BibSonomyburst/bibtex/440fafda1eccf4036066f457eb6674a0BibSonomy RSS feed for /bibtex/440fafda1eccf4036066f457eb6674a02012-02-17T07:03:53+01:00http://www.bibsonomy.org/bibtex/221fdf612ba6b356fb1b311fc9369f32d/jaeschkejaeschke2011-01-27T11:58:48+01:002009 bibsonomy conference framework myown recommender recsys <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>RecSys &#039;09: Proceedings of the third ACM Conference on Recommender Systems, </em><em>page 369--372. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2009</em>)Thu Jan 27 11:58:48 CET 2011New York, NY, USARecSys '09: Proceedings of the third ACM Conference on Recommender Systems369--372Testing and Evaluating Tag Recommenders in a Live System20092009 bibsonomy conference framework myown recommender recsys 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.http://www.bibsonomy.org/bibtex/25e8f40e610e723e966676772aa205f80/philonousphilonous2010-10-13T12:15:25+02:002009 bibsonomy folksonomy recommender tagging <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Workshop on Knowledge Discovery, Data Mining, and Machine Learning, </em><em>page 44--51. </em>(<em>September 2009</em>)Wed Oct 13 12:15:25 CEST 2010Workshop on Knowledge Discovery, Data Mining, and Machine Learningsep44--51Testing and Evaluating Tag Recommenders in a Live System20092009 bibsonomy folksonomy recommender tagging The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on 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 an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework.http://www.bibsonomy.org/bibtex/25e8f40e610e723e966676772aa205f80/folkefolke2010-08-10T07:06:15+02:002009 bibsonomy folksonomy framework myown recommender tagging <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Workshop on Knowledge Discovery, Data Mining, and Machine Learning, </em><em>page 44 --51. </em>(<em>September 2009</em>)Tue Aug 10 07:06:15 CEST 2010Workshop on Knowledge Discovery, Data Mining, and Machine Learningsep44 --51Testing and Evaluating Tag Recommenders in a Live System20092009 bibsonomy folksonomy framework myown recommender tagging The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on evaluation anddevelopment 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 an evaluation of two exemplarily deployed recommendation methods, demonstratingthe power of the framework.http://www.bibsonomy.org/bibtex/25e8f40e610e723e966676772aa205f80/ansans2010-05-03T09:49:14+02:00evaluation folksonomy master recommender tags toVerify <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Workshop on Knowledge Discovery, Data Mining, and Machine Learning, </em><em>page 44 --51. </em>(<em>September 2009</em>)Mon May 03 09:49:14 CEST 2010Workshop on Knowledge Discovery, Data Mining, and Machine Learningsep44 --51Testing and Evaluating Tag Recommenders in a Live System2009evaluation folksonomy master recommender tags toVerify The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on evaluation anddevelopment 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 an evaluation of two exemplarily deployed recommendation methods, demonstratingthe power of the framework.http://www.bibsonomy.org/bibtex/25e8f40e610e723e966676772aa205f80/macekmacek2010-03-19T13:32:16+01:00Evaluation Folksonomy Prediction Recommender Tests Web2.0 <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Workshop on Knowledge Discovery, Data Mining, and Machine Learning, </em><em>page 44 --51. </em>(<em>September 2009</em>)Fri Mar 19 13:32:16 CET 2010Workshop on Knowledge Discovery, Data Mining, and Machine Learningsep44 --51Testing and Evaluating Tag Recommenders in a Live System2009Evaluation Folksonomy Prediction Recommender Tests Web2.0 The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on evaluation anddevelopment 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 an evaluation of two exemplarily deployed recommendation methods, demonstratingthe power of the framework.http://www.bibsonomy.org/bibtex/25e8f40e610e723e966676772aa205f80/jaeschkejaeschke2009-12-10T16:56:57+01:002009 bibsonomy folksonomy framework myown recommender tagging <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Workshop on Knowledge Discovery, Data Mining, and Machine Learning, </em><em>page 44--51. </em>(<em>September 2009</em>)Thu Dec 10 16:56:57 CET 2009Workshop on Knowledge Discovery, Data