learning. A longitudinal analysis of surveys and in-depth interviews with instructors from a distance education graduate school in the United States identified and contextualized features of learner-centered pedagogy linked to blended learning.
Deployment of a Web Based Critiquing System for Essay Writing in Hybrid Learning Environment
Authors: Lee Fion S.L. , Wong Kelvin C.K. , Cheung William K.W. , Lee Cynthia F.K.
Published: May 2010

This chapter describes the use of a Web-based essay critiquing system and its integration into in a series of composition workshops for a group of secondary school students in Hong Kong. It begins with a review and application of the hybrid learning approach, followed by a description of latent semantic analysis, a methodology for corpus preparation. Then, the distribution computing architecture for essay critiquing system is described. It explicates the way in which the system is integrated with a writing pedagogy implemented in the workshop and the feasibility evaluation result is derived. The positive result confirms the benefits of hybrid learning.
Model for an Interaction Assessment Strategy in Hybrid Learning Including Web 2.0 Resources
Authors: Hijón-Neira Raquel , Velázquez-Iturbide Angel , Rodríguez-Martín Jonay
Published: May 2010

Who being a Hybrid Learning teacher in the Web 2.0 era has not made him/herself ask this question: “Are students working effectively while they are not in face to face class?” Sometimes the questions are asked but he/she does not have the knowledge to create an Interaction Assessment Strategy that could provide this information. The authors present in this chapter a Model that provides the steps and data that should result in a much better teaching/learning process. Thus, the Model presents the questions that should be made, the data model that should be worked on, the visualizations that should better fit each type of data and the process of analysis teachers could make to improve different features, such as: the way of presenting information to the students through the year, prevent students’ dropping outs and failures, and generally improve the pace of teaching.
Modular and Systematic Interface Design for Rich Internet Applications
Authors: Rossi Gustavo , Urbieta Matias , Ginzburg Jeronimo
Published: May 2010

In this chapter, we present a design approach for the interface of rich Internet applications, that is, those Web applications in which the conventional hypermedia paradigm has been improved with rich interaction styles. Our approach combines well-known techniques for advanced separation of concerns such as aspect-oriented software design, with the object oriented hypermedia design method (OOHDM) design model allowing to express in a high level way the structure and behaviours of the user interface as oblivious compositions of simpler interface atoms. Using simple illustrative examples we present the rationale of our approach, its core stages and the way it is integrated into the OOHDM. Some implementation issues are finally analyzed.
Towards Web 2.0 Applications
Authors: Bozzon Alessandro , Comai Sara , Fraternali Piero , Carughi Giovanni Toffetti
Published: May 2010

This chapter introduces a conceptual model for the design of Web 2.0 applications relying on rich Internet application (RIA) technologies. RIAs extend Web application features by allowing computation to be partitioned between the client and the server and support core Web 2.0 requirements, like real-time collaboration among users, sophisticated presentation and manipulation of multimedia content, and flexible human-machine interaction (synchronous and asynchronous, connected and disconnected). The proposed approach for the design of Web 2.0 applications extends a conceptual platform-independent model conceived for Web 1.0 applications with novel primitives capturing RIA features; the conceptual model can be automatically converted into implementations in all the most popular RIA technologies and frameworks like AJAX, OpenLaszlo, FLEX, AIR, Google Gears, Google Web toolkit, and Silverlight.
An Overview of and Criteria for the Differentiation and Evaluation of RIA Architectures
Authors: Linnenfelser Marcel , Weber Sebastian , Rech Jörg
Published: May 2010

An important aspect of Web 2.0, mentioned by Tim O’Reilly, is the rich user experience. Web 2.0 applications offer the user a desktop-like interface to bring back efficiency and productivity. The click-wait-andrefresh- cycle of normal Web applications leads to a less responsive, and thus less efficient, user interface. To serve the needs of these so-called rich Internet applications (RIA), many different approaches have emerged, based either on Web standards or on proprietary approaches. This chapter aims at defining a qualified criterion system for comparing RIA platforms. Thereafter, those RIA platforms are selected and analyzed in terms of the criterion system that is most likely to become widely accepted.
Accessing, Analyzing, and Extracting Information from User Generated Contents
Authors: Casoto Paolo , Dattolo Antonina , Omero Paolo , Pudota Nirmala , Tasso Carlo
Published: May 2010

The concepts of the participative Web, mass collaboration, and collective intelligence grow out of a set of Web methodologies and technologies which improve interaction with users in the development, rating, and distribution of user-generated content. UGC is one of the cornerstones of Web 2.0 and is the core concept of several different kinds of applications. UGC suggests new value chains and business models; it proposes innovative social, cultural, and economic opportunities and impacts. However, several open issues concerning semantic understanding and managing of digital information available on the Web, like information overload, heterogeneity of the available content, and effectiveness of retrieval are still unsolved. The research experiences we present in this chapter, described in literature or achieved in our research laboratory, are aimed at reducing the gap between users and information understanding, by means of collaborative and cognitive filtering, sentiment analysis, information extraction, and knowledge conceptual modeling.
Improving the Information Security of Collaborative Web Portals via Fine-Grained Role-Based Access Control
Authors: Demurjian S. , Ren H. , Berhe S. , Devineni M. , Vegad Sushil , Polineni K.
Published: May 2010

