TY - CONF AU - Byde, Andrew AU - Wan, Hui AU - Cayzer, Steve A2 - T1 - Personalized Tag Recommendations via Tagging and Content-based Similarity Metrics T2 - Proceedings of the International Conference on Weblogs and Social

Media PB - CY - PY - 2007/03 M2 - VL - IS - SP - EP - UR - http://www.icwsm.org/papers/paper47.html M3 - KW - tagging KW - similarity KW - recommender KW - tag KW - content L1 - SN - N1 - N1 - AB - This short paper describes a novel technique for generating personalized

tag recommendations for users of social book- marking sites such

as del.icio.us. Existing techniques recom- mend tags on the basis

of their popularity among the group of all users; on the basis of

recent use; or on the basis of simple heuristics to extract keywords

from the url being tagged. Our method is designed to complement these

approaches, and is based on recommending tags from urls that are

similar to the one in question, according to two distinct similarity

metrics, whose principal utility covers complementary cases. ER - TY - CONF AU - Byde, Andrew AU - Wan, Hui AU - Cayzer, Steve A2 - T1 - Personalized Tag Recommendations via Tagging and Content-based Similarity Metrics T2 - Proceedings of the International Conference on Weblogs and Social Media PB - CY - PY - 2007/03 M2 - VL - IS - SP - EP - UR - http://www.icwsm.org/papers/paper47.html M3 - KW - tagging KW - taggingsurvey KW - recommender KW - collaborative KW - social KW - filtering KW - bookmarking KW - toread L1 - SN - N1 - N1 - AB - This short paper describes a novel technique for generating personalized tag recommendations for users of social book- marking sites such as del.icio.us. Existing techniques recom- mend tags on the basis of their popularity among the group of all users; on the basis of recent use; or on the basis of simple heuristics to extract keywords from the url being tagged. Our method is designed to complement these approaches, and is based on recommending tags from urls that are similar to the one in question, according to two distinct similarity metrics, whose principal utility covers complementary cases. ER - TY - CONF AU - Michlmayr, Elke AU - Cayzer, Steve A2 - T1 - Learning User Profiles from Tagging Data and Leveraging them for Personal(ized) Information Access T2 - Tagging and Metadata for Social Information Organization Workshop, WWW07 PB - CY - PY - 2007/ M2 - VL - IS - SP - EP - UR - M3 - KW - tagging KW - taggingsurvey KW - profile KW - folksonomy KW - user KW - toread L1 - SN - N1 - N1 - AB - ER -