Mining, and Machine Learningsep44--51Testing and Evaluating Tag Recommenders in a Live System20092009 bibsonomy folksonomy framework myown recommender tagging The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on 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 an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework.http://www.bibsonomy.org/bibtex/29369050b66240099df80f0aa37040f74/dblpdblp2009-10-28T00:00:00+01:00dblp <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>RecSys, </em><em>page 369-372. </em><em>ACM, </em>(<em>2009</em>)Wed Oct 28 00:00:00 CET 2009RecSysconf/recsys/2009369-372Testing and evaluating tag recommenders in a live system.2009dblp dblphttp://www.bibsonomy.org/bibtex/25e8f40e610e723e966676772aa205f80/hothohotho2009-10-25T13:32:08+01:002009 bibsonomy folksonomy framework myown recommender tagging taggingsurvey <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Workshop on Knowledge Discovery, Data Mining, and Machine Learning, </em><em>page 44 --51. </em>(<em>September 2009</em>)Sun Oct 25 13:32:08 CET 2009Workshop on Knowledge Discovery, Data Mining, and Machine Learningsep44 --51Testing and Evaluating Tag Recommenders in a Live System20092009 bibsonomy folksonomy framework myown recommender tagging taggingsurvey The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on 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 an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework.http://www.bibsonomy.org/bibtex/21320904b208d53bd5d49e751cbfcc268/kasimirokasimiro2009-10-12T14:27:34+02:00bibsonomy evaluation recommendation tag tool <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>RecSys &#039;09: Proceedings of the 2009 ACM Conference on Recommender Systems, </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2009</em>)<em>to appear . </em>Mon Oct 12 14:27:34 CEST 2009New York, NY, USARecSys '09: Proceedings of the 2009 ACM Conference on Recommender Systems(to appear)Testing and Evaluating Tag Recommenders in a Live System2009bibsonomy evaluation recommendation tag tool 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.http://www.bibsonomy.org/bibtex/25e8f40e610e723e966676772aa205f80/stummestumme2009-09-25T21:59:24+02:002009 bibsonomy ecml l3s myown pkdd recommender tagging <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>Workshop on Knowledge Discovery, Data Mining, and Machine Learning, </em><em>page 44 --51. </em>(<em>September 2009</em>)Fri Sep 25 21:59:24 CEST 2009Workshop on Knowledge Discovery, Data Mining, and Machine Learningsep44 --51Testing and Evaluating Tag Recommenders in a Live System20092009 bibsonomy ecml l3s myown pkdd recommender tagging The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on 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 an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework.http://www.bibsonomy.org/bibtex/21320904b208d53bd5d49e751cbfcc268/sdosdo2009-09-04T16:47:44+02:002009 BibSonomy conference folksonomy framework recommender <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>RecSys &#039;09: Proceedings of the 2009 ACM Conference on Recommender Systems, </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2009</em>)<em>to appear . </em>Fri Sep 04 16:47:44 CEST 2009New York, NY, USARecSys '09: Proceedings of the 2009 ACM Conference on Recommender Systems(to appear)Testing and Evaluating Tag Recommenders in a Live System20092009 BibSonomy conference folksonomy framework recommender 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.tag-recommender für acm09http://www.bibsonomy.org/bibtex/21320904b208d53bd5d49e751cbfcc268/toboldtobold2009-08-27T14:51:29+02:00evaluation recommender tagging <span class="authorEditorList"><a href="/author/Jäschke">Robert Jäschke</a>, <a href="/author/Eisterlehner">Folke Eisterlehner</a>, <a href="/author/Hotho">Andreas Hotho</a>, and <a href="/author/Stumme">Gerd Stumme</a> </span><em>RecSys &#039;09: Proceedings of the 2009 ACM Conference on Recommender Systems, </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2009</em>)<em>to appear . </em>Thu Aug 27 14:51:29 CEST 2009New York, NY, USARecSys '09: Proceedings of the 2009 ACM Conference on Recommender Systems(to appear)Testing and Evaluating Tag Recommenders in a Live System2009evaluation recommender tagging 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.