Analysis of the Publication Sharing Behaviour in BibSonomy.
In: U. Priss, S. Polovina und R. Hill
(Herausgeber):
Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007), Band 4604, Reihe Lecture Notes in Artificial Intelligence, Seiten 283-295.
Springer-Verlag, Berlin, Heidelberg, 2007.
Robert Jäschke, Andreas Hotho, Christoph Schmitz und Gerd Stumme.
[Kurzfassung]
[BibTeX]
BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.
Analysis of the Publication Sharing Behaviour in BibSonomy.
In: U. Priss, S. Polovina und R. Hill
(Herausgeber):
Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007), Band 4604, Reihe Lecture Notes in Artificial Intelligence, Seiten 283-295.
Springer-Verlag, Berlin, Heidelberg, 2007.
Robert Jäschke, Andreas Hotho, Christoph Schmitz und Gerd Stumme.
[Kurzfassung]
[BibTeX]
BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.
Analysis of the Publication Sharing Behaviour in BibSonomy.
In:
Proceedings of the 15th International Conference on Conceptual Structures, Band 4604, Reihe LNCS.
Sheffield, England, 2007.
Robert Jäschke, Andreas Hotho, Christoph Schmitz und Gerd Stumme.
[Kurzfassung]
[BibTeX]
BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.
Analysis of the Publication Sharing Behaviour in BibSonomy.
In: U. Priss, S. Polovina und R. Hill
(Herausgeber):
Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007), Band 4604, Reihe Lecture Notes in Artificial Intelligence, Seiten 283-295.
Springer-Verlag, Berlin, Heidelberg, 2007.
Robert Jäschke, Andreas Hotho, Christoph Schmitz und Gerd Stumme.
[Kurzfassung]
[BibTeX]
BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.
Analysis of the Publication Sharing Behaviour in BibSonomy.
In: U. Priss, S. Polovina und R. Hill
(Herausgeber):
Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007), Band 4604, Reihe Lecture Notes in Artificial Intelligence, Seiten 283-295.
Springer-Verlag, Berlin, Heidelberg, 2007.
Robert Jäschke, Andreas Hotho, Christoph Schmitz und Gerd Stumme.
[Kurzfassung]
[BibTeX]
BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.
Organizing Publications and Bookmarks in BibSonomy.
In: H. Alani, N. Noy, G. Stumme, P. Mika, Y. Sure und D. Vrandecic
(Herausgeber):
Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007.
Banff, Canada, 2007.
Robert Jäschke, Miranda Grahl, Andreas Hotho, Beate Krause, Christoph Schmitz und Gerd Stumme.
[doi]
[BibTeX]
Organizing Publications and Bookmarks in BibSonomy.
In: H. Alani, N. Noy, G. Stumme, P. Mika, Y. Sure und D. Vrandecic
(Herausgeber):
Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007.
Banff, Canada, 2007.
Robert Jäschke, Miranda Grahl, Andreas Hotho, Beate Krause, Christoph Schmitz und Gerd Stumme.
[doi]
[BibTeX]
Organizing Publications and Bookmarks in BibSonomy.
In: H. Alani, N. Noy, G. Stumme, P. Mika, Y. Sure und D. Vrandecic
(Herausgeber):
Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007.
Banff, Canada, 2007.
Robert Jäschke, Miranda Grahl, Andreas Hotho, Beate Krause, Christoph Schmitz und Gerd Stumme.
[doi]
[BibTeX]
Organizing Publications and Bookmarks in BibSonomy.
In: H. Alani, N. Noy, G. Stumme, P. Mika, Y. Sure und D. Vrandecic
(Herausgeber):
Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007.
Banff, Canada, 2007.
Robert Jäschke, Miranda Grahl, Andreas Hotho, Beate Krause, Christoph Schmitz und Gerd Stumme.
[doi]
[BibTeX]
Organizing Publications and Bookmarks in BibSonomy.
In: H. Alani, N. Noy, G. Stumme, P. Mika, Y. Sure und D. Vrandecic
(Herausgeber):
Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007.
Banff, Canada, 2007.
Robert Jäschke, Miranda Grahl, Andreas Hotho, Beate Krause, Christoph Schmitz und Gerd Stumme.
[doi]
[BibTeX]
Organizing Publications and Bookmarks in BibSonomy.
In: H. Alani, N. Noy, G. Stumme, P. Mika, Y. Sure und D. Vrandecic
(Herausgeber):
Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007.
Banff, Canada, 2007.
Robert Jäschke, Miranda Grahl, Andreas Hotho, Beate Krause, Christoph Schmitz und Gerd Stumme.
[doi]
[BibTeX]
Organizing Publications and Bookmarks in BibSonomy.
In: H. Alani, N. Noy, G. Stumme, P. Mika, Y. Sure und D. Vrandecic
(Herausgeber):
Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007.
Banff, Canada, 2007.
Robert Jäschke, Miranda Grahl, Andreas Hotho, Beate Krause, Christoph Schmitz und Gerd Stumme.
[doi]
[BibTeX]
Tag Recommendations in Folksonomies.
In: J. N. Kok, J. Koronacki, R. L. de Mántaras, S. Matwin, D. Mladenic und A. Skowron
(Herausgeber):
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Band 4702, Reihe Lecture Notes in Computer Science, Seiten 506-514.
Springer, Berlin, Heidelberg, 2007.
Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme und Gerd Stumme.
[doi]
[Kurzfassung]
[BibTeX]
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.
In 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.
Tag Recommendations in Folksonomies.
In: A. Hinneburg
(Herausgeber):
Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007), Seiten 13-20.
Martin-Luther-Universität Halle-Wittenberg, 2007.
Robert Jäschke, Leandro Marinho, Andreas Hotho, Lars Schmidt-Thieme und Gerd Stumme.
[doi]
[BibTeX]
Tag Recommendations in Folksonomies.
In: J. N. Kok, J. Koronacki, R. L. de Mántaras, S. Matwin, D. Mladenic und A. Skowron
(Herausgeber):
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings, Band 4702, Reihe Lecture Notes in Computer Science, Seiten 506-514.
Springer, 2007.
Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme und Gerd Stumme.
[doi]
[BibTeX]
Tag Recommendations in Folksonomies.
In: A. Hinneburg
(Herausgeber):
Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007), Seiten 13-20.
Martin-Luther-Universität Halle-Wittenberg, 2007.
Robert Jäschke, Leandro Marinho, Andreas Hotho, Lars Schmidt-Thieme und Gerd Stumme.
[doi]
[Kurzfassung]
[BibTeX]
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. In this paper we present two tag recommendation algorithms: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank, an adaptation of the well-known PageRank algorithm that can cope with undirected triadic hyperedges. We evaluate and compare both algorithms on large-scale real life datasets and show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.
Tag Recommendations in Folksonomies.
In: J. N. Kok, J. Koronacki, R. L. de Mántaras, S. Matwin, D. Mladenic und A. Skowron
(Herausgeber):
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Band 4702, Reihe Lecture Notes in Computer Science, Seiten 506-514.
Springer, Berlin, Heidelberg, 2007.
Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme und Gerd Stumme.
[doi]
[Kurzfassung]
[BibTeX]
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. In 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.
Tag Recommendations in Folksonomies.
In: J. N. Kok, J. Koronacki, R. L. de Mántaras, S. Matwin, D. Mladenic und A. Skowron
(Herausgeber):
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Band 4702, Reihe Lecture Notes in Computer Science, Seiten 506-514.
Springer, Berlin, Heidelberg, 2007.
Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme und Gerd Stumme.
[doi]
[Kurzfassung]
[BibTeX]
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. In 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.