Exploring The Value Of Folksonomies For Creating Semantic Metadata

Finding good keywords to describe resources is an on-going problem: typically we select such words manually from a thesaurus of terms, or they are created using automatic keyword extraction techniques. Folksonomies are an increasingly well populated source of unstructured tags describing web resources. This paper explores the value of the folksonomy tags as potential source of keyword metadata by examining the relationship between folksonomies, community produced annotations, and keywords extracted by machines. The experiment has been carried-out in two ways: subjectively, by asking two human indexers to evaluate the quality of the generated keywords from both systems; and automatically, by measuring the percentage of overlap between the folksonomy set and machine generated keywords set. The results of this experiment show that the folksonomy tags agree more closely with the human generated keywords than those automatically generated. The results also showed that the trained indexers preferred the semantics of folksonomy tags compared to keywords extracted automatically. These results can be considered as evidence for the strong relationship of folksonomies to the human indexer’s mindset, demonstrating that folksonomies used in the del.icio.us bookmarking service are a potential source for generating semantic metadata to annotate web resources

Creating structure from disorder: using folksonomies to create semantic metadata

This paper reports on an on-going research project to create educational semantic metadata out of folksonomies. The paper describes a simple scenario for the usage of the generated semantic metadata in teaching, and describes the ‘FolksAnnotation’ tool which applies an organization scheme to tags in a specific domain of interest. The contribution of this paper is to describe an evaluation framework which will allow us to validate our claim that folksonomies are potentially a rich source of metadata

Automatic document-level semantic metadata annotation using folksonomies and domain ontologies

The last few years have witnessed a fast growth of the concept of Social Software. Be it video sharing such as YouTube, photo sharing such as Flickr, community building such as MySpace, or social bookmarking such as del.icio.us. These websites contain valuable user-generated metadata called folksonomies. Folksonomies are ad hoc, light-weight knowledge representation artefacts to describe web resources using people’s own vocabulary. The cheap metadata contained in such websites presents potential opportunities for us (researchers) to benefit from. This thesis presents a novel tool that uses folksonomies to automatically generate metadata with educational semantics in an attempt to provide semantic annotations to bookmarked web resources, and to help in making the vision of the Semantic Web a reality. The tool comprises two components: the tags normalisation process and the semantic annotation process. The tool uses the del.icio.us social bookmarking service as a source for folksonomy tags. The tool was applied to a case study consisting of a framework for evaluating the usefulness of the generated semantic metadata within the context of a particular eLearning application. This implementation of the tool was evaluated over three dimensions: the quality, the searchability and the representativeness of the generated semantic metadata. The results show that folksonomy tags were acceptable for creating semantic metadata. Moreover, folksonomy tags showed the power of aggregating people’s intelligence. The novel contribution of this work is the design of a tool that utilises folksonomy tags to automatically generate metadata with fine gained and extra educational semantics

FAsTA: A Folksonomy-Based Automatic Metadata Generator

Folksonomies provide a free source of keywords describing web resources, however, these keywords are free form and unstructured. In this paper, we describe a novel tool that converts folksonomy tags into semantic metadata, and present a case study consisting of a framework for evaluating the usefulness of this metadata within the context of a particular eLearning application. The evaluation shows the number of ways in which the generated semantic metadata adds value to the raw folksonomy tags

Towards Better Understanding of Folksonomic Patterns

Folksonomies provide a free source of keywords describing web resources; however, these keywords are free form and their semantics spans multiple contextual dimension. In this paper, we present a pragmatic experiment that analyzes folksonomy tags using three classification categories: Personal, Factual and Subjective, in order to gain more understanding of the types of tags used in the social tagging process. The rational for this work was to measure the potential portion of folksonomy tags that might be helpful when considering the creation of structured metadata

An Educational Tool for Generating Inaccessible Page Examples Based on WCAG 2.0 Failures

Abstract One of the problems encountered while teaching web accessibility evaluation to undergraduate students is the lack of proper educational tools that support learning accessibility barriers modularly. This paper presents an online educational tool called Accessibility Example Generator (AEG), designed to assist instructors in the process of creating examples of inaccessible web pages that violate the accessibility guidelines of WCAG 2.0. The online tool supports generating the examples in a form which can be received and reviewed easily by undergraduate computing students. By using a sequence of tailored checks, the instructor can choose which failure or combination of failures the example should include. Utilizing such a tool while teaching web accessibility will enrich the learning and understanding of WCAG 2.0 guidelines through generating modular examples that will not overwhelm the student and at the same time will help spread the knowledge of accessibility through future developers.King Saud Universit

On the Development of a Web-Based M-Learning System for Dual Screen Handheld Game Consoles

This paper presents our experience on the design and development of an M-Learning web-based system for the Nintendo DSi game console. The paper starts by addressing the difficulties that emerged from the lack of resources on design guidelines for dual screen devices also the absence of adequate techniques and methods to support the design decisions. Then it explains how we overcame these challenges by adopting a design decision suitable for the screen requirements of the Nintendo DSi console. Finally, we present the components of our M-Learning system and the results of a preliminary usability evaluation

On the Development of a Web-Based M-Learning System for Dual Screen Handheld Game Consoles

This paper presents our experience on the design and development of an M-Learning web-based system for the Nintendo DSi game console. The paper starts by addressing the difficulties that emerged from the lack of resources on design guidelines for dual screen devices also the absence of adequate techniques and methods to support the design decisions. Then it explains how we overcame these challenges by adopting a design decision suitable for the screen requirements of the Nintendo DSi console. Finally, we present the components of our M-Learning system and the results of a preliminary usability evaluation