Collaborative portals are emerging as a viable technology to allow groups of individuals to easily author, create, update, and share content via easy-to-use Web-based interfaces, for example, MediaWiki, Microsoft’s Sharepoint, and so forth. From a security perspective, these products are often limited and coarse grained in their authorization and authentication. For example, in a Wiki, the security model is often at two ends of the spectrum: anonymous users with no authorization and limited access via readonly browsing vs. registered users with full-range of access and limited oversight in content creation and modification. However, in practice, such full and unfettered access may not be appropriate for all users and for all applications, particularly as the collaborative technology moves into commercial usage (where copyright and intellectual property are vital) or sensitive domains such as healthcare (which ushave stringent HIPAA requirements). In this chapter, we report on our research and development effort of a role-based access control for collaborative Web portals that encompasses and realizes security at the application level, the document level (authoring and viewing), and the look-and-feel of the portal itself.
On Using Wiki as a Tool for Collaborative Online Blended Learning
Authors: Wheeler Steve
Published: May 2010

This chapter explores the use of the wiki and its role as a cognitive tool to promote interaction and collaborative learning in higher education. The importance of the software to enable student created content, storage, and sharing of knowledge is reviewed. This chapter provides an evaluation of some of the affordances and constraints of wikis to promote critical thinking within a blended learning context. It assesses their potential to facilitate collaborative learning through community focused enquiry for geographically separated students and nomadic learners. One particular focus of the chapter is the development of new digital literacies and how students present their written work in wikis. The chapter also examines group dynamics within collaborative learning environments drawing on the data from a study conducted at the University of Plymouth in 2007, using wikis in teacher education. Finally, the chapter highlights some recent key contributions to the developing discourse on social software in what has been termed ‘the architecture of participation.’
Capturing Online Collaboration in the Design Elements Model for Web 2.0 and Beyond
Authors: Yang T. Andrew , Kim Dan J. , Vu Tri , Dhalwani Vishal
Published: May 2010

When analyzing the design elements of Web 1.0 applications, Rayport and Jaworski’s 7C Framework (2001) is a model commonly used by researchers. With the advancement of the Web into the Web 2.0 generation, the 7C Framework is insufficient in addressing a critical feature ubiquitously present in Web 2.0 applications, that is, collaboration. In our previous work, we had extended the 7C Framework into the 8C Framework by incorporating the collaboration element in order to capture the collaboration element in Web 2.0 applications (Yang, Kim, Dhalwani, & Vu, 2008). In this chapter, we present the 8C framework as a reference model for analyzing collaborative Web 2.0 applications, including online social networking Web sites and online collaborative sites such as Wikipedia.
Assessing the Total Cost of Ownership of Virtual Communities
Authors: vom Brocke Jan , Sonnenberg Christian , Lattemann Christoph , Stieglitz Stefan
Published: May 2010

The usage of social software and virtual community platforms opens up opportunities to bridge the gap between customers and companies and to integrate customers into the value-added process. Ideas generated by members of a virtual community can be utilized to improve and to innovate a company’s value adding activities. However, the implementation and operation of virtual communities may have a considerable impact on financial performance measures of a company. Hence, to measure the profitability of a virtual community appropriately, means of efficiency calculations have to be employed. The objective of this chapter is, therefore, to develop a measurement framework to evaluate the financial performance of a virtual community. The focus is on calculating the total cost of ownership. After introducing a general measurement framework, a particular measurement system is derived from the framework and is subsequently applied to a real life example of the Berlin Stock Exchange.
Online Human Activity Networks (OnHANs)
Authors: Kim Dan J. , Yang T. Andrew , Naik Ninad
Published: May 2010

Recently, Web 2.0 applications such as blogs, wikis (e.g., Wikipedia), social networks (e.g., MySpace), 3-D virtual worlds (e.g., Second Life), and so forth, have created fresh interest in the Internet as a new medium of social interactions and human collaborative activities. Since the emergence of Web 2.0 applications, Web services that support online human activities have gained an unprecedented boost. There have been conceptual studies on and overviews of individual Web 2.0 applications like blogs, online social networks, and so forth, but there has not been a study to date which provides a theoretical perspective on the online human activity networks (OnHANs) formed by these Web 2.0 applications. In this chapter, we classify various forms of OnHANs focusing on their social and business purposes, analyzing the core components of representative OnHANs from the angle of the activity theory, and finally providing a theoretical discussion concerning how OnHANs provide values to the individuals and the organizations involved in those activities.
Teamworking for Security
Authors: Bye Rainer , Camtepe Ahmet , Albayrak Sahin
Published: May 2010

