GiveALink: mining a semantic network of bookmarks for web search and recommendation Export

@inproceedings{citeulike:1127617, abstract = {GiveALink is a public site where users donate their bookmarks to the Web community. Bookmarks are analyzed to build a new generation of Web mining techniques and new ways to search, recommend, surf, personalize and visualize the Web. We present a semantic similarity measure for URLs that takes advantage both of the hierarchical structure of the bookmark files of individual users, and of collaborative filtering across users. We analyze the social bookmark network induced by the similarity measure. A search and recommendation system is built from a number of ranking algorithms based on prestige, generality, and novelty measures extracted from the similarity data.}, address = {New York, NY, USA}, author = {Stoilova, Lubomira and Holloway, Todd and Markines, Ben and Maguitman, Ana G. and Menczer, Filippo}, booktitle = {LinkKDD '05: Proceedings of the 3rd international workshop on Link discovery}, citeulike-article-id = {1127617}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1134271.1134281}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1134271.1134281}, doi = {10.1145/1134271.1134281}, isbn = {1-59593-215-1}, keywords = {isi, ls, semantic}, location = {Chicago, Illinois}, pages = {66--73}, posted-at = {2009-11-12 20:56:07}, priority = {2}, publisher = {ACM}, title = {GiveALink: mining a semantic network of bookmarks for web search and recommendation}, url = {http://dx.doi.org/10.1145/1134271.1134281}, year = {2005} }

TY - CONF ID - citeulike:1127617 L3 - citeulike-article-id:1127617 N2 - GiveALink is a public site where users donate their bookmarks to the Web community. Bookmarks are analyzed to build a new generation of Web mining techniques and new ways to search, recommend, surf, personalize and visualize the Web. We present a semantic similarity measure for URLs that takes advantage both of the hierarchical structure of the bookmark files of individual users, and of collaborative filtering across users. We analyze the social bookmark network induced by the similarity measure. A search and recommendation system is built from a number of ranking algorithms based on prestige, generality, and novelty measures extracted from the similarity data. CY - Chicago, Illinois SN - 1-59593-215-1 AD - New York, NY, USA EP - 73 TI - GiveALink: mining a semantic network of bookmarks for web search and recommendation PB - ACM T2 - LinkKDD '05: Proceedings of the 3rd international workshop on Link discovery SP - 66 KW - isi KW - ls KW - semantic AU - Stoilova, Lubomira AU - Holloway, Todd AU - Markines, Ben AU - Maguitman, Ana AU - Menczer, Filippo PY - 2005/// UR - http://dx.doi.org/10.1145/1134271.1134281 ER -