TY - CONF AU - Xu, Z. AU - Fu, Y. AU - Mao, J. AU - Su, D. A2 - T1 - Towards the semantic web: Collaborative tag suggestions T2 - Proceedings of the Collaborative Web Tagging Workshop at the WWW 2006 PB - C1 - Edinburgh, Scotland PY - 2006/05 CY - VL - IS - SP - EP - UR - http://www.ibiblio.org/www_tagging/2006/13.pdf DO - KW - tagging KW - recommender KW - tag L1 - SN - N1 - N1 - AB - Content organization over the Internet went through several

interesting phases of evolution: from structured directories to

unstructured Web search engines and more recently, to tagging

as a way for aggregating information, a step towards the

semantic web vision. Tagging allows ranking and data

organization to directly utilize inputs from end users, enabling

machine processing of Web content. Since tags are created by

individual users in a free form, one important problem facing

tagging is to identify most appropriate tags, while eliminating

noise and spam. For this purpose, we define a set of general

criteria for a good tagging system. These criteria include high

coverage of multiple facets to ensure good recall, least effort to

reduce the cost involved in browsing, and high popularity to

ensure tag quality. We propose a collaborative tag suggestion

algorithm using these criteria to spot high-quality tags. The

proposed algorithm employs a goodness measure for tags derived

from collective user authorities to combat spam. The goodness

measure is iteratively adjusted by a reward-penalty algorithm,

which also incorporates other sources of tags, e.g., content-based

auto-generated tags. Our experiments based on My Web 2.0 show

that the algorithm is effective. ER -