6. A computer-readable storage medium containing computer-executable instructions for controlling a computing device to detect events based on query-page relationships, by a method comprising: providing a query-page store identifying occurrences of query-page pairs, each occurrence of a query-page pair indicating that a user selected that page from a search result for that query, each occurrence of a query-page pair having a time associated with the user selection; generating a dual graph having vertices corresponding to distinct query-page pairs of the query-page store and edges between vertices that have a common query or a common page, each vertex having a time period vector with an element for each time period, each element having a value derived from occurrences of the query-page pair of the vertex with a time within the time period; identifying clusters of vertices of the dual graph, each cluster having vertices whose query-page pairs are semantically similar; and identifying time pattern clusters of a semantic cluster, a time pattern cluster having vertices representing semantically related query-page pairs that have similar patterns of associated times, wherein an identified time pattern cluster represents an event relating to the query-page pairs of the vertices within the identified time pattern cluster, and wherein query-page pairs are semantically similar based on the following: S S ⁡ ( a , b ) = C  N ⁡ ( a ) ⁢   ⁢ N ⁡ ( b )  ⁢ ∑ i = 1  N ⁡ ( a ) ⁢ ⁢ ∑ j = 1  N ⁡ ( b )  ⁢ ⁢ S S ⁡ ( N i ⁡ ( a ) , N j ⁡ ( b ) ) where S s (a, b) represents the semantic similarity between vertex a and vertex b, N(k) represents the neighboring vertices of vertex k, N i (k) represents the i th neighbor vertex of vertex k, and C represents a decay factor between 0 and 1 that indicates the contribution of the neighbors to the similarity of a pair of vertices.
6. A computer-readable storage medium containing computer-executable instructions for controlling a computing device to detect events based on query-page relationships, by a method comprising: providing a query-page store identifying occurrences of query-page pairs, each occurrence of a query-page pair indicating that a user selected that page from a search result for that query, each occurrence of a query-page pair having a time associated with the user selection; generating a dual graph having vertices corresponding to distinct query-page pairs of the query-page store and edges between vertices that have a common query or a common page, each vertex having a time period vector with an element for each time period, each element having a value derived from occurrences of the query-page pair of the vertex with a time within the time period; identifying clusters of vertices of the dual graph, each cluster having vertices whose query-page pairs are semantically similar; and identifying time pattern clusters of a semantic cluster, a time pattern cluster having vertices representing semantically related query-page pairs that have similar patterns of associated times, wherein an identified time pattern cluster represents an event relating to the query-page pairs of the vertices within the identified time pattern cluster, and wherein query-page pairs are semantically similar based on the following: S S ⁡ ( a , b ) = C  N ⁡ ( a ) ⁢   ⁢ N ⁡ ( b )  ⁢ ∑ i = 1  N ⁡ ( a ) ⁢ ⁢ ∑ j = 1  N ⁡ ( b )  ⁢ ⁢ S S ⁡ ( N i ⁡ ( a ) , N j ⁡ ( b ) ) where S s (a, b) represents the semantic similarity between vertex a and vertex b, N(k) represents the neighboring vertices of vertex k, N i (k) represents the i th neighbor vertex of vertex k, and C represents a decay factor between 0 and 1 that indicates the contribution of the neighbors to the similarity of a pair of vertices. 9. The computer-readable storage medium of claim 6 wherein the semantic similarity between query-page pairs is based on similarity between neighbors of the query page pairs.