Discovering shared conceptualizations in folksonomies

Jäschke, Robert; Hotho, Andreas; Schmitz, Christoph; Ganter, Bernhard; Stumme, Gerd

doi:10.1016/j.websem.2007.11.004

Cited by 101 publications

(53 citation statements)

References 53 publications

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“…Aschke et al [5], observed that many factors limit WordNet from extensive coverage of Del.icio.us tags. WordNet only provides coverage of English language and is composed of static body of words while Del.icio.us has tags from different languages.…”

Section: Statistical and Mathematical Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Semantics discovery in social tagging systems: A review

Jabeen

Khusro

Majid

et al. 2014

Multimed Tools Appl

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Web 2.0 has brought many collaborative and novel applications which transformed the web as a medium and resulted in its exponential growth. Tagging systems are one of these killer applications. Tags are in free-form but represent the link between objective information and users' cognitive information. However, tags have ambiguity problem reducing precision. Hence search and retrieval pose a challenge on folksonomy systems which have flat, unstructured, non-hierarchical organization with unsupervised vocabulary. We present a brief survey of different approaches for adding semantics in folksonomies thus bringing structure and precision in search and navigation. We did comparative analysis to estimate the significance of each source of semantics. Then, we have categorized the approaches in a systematic way and summarized the feature set support. Based on the survey we end up with recommendations. Our survey and conclusion will prove to be relevant and beneficial for engineers and designers aiming to design and maintain well structured folksonomy with precise search and navigation results.

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Section: Statistical and Mathematical Techniquesmentioning

confidence: 99%

“…& Statistical/ Mathematical Approaches-Clustering techniques keeping in view only tagging information and tag co-occurrence to find out semantically related sets of tags and resources, out of folksonomy, are achieved in [12] Flickr clusters 5 . Such techniques require only statistical analysis tags and they lack semantic information.…”

Section: Clusteringmentioning

confidence: 99%

Semantics discovery in social tagging systems: A review

Jabeen

Khusro

Majid

et al. 2014

Multimed Tools Appl

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“…An approach for making explicit the semantics behind the tag space through mapping folksonomies to existent ontologies are presented by Specia et al [17]. Jaschke et al [18] defined a new data mining task, the mining of frequent tri-concepts, and presented an efficient algorithm to discover these implicit shared conceptualizations. Furthermore, there are many research works focusing on ontology learning from folksonomies.…”

Section: Related Workmentioning

confidence: 99%

Generating ontologies with basic level concepts from folksonomies

Chen

Cai

Leung

et al. 2010

Procedia Computer Science

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This paper deals with the problem of ontology generation. Ontology plays an important role in knowledge representation, and it is an artifact describing a certain reality with specific vocabulary. Recently many researchers have realized that folksonomy is a potential knowledge source for generating ontologies. Although some results have already been reported on generating ontologies from folksonomies, most of them do not consider what a more acceptable and applicable ontology for users should be, nor do they take human thinking into consideration. Cognitive psychologists find that most human knowledge is represented by basic level concepts which is a family of concepts frequently used by people in daily life. Taking cognitive psychology into consideration, we propose a method to generate ontologies with basic level concepts from folksonomies. Using Open Directory Project (ODP) as the benchmark, we demonstrate that the ontology generated by our method is reasonable and consistent with human thinking.

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“…Views are used in this case, since that blogs are not typically available on collaborative tagging websites, and as such the tags provided by bloggers suffer from the vocabulary problem and cannot be adequately used as a shared index. Finally in [17], the goal is to provide a seamless navigation between tag spaces, while the the work presented in [6] merges the areas of formal concept analysis and association rule mining to discover shared conceptualizations that are hidden in folksonomies.…”

Section: Unified Tag Spacesmentioning

confidence: 99%

Cross-tagging for personalized open social networking

Stewart

Diaz-Aviles

Nejdl

et al. 2009

Proceedings of the 20th ACM Conference on Hypertext and Hypermedia

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The Social Web is successfully established and poised for continued growth. Web 2.0 applications such as blogs, bookmarking, music, photo and video sharing systems are among the most popular; and all of them incorporate a social aspect, i.e., users can easily share information with other users. But due to the diversity of these applications -serving different aims -the Social Web is ironically divided. Blog users who write about music for example, could possibly benefit from other users registered in other social systems operating within the same domain, such as a social radio station. Although these sites are two different and disconnected systems, offering distinct services to the users, the fact that domains are compatible could benefit users from both systems with interesting and multi-faceted information. In this paper we propose to automatically establish social links between distinct social systems through cross-tagging, i.e., enriching a social system with the tags of other similar social system(s). Since tags are known for increasing the prediction quality of recommender systems (RS), we propose to quantitatively evaluate the extent to which users can benefit from cross-tagging by measuring the impact of different cross-tagging approaches on tag-aware RS for personalized resource recommendations. We conduct experiments in real world data sets and empirically show the effectiveness of our approaches.

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Discovering shared conceptualizations in folksonomies

Cited by 101 publications

References 53 publications

Semantics discovery in social tagging systems: A review

Semantics discovery in social tagging systems: A review

Generating ontologies with basic level concepts from folksonomies

Cross-tagging for personalized open social networking

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