%0 Journal Article %1 Zeng2009 %A Zeng, Daniel %A Li, Huiqian %D 2009 %J Intelligence and Security Informatics %K recommendation tagging %P 320--330 %T How Useful Are Tags? — An Empirical Analysis of Collaborative Tagging for Web Page Recommendation %U http://dx.doi.org/10.1007/978-3-540-69304-8_32 %X As a representative Web 2.0 application, collaborative tagging has been widely adopted and inspires significant interest from academies. Roughly, two lines of research have been pursued: (a) studying the structure of tags, and (b) using tag to promoteWeb search. However, both of them remain preliminary. Research reported in this paper is aimed at addressing some of theseresearch gaps. First, we apply complex network theory to analyze various structural properties of collaborative tagging activitiesto gain a detailed understanding of user tagging behavior and also try to capture the mechanism that can help explain suchtagging behavior. Second, we conduct a preliminary computational study to utilize tagging information to help improve thequality of Web page recommendation. The results indicate that under the user-based recommendation framework, tags can be fruitfullyexploited as they facilitate better user similarity calculation and help reduce sparsity related to past user-Web page interactions.

@article{Zeng2009, abstract = {As a representative Web 2.0 application, collaborative tagging has been widely adopted and inspires significant interest from academies. Roughly, two lines of research have been pursued: (a) studying the structure of tags, and (b) using tag to promoteWeb search. However, both of them remain preliminary. Research reported in this paper is aimed at addressing some of theseresearch gaps. First, we apply complex network theory to analyze various structural properties of collaborative tagging activitiesto gain a detailed understanding of user tagging behavior and also try to capture the mechanism that can help explain suchtagging behavior. Second, we conduct a preliminary computational study to utilize tagging information to help improve thequality of Web page recommendation. The results indicate that under the user-based recommendation framework, tags can be fruitfullyexploited as they facilitate better user similarity calculation and help reduce sparsity related to past user-Web page interactions.}, added-at = {2009-11-13T10:45:40.000+0100}, author = {Zeng, Daniel and Li, Huiqian}, biburl = {https://www.bibsonomy.org/bibtex/2eab24a2805ad88f155f24bf3f53248e7/chriskoerner}, description = {SpringerLink - Book Chapter}, interhash = {1ede79adecab4b214f789d9002baaa3b}, intrahash = {eab24a2805ad88f155f24bf3f53248e7}, journal = {Intelligence and Security Informatics}, keywords = {recommendation tagging}, pages = {320--330}, timestamp = {2009-11-13T10:45:40.000+0100}, title = {How Useful Are Tags? — An Empirical Analysis of Collaborative Tagging for Web Page Recommendation}, url = {http://dx.doi.org/10.1007/978-3-540-69304-8_32}, year = 2009 }