| Author | Title | Year | Journal/Proceedings | Reftype | DOI/URL |
|---|---|---|---|---|---|
| Illig, J., Hotho, A., Jäschke, R. & Stumme, G. | A Comparison of content-based Tag Recommendations in Folksonomy Systems [BibTeX] |
2011 | Postproceedings of the International Conference on Knowledge Processing in Practice (KPP 2007) | inproceedings | |
BibTeX:
@inproceedings{illig2011comparison,
author = {Illig, Jens and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
title = {A Comparison of content-based Tag Recommendations in Folksonomy Systems},
booktitle = {Postproceedings of the International Conference on Knowledge Processing in Practice (KPP 2007)},
publisher = {Springer},
year = {2011}
}
|
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| Cattuto, C., Benz, D., Hotho, A. & Stumme, G. | Semantic Grounding of Tag Relatedness in Social Bookmarking Systems | 2008 | The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008 | inproceedings | DOIURL |
| Abstract: Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For taskslike synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application. | |||||
BibTeX:
@inproceedings{cattuto2008semantica,
author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
title = {Semantic Grounding of Tag Relatedness in Social Bookmarking Systems},
booktitle = {The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008},
publisher = {Springer},
year = {2008},
volume = {5318},
pages = {615--631},
url = {http://www.kde.cs.uni-kassel.de/pub/pdf/cattuto2008semantica.pdf},
doi = {http://dx.doi.org/10.1007/978-3-540-88564-1_39}
}
|
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| Jäschke, R., Marinho, L., Hotho, A., Schmidt-Thieme, L. & Stumme, G. | Tag Recommendations in Social Bookmarking Systems | 2008 | AI Communications | article | DOIURL |
| Abstract: Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied.
this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of er-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender. |
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BibTeX:
@article{jaeschke2008tag,
author = {Jäschke, Robert and Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
title = {Tag Recommendations in Social Bookmarking Systems},
journal = {AI Communications},
publisher = {IOS Press},
year = {2008},
volume = {21},
number = {4},
pages = {231-247},
url = {http://dx.doi.org/10.3233/AIC-2008-0438},
doi = {http://dx.doi.org/10.3233/AIC-2008-0438}
}
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