Improving the Exploration of Tag Spaces Using Automated Tag Clustering

Radelaar, Joni; Boor, Aart-Jan; Vandic, Damir; Dam, Jan-Willem van; Hogenboom, Frederik; Frăsincar, Flavius

doi:10.1007/978-3-642-22233-7_19

Cited by 7 publications

(5 citation statements)

References 17 publications

(18 reference statements)

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“…Finally, it is worthwhile to notice that clustering techniques has been extensively used in open metadata schemata (i.e., folksonomy-like systems) to enable the discovering of useful semantic relationships among terms in order to provide better guidance to users (e.g., [9][13] [16]). Thus, clustering in these approaches is oriented to enhance users' navigation efficiency, while our navigation dendrograms are oriented to enhance the internal efficiency of the supporting software.…”

Section: Related Workmentioning

confidence: 99%

Learning object repositories with dynamically reconfigurable metadata schemata

Gayoso-Cabada

Rodríguez-Cerezo

Sierra

2016

2016 International Symposium on Computers in Education (SIIE)

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Abstract-In this paper we describe a model of learning object repository in which users have full control on the metadata schemata. Thus, they can define new schemata and they can reconfigure existing ones in a collaborative fashion. As consequence, the repository must react to changes in schemata in a dynamic and responsive way. Since schemata enable operations like navigation and search, dynamic reconfigurability requires clever indexing strategies, resilient to changes in these schemata. For this purpose, we have used conventional inverted indexing approaches and we have also devised a hierarchical clusteringbased indexing model. By using Clavy, a system for managing learning object repositories in the field of the Humanities, we provide some experimental results that show how the hierarchical clustering-based model can outperform the more conventional inverted indexes-based solutions.

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Section: Related Workmentioning

confidence: 99%

Learning object repositories with dynamically reconfigurable metadata schemata

Gayoso-Cabada

Rodríguez-Cerezo

Sierra

2016

2016 International Symposium on Computers in Education (SIIE)

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“…Indeed, current OSNs offer little or no synonym (i.e., different words, same meaning) or homonym (i.e., same word, different meanings) control [33,48]. To overcome these problems, recent advances in the field of information sciences have proposed mechanisms for clustering semantically related tags (i.e., referred as topics in our paper) [24,56,31].…”

Section: Topic Analysismentioning

confidence: 99%

Implicit Contextual Integrity in Online Social Networks

Criado¹,

Such²

2015

Information Sciences

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Many real incidents demonstrate that users of Online Social Networks need mechanisms that help them manage their interactions by increasing the awareness of the different contexts that coexist in Online Social Networks and preventing them from exchanging inappropriate information in those contexts or disseminating sensitive information from some contexts to others. Contextual integrity is a privacy theory that conceptualises the appropriateness of information sharing based on the contexts in which this information is to be shared. Computational models of Contextual Integrity assume the existence of well-defined contexts, in which individuals enact pre-defined roles and information sharing is governed by an explicit set of norms. However, contexts in Online Social Networks are known to be implicit, unknown a priori and ever changing; users relationships are constantly evolving; and the information sharing norms are implicit. This makes current Contextual Integrity models not suitable for Online Social Networks. In this paper, we propose the first computational model of Implicit Contextual Integrity, presenting an information model and an Information Assistant Agent that uses the information model to learn implicit contexts, relationships and the information sharing norms to help users avoid inappropriate information exchanges and undesired information disseminations. Through an experimental evaluation, we validate the properties of Information Assistant Agents, which are shown to: infer the information sharing norms even if a small proportion of the users follow the norms and in presence of malicious users; help reduce the exchange of inappropriate information and the dissemination of sensitive information with only a partial view of the system and the information received and sent by their users; and minimise the burden to the users in terms of raising unnecessary alerts.Comment: Authors Version of the paper accepted for publication in the Information Sciences journal (http://www.journals.elsevier.com/information-sciences/

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“…They use the cosine similarity based on co-occurrence vectors to create semantic clusters of tags. (Radelaar et al, 2011)…”

Section: Radelaar Et Al's Approachmentioning

confidence: 99%

Semantic Emergence From Social Tagging Systems

Alruqimi

Aknin

2015

International Journal of Organizational and Collective Intelligence

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Recently, Social tagging systems (folksonomies) have become very popular platforms where content is created collaboratively by users. This kind of environments allows users to assign shared resources with freely chosen keywords (tags). Folksonomies provide a valuable addition to the knowledge organization methods since they allow users to choose vocabularies that meet their real tastes and cognition. However, the lacking of standardization and the flat structure of tags in folksonomies pose challenges for folksonomy searching and information retrieval. Several researches have been proposed to overcome these drawbacks. In this paper, the authors present, describe and compare the most relevant approaches to capturing hidden semantics in folksonomies and turning it into ontologies. The authors also present and describe many techniques, tools and online resources that can be useful in working on such systems. Finally, the authors propose an approach to extract ontology from social tagging systems.

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Improving the Exploration of Tag Spaces Using Automated Tag Clustering

Cited by 7 publications

References 17 publications

Learning object repositories with dynamically reconfigurable metadata schemata

Learning object repositories with dynamically reconfigurable metadata schemata

Implicit Contextual Integrity in Online Social Networks

Semantic Emergence From Social Tagging Systems

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