Collaborative methods are promising tools for solving complex security tasks. In this context, the authors present the security overlay framework CIMD (Collaborative Intrusion and Malware Detection), enabling participants to state objectives and interests for joint intrusion detection and find groups for the exchange of security-related data such as monitoring or detection results accordingly; to these groups the authors refer as detection groups. First, the authors present and discuss a tree-oriented taxonomy for the representation of nodes within the collaboration model. Second, they introduce and evaluate an algorithm for the formation of detection groups. After conducting a vulnerability analysis of the system, the authors demonstrate the validity of CIMD by examining two different scenarios inspired sociology where the collaboration is advantageous compared to the non-collaborative approach. They evaluate the benefit of CIMD by simulation in a novel packet-level simulation environment called NeSSi (Network Security Simulator) and give a probabilistic analysis for the scenarios.
Trusted Computing for Collaboration
Authors: Abendroth Joerg , Kinkelin Holger
Published: May 2010

The term “trusted computing” refers to a technology developed by the Trusted Computing Group. It mainly addresses two questions: “Which software is executed on a remote computer?” and “How can secret keys and other security sensitive data be stored and used safely on a computer?”. In this chapter the authors introduce the ideas of the trusted computing technology first and later explain how it can help us with establishing “trust” into a business partner (e.g., for B2B or B2C interactions). More precisely: the authors explain how to establish trust into the business partner’s computing machinery. So in their chapter “trust” means, that one business partner can be sure, that the other business partner’s computing system behaves in an expected and non malicious manner. The authors define “trust” as something that can be measured by cryptographic functions on one computer and be reported towards and evaluated by the business partner’s computer, not as something that is derived from observations or built upon legal contracts.
Association between Web Semantics and Geographical Locations
Authors: Lui Kimman , Chan Keith C.C. , Mark Kai-Pan
Published: May 2010

Social software completely revolutionizes the way of information sharing by allowing every individual to read, share and publish online. In terms of marketing, it is an effective way to understand consumers’ perceptions and beliefs in different local regions by analyzing and comparing the web content regarding a specific product retrieved on the Internet with respect to different locations. Interestingly, incidents originated from a location may attract more Internet discussions by individuals from remote locations. Therefore, it is difficult to measure the strength of people’s perceptions between different locations if we solely rely on the web traffic statistics. Moreover, it is difficult to compare strength of perceptions retrieved by different search engines, at different times, and on different topics. To overcome these inadequacies, the authors introduce a quantitative metric, Perceived Index on Information (PI), to measure the strength of web content over different search engines, different time intervals, and different topics with respect to geographical locations. Further visualizing PI in maps provides an instant and low-cost mean for word-of-mouth analysis that brings competitive advantages in business marketing.
Visualization in Support of Social Networking on the Web
Authors: Leng J. , Sharrock Wes
Published: May 2010

In this chapter the authors explore the contribution visualization can make to the new interfaces of the Semantic Web in terms of the quality of presentation of content. In doing this they discuss some of the underlying technologies enabling the Web and the social forces that are driving the further development of user-manipulable interfaces.
On the Social Shaping of the Semantic Web
Authors: Kidd Paul T.
Published: May 2010

Addressed in this chapter is the Social Shaping of the Semantic Web in the context of moving beyond the workplace application domain that has so dominated the development of both Information and Communications Technologies (ICTs), and the Social Shaping of Technology perspective. The importance of paradigms and the values that shape technology are considered along with the utility value of ICT, this latter issue being somewhat central in the development of these technologies. The new circumstances of ubiquity and of uses of ICT beyond mere utility, as a means of having fun for example, are considered leading to a notion of the Semantic Web, not just as a tool for more effective Web searches, but also as a means of having fun. Given this possibility of the Semantic Web serving two very different audiences and purposes, the matter of how to achieve this is considered, but without resorting to the obvious and rather simple conceptual formulation of the Semantic Web as either A or B. The relevance of existing Social Shaping of Technology perspectives is addressed. New thoughts are presented on what needs to be central to the development of a Semantic Web that is both A and B. Key here is an intelligent relationship between the Semantic Web and those that use it. Central to achieving this are the notions of the value of people, control over technology, and non-utility as a dominant design principle (the idea of things that do not necessarily serve a specific purpose).
Social/Human Dimensions of Web Services
Authors: Draghici Anca , Barglazan Diana , Lewkowicz Myriam , Molcho Gila
Published: May 2010

This chapter presents some recent studies of the social and human dimension of Semantic Web services in the era of virtual organizations, focusing on the challenges, effects, and implications. The issues and results presented refer to the virtual organization known as the Virtual Research Laboratory for a Knowledge Community in Production (VRL-KCiP), Network of Excellence (NoE). In this chapter the authors analyze the risks arising from the modern communication process in this new form of organization, focusing in particular on the knowledge sharing process. Furthermore, they discuss the cultural aspects of managing a virtual organization that determine the efficiency of the knowledge management processes. The aim is to consider the challenges and the associated effect on developing Web services from the social/human perspective and to examine the impact on an organization’s cultural dimensions.