Abstract: An approach is provided for a holistic framework to model user item rating with user generated tag information. A tagging manager determines one or more tags associated with one or more items, wherein the one or more tags are generated by one or more users. The tagging manager processes and/or facilitates a processing of the one or more tags to cause, at least in part, a generation of one or more semantic spaces. The one or more semantic spaces and/or one or more semantic concepts within the one or more semantic spaces represent one or more groupings of the one or more tags. The tagging manager determines one or more probability parameters that the one or more tags, the one or more users, the one or more items, or a combination thereof are associated with respective ones of the one or more semantic concepts in the semantic spaces.

Abstract: Various methods for modeling personalized contexts are provided. One example method includes accessing a context data set comprised of a plurality of context records. The context records may include a number of contextual feature-value pairs. The example method may also include generating at least one grouping of contextual feature-value pairs based on a co-occurrence of the contextual feature-value pairs in context records, and defining at least one user context based on the at least one grouping of contextual feature-value pairs. Similar and related example methods and example apparatuses are also provided.