471 research outputs found

    Semantic modelling of user interests based on cross-folksonomy analysis

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    The continued increase in Web usage, in particular participation in folksonomies, reveals a trend towards a more dynamic and interactive Web where individuals can organise and share resources. Tagging has emerged as the de-facto standard for the organisation of such resources, providing a versatile and reactive knowledge management mechanism that users find easy to use and understand. It is common nowadays for users to have multiple profiles in various folksonomies, thus distributing their tagging activities. In this paper, we present a method for the automatic consolidation of user profiles across two popular social networking sites, and subsequent semantic modelling of their interests utilising Wikipedia as a multi-domain model. We evaluate how much can be learned from such sites, and in which domains the knowledge acquired is focussed. Results show that far richer interest profiles can be generated for users when multiple tag-clouds are combine

    Analyzing Tag Semantics Across Collaborative Tagging Systems

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    The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance

    Folksonomy: the New Way to Serendipity

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    Folksonomy expands the collaborative process by allowing contributors to index content. It rests on three powerful properties: the absence of a prior taxonomy, multi-indexation and the absence of thesaurus. It concerns a more exploratory search than an entry in a search engine. Its original relationship-based structure (the three-way relationship between users, content and tags) means that folksonomy allows various modalities of curious explorations: a cultural exploration and a social exploration. The paper has two goals. Firstly, it tries to draw a general picture of the various folksonomy websites. Secundly, since labelling lacks any standardisation, folksonomies are often under threat of invasion by noise. This paper consequently tries to explore the different possible ways of regulating the self-generated indexation process.taxonomy; indexation; innovation and user-created content

    Why Do Folksonomies Need Semantic Web Technologies?

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    This paper is to investigate some general features of social tagging and folksonomies along with their advantages and disadvantages, and to present an overview of a tag ontology that can be used to represent tagging data at a semantic level using Semantic Web technologies. Several tag ontologies have been developed with a specific purpose and used in various websites. However, in order to represent tagging data at semantic level existing tag ontologies need to be interlinked, since individual tag ontology cannot represent overall features of tagging activities. After introducing conceptual overview of tagging and folksonomies and tag ontologies, we will propose the combinational model for linking tag ontologies

    Classifying Web 2.0 Supported Applications By Pattern Of Usage: Functional & Technical ISSUES

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    The rapid evolution of Internet technologies have witnessed new Web elements, such as blogs, wikis, social networking, social bookmarking, and other related applications referred to as Web 2.0. Web 1.0 paradigm was related with passive, just receptive users, whereas Web 2.0 paradigm relies mainly on user participation and user-generated content. In Web 2.0 applications users are invited to comment, share, edit, classify, as well as remix data from multiple sources. Although there are several Web 2.0 applications in the market there is still lack of a profound approach guiding the analysis, design and development of such applications. This paper suggests classifying Web 2.0 tools by “Pattern of Usage” or in other words the functionalities that characterize their specific features. By reviewing several literatures we extracted multiple attributes related to functionalities of Web 2.0 tools. These have been crystallised into 7 patterns of usage that include; Inter-connectivity, Content authoring, Content tagging & rating, Content aggregation & syndication, Content remixing, Content streaming and File sharing. By interlinking functionality/ usage with underlying technologies, techniques and architecture we provided insight into design and technical requirements for Web 2.0 supported applications. Furthermore we broke down the patterns into basic, elementary to include Inter-connectivity, File sharing and Content remixing, and secondary, supportive to include the other four patterns. This would provide the technical core for any development methodology targeted at Web 2.0 applications

    Semantic technologies: from niche to the mainstream of Web 3? A comprehensive framework for web Information modelling and semantic annotation

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    Context: Web information technologies developed and applied in the last decade have considerably changed the way web applications operate and have revolutionised information management and knowledge discovery. Social technologies, user-generated classification schemes and formal semantics have a far-reaching sphere of influence. They promote collective intelligence, support interoperability, enhance sustainability and instigate innovation. Contribution: The research carried out and consequent publications follow the various paradigms of semantic technologies, assess each approach, evaluate its efficiency, identify the challenges involved and propose a comprehensive framework for web information modelling and semantic annotation, which is the thesis’ original contribution to knowledge. The proposed framework assists web information modelling, facilitates semantic annotation and information retrieval, enables system interoperability and enhances information quality. Implications: Semantic technologies coupled with social media and end-user involvement can instigate innovative influence with wide organisational implications that can benefit a considerable range of industries. The scalable and sustainable business models of social computing and the collective intelligence of organisational social media can be resourcefully paired with internal research and knowledge from interoperable information repositories, back-end databases and legacy systems. Semantified information assets can free human resources so that they can be used to better serve business development, support innovation and increase productivity

    The next generation of the web: an organisational perspective

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    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

    Review of the state of the art: discovering and associating semantics to tags in folksonomies

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    This paper describes and compares the most relevant approaches for associating tags with semantics in order to make explicit the meaning of those tags. We identify a common set of steps that are usually considered across all these approaches and frame our descriptions according to them, providing a unified view of how each approach tackles the different problems that appear during the semantic association process. Furthermore, we provide some recommendations on (a) how and when to use each of the approaches according to the characteristics of the data source, and (b) how to improve results by leveraging the strengths of the different approaches
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