Described is a behavioral targeting technology for online advertising, by which an original attribute is uniformly expanded. Users that meet an original attribute are aggregated into a mid-result used to determine similarity relative to candidate attribute types. The most similar candidate attributes are selected for the expanded attribute. A URL/URL pattern suggestion technology is provided, with similarity computed from users/URLs visited by the users. URLs are separated into URL tree nodes, for calculating the number of users who have visited each URL and the number of users who have visited the URL on a sub-tree whose root is the node. URL/URL patterns are output based on similarity. Domains are also suggested based on user-visits. Similarities between pairs of domains may be computed (e.g., offline), with an output for a given domain provided in based on its similarity with each other domain.