The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on the evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance.
In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents a rst evaluation of two exemplarily deployed recommendation methods.
%0 Conference Paper
%1 jaeschke2009testing
%A Jäschke, Robert
%A Eisterlehner, Folke
%A Hotho, Andreas
%A Stumme, Gerd
%B Workshop on Knowledge Discovery, Data Mining, and Machine Learning
%D 2009
%E Benz, Dominik
%E Janssen, Frederik
%K bibsonomy folksonomy recommender socialtagging tagging
%P 44-51
%T Testing and Evaluating Tag Recommenders in a Live System
%U http://www.kde.cs.uni-kassel.de/pub/pdf/jaeschke2009testing.pdf
%X The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on the evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance.
In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents a rst evaluation of two exemplarily deployed recommendation methods.
@inproceedings{jaeschke2009testing,
abstract = {The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on the evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance.
In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents a rst evaluation of two exemplarily deployed recommendation methods.},
added-at = {2020-09-29T13:37:19.000+0200},
author = {Jäschke, Robert and Eisterlehner, Folke and Hotho, Andreas and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/25e8f40e610e723e966676772aa205f80/seboettg},
booktitle = {Workshop on Knowledge Discovery, Data Mining, and Machine Learning},
editor = {Benz, Dominik and Janssen, Frederik},
file = {:13_Recommender.pdf:PDF},
interhash = {440fafda1eccf4036066f457eb6674a0},
intrahash = {5e8f40e610e723e966676772aa205f80},
keywords = {bibsonomy folksonomy recommender socialtagging tagging},
month = {9},
pages = {44-51},
timestamp = {2020-09-29T13:37:19.000+0200},
title = {Testing and Evaluating Tag Recommenders in a Live System},
url = {http://www.kde.cs.uni-kassel.de/pub/pdf/jaeschke2009testing.pdf},
year = 2009
}