X. Si, Z. Liu, P. Li, Q. Jiang, and M. Sun. ECML PKDD Discovery Challenge 2009 (DC09), 497, page 243--260. Bled, Slovenia, CEUR Workshop Proceedings, (September 2009)
Abstract
Social tagging is a popular and convenient way to organize information. Automatic tag suggestion can ease the user’s tagging activity. In this paper, we exam both content-based and graph-based methods for tag suggestion using the BibSonomy dataset, and describe our methods for ECML/PKDD Discovery Challenge 2009 submissions . In content-based tag suggestion, we propose a fast yet accurate method named Feature-Driven Tagging. In graph-based tag suggestion, we apply DiffusionRank to solve the problem, and get a better result than current state-of-the-art methods in cross-validation.
%0 Conference Paper
%1 marinho:ecml2009
%A Si, Xiance
%A Liu, Zhiyuan
%A Li, Peng
%A Jiang, Qixia
%A Sun, Maosong
%B ECML PKDD Discovery Challenge 2009 (DC09)
%C Bled, Slovenia
%D 2009
%E Eisterlehner, Folke
%E Hotho, Andreas
%E Jäschke, Robert
%I CEUR Workshop Proceedings
%K 2009 ECML09 _todo content graph recommendation tagging
%P 243--260
%T Content-based and Graph-based Tag Suggestion
%U http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-497/
%V 497
%X Social tagging is a popular and convenient way to organize information. Automatic tag suggestion can ease the user’s tagging activity. In this paper, we exam both content-based and graph-based methods for tag suggestion using the BibSonomy dataset, and describe our methods for ECML/PKDD Discovery Challenge 2009 submissions . In content-based tag suggestion, we propose a fast yet accurate method named Feature-Driven Tagging. In graph-based tag suggestion, we apply DiffusionRank to solve the problem, and get a better result than current state-of-the-art methods in cross-validation.
@inproceedings{marinho:ecml2009,
abstract = {Social tagging is a popular and convenient way to organize information. Automatic tag suggestion can ease the user’s tagging activity. In this paper, we exam both content-based and graph-based methods for tag suggestion using the BibSonomy dataset, and describe our methods for ECML/PKDD Discovery Challenge 2009 submissions . In content-based tag suggestion, we propose a fast yet accurate method named Feature-Driven Tagging. In graph-based tag suggestion, we apply DiffusionRank to solve the problem, and get a better result than current state-of-the-art methods in cross-validation.},
added-at = {2010-01-29T16:57:33.000+0100},
address = {Bled, Slovenia},
author = {Si, Xiance and Liu, Zhiyuan and Li, Peng and Jiang, Qixia and Sun, Maosong},
biburl = {https://www.bibsonomy.org/bibtex/2b63d4fcfea0483690875214f229ca3ac/trude},
booktitle = {ECML PKDD Discovery Challenge 2009 (DC09)},
editor = {Eisterlehner, Folke and Hotho, Andreas and Jäschke, Robert},
interhash = {060d0b9532600a70bccbabd8628f64a9},
intrahash = {b63d4fcfea0483690875214f229ca3ac},
issn = {1613-0073},
keywords = {2009 ECML09 _todo content graph recommendation tagging},
month = {September},
pages = {243--260},
publisher = {CEUR Workshop Proceedings},
timestamp = {2010-01-29T16:57:33.000+0100},
title = {Content-based and Graph-based Tag Suggestion},
url = {http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-497/},
volume = 497,
year = 2009
}