Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis

Collaborative tagging is a simple and effective method for organizing and sharing web resources using human created metadata. It has arisen out of the need for an efficient method of personal organization, as the number of digital resources in everyday lives increases. While tagging has become a proven organization scheme through its popularity and widespread use on the Web, little is known about its implications and how it may effectively be applied in different situations. This is due to the fact that tagging has evolved through several iterations of use on social software websites, rather than through a scientific or an engineering design process. The research presented in this thesis, through investigations in the domain of e-learning, seeks to understand more about the scientific nature of collaborative tagging through a number of human subject studies. While broad in scope, touching on issues in human computer interaction, knowledge representation, Web system architecture, e-learning, metadata, and information visualization, this thesis focuses on how collaborative tagging can supplement the growing metadata requirements of e-learning. I conclude by looking at how the findings may be used in future research, through using information based in the emergent social networks of social software, to automatically adapt to the needs of individual users

Automated deployment of machine learning applications to the cloud

The use of machine learning (ML) as a key technology in artificial intelligence (AI) is becoming more and more important in the increasing digitalization of business processes. However, the majority of the development effort of ML applications is not related to the programming of the ML model, but to the creation of the server structure, which is responsible for a highly available and error-free productive operation of the ML application. The creation of such a server structure by the developers is time-consuming and complicated, because extensive configurations have to be made. Besides the creation of the server structure, it is also useful not to put new ML application versions directly into production, but to observe the behavior of the ML application with respect to unknown data for quality assurance. For example, the error rate as well as the CPU and RAM consumption should be checked. The goal of this thesis is to collect requirements for a suitable server structure and an automation mechanism that generates this server structure, deploys the ML application and allows to observe the behavior of a new ML application version based on real-time user data. For this purpose, a systematic literature review is conducted to investigate how the behavior of ML applications can be analyzed under the influence of real-time user data before their productive operation. Subsequently, in the context of the requirements analysis, a target-performance analysis is carried out in the department of a management consulting company in the automotive sector. Together with the results of the literature research, a list of user stories for the automation tool is determined and prioritized. The automation tool is implemented in the form of a Python console application that enables the desired functionality by using IaC (Infrastructure as code) and the AWS (Amazon Web Services) SDK in the cloud. The automation tool is finally evaluated in the department. The ten participants independently carry out predefined usage scenarios and then evaluate the tool using a questionnaire developed on the basis of the TAM model. The results of the evaluation are predominantly positive and the constructive feedback of the participants includes numerous interesting comments on possible adaptions and extensions of the automation tool

From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

The next generation of the web: an organisational perspective

The web has revolutionised information sharing, management, interoperability and knowledge discovery. The union of the two prominent web frameworks, Web 2.0 and the Semantic Web is often referred to as Web 3.0. This paper explores the basics behind the two paradigms, assesses their influence over organisational change and considers their effectiveness in supporting innovative solutions. It then outlines the challenges of combining the two web paradigms to form Web 3.0 and critically evaluates the impact that Web 3.0 will have on the social organisation. The research carried out follows action research principles and adopts an investigative and reviewing approach to the emerging trends and patterns that develop from the web's changing use, examining the underpinning enabling technologies that facilitate access, innovation and organisational change

Social software for music

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 200

Smart manufacturing: role of Internet of Things in process optimization

This research is primarily focused on process optimization in manufacturing field in business-to-business context. The study is an effort to point out the issues manufacturers face at their shop floor and it provides solutions for dealing with those issues. During the last decade the Internet of Things (IoT) has gained a lot of attention from both academia and practitioners. IoT emphasizes on the importance of physical objects transferring information by using both software and the Internet. Based on the global trends, nowadays, there is a clear requirement for companies to focus on how they can implement IoT in order to facilitate their businesses and create new business and market opportunities. IoT is able to connect various things and objects around us which are able to interact with each other. In other words, IoT technologies not only connect a particular industrial system or supply chain, but also connects stakeholders and end-customers. The goal of the thesis is to discuss IoT technologies and elaborate on how they are implemented in manufacturing processes. One empirical case study on IoT applications in shop floors and production lines carried out. Two cases were selected based on being a pioneer in implementing IoT technologies into manufacturing and highly optimized production at targeted factories. The cases represent next generation of smart factories which IoT technologies and in particular RFID solutions play an important role. A qualitative document analysis was conducted. The topic of this research is relatively new and therefore majority of references used for this paper are from 2014 onwards. Data were collected from public, non-confidential information sources including press releases, newspapers, articles and journals. The research approach was primarily descriptive with the focus on differences between previous production optimization technologies and IoT applications in use today. The results of thesis demonstrates that IoT technologies bring transparency, traceability, adaptability, scalability and flexibility to the system. Therefore, the adoption of IoT has quite a few potential benefits, including improvement in cost and risk reduction, operational processes and value creation. This research also shows that using IoT technologies for their benefits is not an easy task for enterprises. Companies face many challenges on the way including layout changes in the factory’s shop floor, changes in the design of the products, security concerns and consumer privacy. Moreover, since the IoT is a recent development, different aspects of the IoT such as economical, managerial and industrial aspects need to be studied. And this makes companies hesitant to make decisions regarding the adoption of IoT

MC2: MPEG-7 content modelling communities

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe use of multimedia content on the web has grown significantly in recent years. Websites such as Facebook, YouTube and Flickr cater for enormous amounts of multimedia content uploaded by users. This vast amount of multimedia content requires comprehensive content modelling otherwise retrieving relevant content will be challenging. Modelling multimedia content can be an extremely time consuming task that may seem impossible particularly when undertaken by individual users. However, the advent of Web 2.0 and associated communities, such as YouTube and Flickr, has shown that users appear to be more willing to collaborate in order to take on enormous tasks such as multimedia content modelling. Harnessing the power of communities to achieve comprehensive content modelling is the primary focus of this research. The aim of this thesis is to explore collaborative multimedia content modelling and in particular the effectiveness of existing multimedia content modelling tools, taking into account the key development challenges of existing collaborative content modelling research and the associated modelling tools. Four research objectives are pursued in order to achieve this; first, design a user experiment to study users’ tagging behaviour with existing multimedia tagging tools and identify any relationships between such user behaviour; second, design and develop a framework for MPEG-7 content modelling communities based on the results of the experiment; third, implement an online service as a proof of concept of the framework; fourth, validate the framework through the online service during a repeat of the initial user experiment. This research contributes first, a conceptual model of user behaviour visualised as a fuzzy cognitive map and, second, an MPEG-7 framework for multimedia content modelling communities (MC2) and its proof of concept as an online service. The fuzzy cognitive model embodies relationships between user tagging behaviour and context and provides an understanding of user priorities in the description of content features and the relationships that exist between them. The MC2 framework, developed based on the fuzzy cognitive model, is deep-rooted in user content modelling behaviour and content preferences. A proof of concept of the MC2 framework is implemented as an online service in which all metadata is modelled using MPEG-7. The online service is validated, first, empirically with the same group of users and through the same experiment that led to the development of the fuzzy cognitive model and, second, functionally against the folksonomy and MPEG-7 content modelling tools used in the initial experiment. The validation demonstrates that MC2 has the advantages without the shortcomings of existing multimedia tagging tools by harnessing the ease of use of folksonomy tools while producing comprehensive structured metadata.Supported by UK Engineering and Physical Sciences Research Council (EPSRC