Jäschke, R.; Marinho, L. B.; Hotho, A.; Schmidt-Thieme, L. & Stumme, G.: Tag Recommendations in Folksonomies. In: Kok, J. N.; Koronacki, J.; de Mántaras, R. L.; Matwin, S.; Mladenic, D. & Skowron, A. (Hrsg.): Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases. Berlin, Heidelberg: Springer, 2007 (Lecture Notes in Computer Science 4702), S. 506-514
[Volltext]
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 two recommendation algorithms on largescale real life datasets: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank. We show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.
@inproceedings{jaeschke2007tag,
author = {Jäschke, Robert and Marinho, Leandro Balby and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
title = {Tag Recommendations in Folksonomies},
editor = {Kok, Joost N. and Koronacki, Jacek and de Mántaras, Ramon López and Matwin, Stan and Mladenic, Dunja and Skowron, Andrzej},
booktitle = {Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
address = {Berlin, Heidelberg},
year = {2007},
volume = {4702},
pages = {506-514},
url = {http://dx.doi.org/10.1007/978-3-540-74976-9_52},
isbn = {978-3-540-74975-2},
keywords = {2007, FolkRank, Folksonomies, Recommendations, folksonomies, itegpub, l3s, myown, nepomuk, ranking, recommendations, tagging},
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 two recommendation algorithms on largescale real life datasets: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank. We show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.}
}
Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.: FolkRank: A Ranking Algorithm for Folksonomies. Proc. FGIR 2006. 2006
[Volltext]
In social bookmark tools users are setting up
ghtweight conceptual structures called folksonomies. Currently,
e information retrieval support is limited. We present a formal
del and a new search algorithm for folksonomies, called
lkRank, that exploits the structure of the folksonomy. The
oposed algorithm is also applied to find communities within the
lksonomy and is used to structure search results. All findings are
monstrated on a large scale dataset. A long version of this paper
s been published at the European Semantic Web Conference
06.
@inproceedings{hotho2006folkrank,
author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
title = {FolkRank: A Ranking Algorithm for Folksonomies},
booktitle = {Proc. FGIR 2006},
year = {2006},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006folkrank.pdf},
keywords = {2006, algorithm, folkrank, ir, itegpub, l3s, myown, nepomuk, pagerank, ranking},
abstract = { In social bookmark tools users are setting up
ghtweight conceptual structures called folksonomies. Currently,
e information retrieval support is limited. We present a formal
del and a new search algorithm for folksonomies, called
lkRank, that exploits the structure of the folksonomy. The
oposed algorithm is also applied to find communities within the
lksonomy and is used to structure search results. All findings are
monstrated on a large scale dataset. A long version of this paper
s been published at the European Semantic Web Conference
06.}
}
Hotho, A.; J?schke, R.; Schmitz, C. & Stumme, G.: Information Retrieval in Folksonomies: Search and Ranking. In: Sure, Y. & Domingue, J. (Hrsg.): The Semantic Web: Research and Applications. Heidelberg: Springer, 2006 (LNAI 4011), S. 411-426
@inproceedings{hotho2006information,
author = {Hotho, Andreas and J?schke, Robert and Schmitz, Christoph and Stumme, Gerd},
title = {Information Retrieval in Folksonomies: Search and Ranking},
editor = {Sure, York and Domingue, John},
booktitle = {The Semantic Web: Research and Applications},
series = {LNAI},
publisher = {Springer},
address = {Heidelberg},
year = {2006},
volume = {4011},
pages = {411-426},
keywords = {2006, FCA, IR, OntologyHandbook, folkrank, folksonomy, information, informationretrieval, itegpub, mimose, myown, pagerank, ranking, retrieval}
}
Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.: Information Retrieval in Folksonomies: Search and Ranking. In: Sure, Y. & Domingue, J. (Hrsg.): The Semantic Web: Research and Applications. Heidelberg: Springer, 2006 (LNAI 4011), S. 411-426
@inproceedings{hotho2006information,
author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
title = {Information Retrieval in Folksonomies: Search and Ranking},
editor = {Sure, York and Domingue, John},
booktitle = {The Semantic Web: Research and Applications},
series = {LNAI},
publisher = {Springer},
address = {Heidelberg},
year = {2006},
volume = {4011},
pages = {411-426},
keywords = {2006, FCA, IR, OntologyHandbook, folkrank, folksonomy, information, informationretrieval, itegpub, mimose, myown, pagerank, ranking, retrieval}
}