1. A method for determining a semantic relationship between two search engine queries, comprising the steps of: (a) receiving a first search engine query; (b) identifying a second search engine query stored in memory; (c) determining a cumulative density of the first and second search engine queries over a plurality of time periods, wherein the density of each of the two search engine queries during a given time period is the frequency of each of the search engine queries in comparison to the combined number of search engine queries during that time period, the cumulative density for the first and second search engine queries being the density of the first and second search engine queries over all time periods in the plurality of time periods; (d) identifying a semantic correlation between the two search engine queries based on the density of the two search engine queries determined in said step (a), wherein identifying a semantic correlation between the two queries comprises the step of representing the data of the two search engine query frequencies by a bit string, and examining a degree to which corresponding bits in the bit strings representing the two search engine query frequencies match each other; (e) modifying the second search engine query to include a linking association in memory with the first search engine query in the event it is determined that the semantic correlation identified in said step (d) is above a threshold level; and (f) displaying results associated with the second search engine query to the user in the event it is determined that the semantic correlation identified in said step (d) is above a threshold level.
1. A method for determining a semantic relationship between two search engine queries, comprising the steps of: (a) receiving a first search engine query; (b) identifying a second search engine query stored in memory; (c) determining a cumulative density of the first and second search engine queries over a plurality of time periods, wherein the density of each of the two search engine queries during a given time period is the frequency of each of the search engine queries in comparison to the combined number of search engine queries during that time period, the cumulative density for the first and second search engine queries being the density of the first and second search engine queries over all time periods in the plurality of time periods; (d) identifying a semantic correlation between the two search engine queries based on the density of the two search engine queries determined in said step (a), wherein identifying a semantic correlation between the two queries comprises the step of representing the data of the two search engine query frequencies by a bit string, and examining a degree to which corresponding bits in the bit strings representing the two search engine query frequencies match each other; (e) modifying the second search engine query to include a linking association in memory with the first search engine query in the event it is determined that the semantic correlation identified in said step (d) is above a threshold level; and (f) displaying results associated with the second search engine query to the user in the event it is determined that the semantic correlation identified in said step (d) is above a threshold level. 2. The method for determining a semantic relationship between two search engine queries as recited in claim 1 , wherein a first query of the two search engine queries is an input query, and a second query of the two search engine queries is a stored query, the method further comprising the step of suggesting the stored query to a user or advertiser where it is determined that a semantic relationship above a threshold level exists between the input query and the stored query.