10. A method, comprising: computing, by a processor, a plurality of sets of candidate tags for a document in accordance with different factors by extracting at least one keyword from the document, and associating an importance score with each keyword, wherein each keyword is a candidate tag, wherein the plurality of sets of candidate tags include a set of candidate tags based on document-specific factors including keywords in the document, a set of candidate tags based on collaborative factors including tags that other users have applied to the document, a set of candidate tags based on personalized factors including information about a user and a set of candidate tags based on tag co-occurrences factors including tads that are often applied together with certain keywords; combining the plurality of sets of candidate tags from different factors into an overall recommendation list of candidate tags; returning at least one suggested tag from the overall recommendation list of candidate tags; recording at least one applied tag that is applied to the document by a user of a computer system; and adjusting the overall recommendation list of candidate tagsbased on the at least one applied tag.
10. A method, comprising: computing, by a processor, a plurality of sets of candidate tags for a document in accordance with different factors by extracting at least one keyword from the document, and associating an importance score with each keyword, wherein each keyword is a candidate tag, wherein the plurality of sets of candidate tags include a set of candidate tags based on document-specific factors including keywords in the document, a set of candidate tags based on collaborative factors including tags that other users have applied to the document, a set of candidate tags based on personalized factors including information about a user and a set of candidate tags based on tag co-occurrences factors including tads that are often applied together with certain keywords; combining the plurality of sets of candidate tags from different factors into an overall recommendation list of candidate tags; returning at least one suggested tag from the overall recommendation list of candidate tags; recording at least one applied tag that is applied to the document by a user of a computer system; and adjusting the overall recommendation list of candidate tagsbased on the at least one applied tag. 13. The method of claim 10 , wherein the online social system is selected from the group consisting of: blogging; people tagging; social bookmarking; and mini blogging.