11. An apparatus for automatically determining any of importance of an on-line asset and expertise that one or more members of an online community possess, without asking said community members directly, comprising: means for observing usage by a community of peers and experts who show high affinity in connection with online assets; a processor for employing automatic techniques to extract patterns from said usage; said processor comprising a module for identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; said processor comprising a module for refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; said processor comprising a module for assigning to each said online asset a document impact factor score for each possible topic/term, said document impact factor representing the importance of each said online asset to each topic; said processor comprising a module for assigning to each user an expert impact factor which is determined by aggregating identified topics of online assets each user has found useful, weighted by the document impact factor and by document rareness, wherein said expert impact factor and other observed patterns of behavior define a user's identified expertise; said processor comprising a module for using said identified expertise of each user to identify a community of experts given a specific topic/term of interest expressed by a user, and to identify a community of peers for a given user based upon a relationship between a target user's identified expertise and all other users; and said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail; assets viewed and position in user trail; dwell, range, scrolling, think time, and mouse movement on an asset; anchors and lines used in asset text; virtual bookmarks and virtual printing; and explicit downloading, emailing, printing, saving, and removing.
11. An apparatus for automatically determining any of importance of an on-line asset and expertise that one or more members of an online community possess, without asking said community members directly, comprising: means for observing usage by a community of peers and experts who show high affinity in connection with online assets; a processor for employing automatic techniques to extract patterns from said usage; said processor comprising a module for identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; said processor comprising a module for refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; said processor comprising a module for assigning to each said online asset a document impact factor score for each possible topic/term, said document impact factor representing the importance of each said online asset to each topic; said processor comprising a module for assigning to each user an expert impact factor which is determined by aggregating identified topics of online assets each user has found useful, weighted by the document impact factor and by document rareness, wherein said expert impact factor and other observed patterns of behavior define a user's identified expertise; said processor comprising a module for using said identified expertise of each user to identify a community of experts given a specific topic/term of interest expressed by a user, and to identify a community of peers for a given user based upon a relationship between a target user's identified expertise and all other users; and said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail; assets viewed and position in user trail; dwell, range, scrolling, think time, and mouse movement on an asset; anchors and lines used in asset text; virtual bookmarks and virtual printing; and explicit downloading, emailing, printing, saving, and removing. 18. The apparatus of claim 11 , further comprising: said processor identifying communities comprising any of peer groups and expert groups based on an information context; wherein communities are nested and defined by different levels of contexts.