Towards effective browsing of large scale social annotations Export

@inproceedings{citeulike:1705692, abstract = {This paper is concerned with the problem of browsing social annotations. Today, a lot of services (e.g., Del.icio.us, Filckr) have been provided for helping users to manage and share their favorite URLs and photos based on social annotations. Due to the exponential increasing of the social annotations, more and more users, however, are facing the problem how to effectively find desired resources from large annotation data. Existing methods such as tag cloud and annotation matching work well only on small annotation sets. Thus, an effective approach for browsing large scale annotation sets and the associated resources is in great demand by both ordinary users and service providers. In this paper, we propose a novel algorithm, namely Effective Large Scale Annotation Browser (ELSABer), to browse large-scale social annotation data. ELSABer helps the users browse huge number of annotations in a semantic, hierarchical and efficient way. More specifically, ELSABer has the following features: 1) the semantic relations between annotations are explored for browsing of similar resources; 2) the hierarchical relations between annotations are constructed for browsing in a top-down fashion; 3) the distribution of social annotations is studied for efficient browsing. By incorporating the personal and time information, ELSABer can be further extended for personalized and time-related browsing. A prototype system is implemented and shows promising results.}, address = {New York, NY, USA}, author = {Li, Rui and Bao, Shenghua and Yu, Yong and Fei, Ben and Su, Zhong}, booktitle = {WWW '07: Proceedings of the 16th international conference on World Wide Web}, citeulike-article-id = {1705692}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1242572.1242700}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1242572.1242700}, doi = {10.1145/1242572.1242700}, isbn = {9781595936547}, keywords = {clustering, delicious, folksonomy, hierachy, navigation, sbm, tagging}, pages = {943--952}, posted-at = {2009-07-27 21:46:44}, priority = {2}, publisher = {ACM Press}, title = {Towards effective browsing of large scale social annotations}, url = {http://dx.doi.org/10.1145/1242572.1242700}, year = {2007} }

TY - CONF ID - citeulike:1705692 L3 - citeulike-article-id:1705692 N2 - This paper is concerned with the problem of browsing social annotations. Today, a lot of services (e.g., Del.icio.us, Filckr) have been provided for helping users to manage and share their favorite URLs and photos based on social annotations. Due to the exponential increasing of the social annotations, more and more users, however, are facing the problem how to effectively find desired resources from large annotation data. Existing methods such as tag cloud and annotation matching work well only on small annotation sets. Thus, an effective approach for browsing large scale annotation sets and the associated resources is in great demand by both ordinary users and service providers. In this paper, we propose a novel algorithm, namely Effective Large Scale Annotation Browser (ELSABer), to browse large-scale social annotation data. ELSABer helps the users browse huge number of annotations in a semantic, hierarchical and efficient way. More specifically, ELSABer has the following features: 1) the semantic relations between annotations are explored for browsing of similar resources; 2) the hierarchical relations between annotations are constructed for browsing in a top-down fashion; 3) the distribution of social annotations is studied for efficient browsing. By incorporating the personal and time information, ELSABer can be further extended for personalized and time-related browsing. A prototype system is implemented and shows promising results. SN - 9781595936547 AD - New York, NY, USA EP - 952 TI - Towards effective browsing of large scale social annotations PB - ACM Press T2 - WWW '07: Proceedings of the 16th international conference on World Wide Web SP - 943 KW - clustering KW - delicious KW - folksonomy KW - hierachy KW - navigation KW - sbm KW - tagging AU - Li, Rui AU - Bao, Shenghua AU - Yu, Yong AU - Fei, Ben AU - Su, Zhong PY - 2007/// UR - http://dx.doi.org/10.1145/1242572.1242700 ER -