1. A computing device for detecting events based on query-page relationships, comprising: 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; a generate dual graph component that generates 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; an identify semantic cluster component that identifies clusters of vertices of the dual graph, each cluster having vertices whose query-page pairs are semantically similar; and an identify time pattern cluster component that identifies 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 wherein the components are implemented as instructions stored in memory of the computing device for execution by a processor of the computing device.
1. A computing device for detecting events based on query-page relationships, comprising: 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; a generate dual graph component that generates 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; an identify semantic cluster component that identifies clusters of vertices of the dual graph, each cluster having vertices whose query-page pairs are semantically similar; and an identify time pattern cluster component that identifies 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 wherein the components are implemented as instructions stored in memory of the computing device for execution by a processor of the computing device. 2. The computing device of claim 1 including: a generate time period bipartite graphs component that generates a time period graph for each time period; and a generate time period vector bipartite graph component that generates a time period vector graph from the generated time period bipartite graphs, wherein the generate dual graph component generates the dual graph from the time period vector bipartite graph.