System and method for query temporality analysis

A method, comprising:

• using one or more processors to accept a query from a user as part of a search request;
• using one or more processors to retrieve a plurality of objects that match the query;
• using one or more processors to determine distribution over time of the objects matching the query for a temporality analysis of the query;
• using one or more processors to analyze the distribution over time of the objects to provide a classification of the query;
• the one or more processors generating a search result including the objects matching the query and the classification of the query;
• using one or more processors to select a preferred time window from a set of time windows based on the time distribution of the objects matching the query, the selecting of the preferred time window based on at least a comparison of an actual number of objects matching the query within the time window and an expected number of the objects matching the query within a time window for each time window in the set of time windows and the expected number of objects for this time window is based on a ratio of a number of objects matching the query and a length of the time window, wherein the preferred time window is a time interval that encompasses at least some timestamps associated with the objects;
• using one or more processors to determine a temporality of the query to generate a search result of a list of objects that are based on objects matching the query and the classification of the query within the preferred time window based on timestamp metadata of the objects matching the query;
• and
• the one or more processors ranking the list of objects.

A non-transitory machine readable medium having software instructions stored thereon that when executed cause a system to:

• accept a query from a user as part of a search request;
• retrieve a plurality of objects that match the query;
• determine a distribution over time of the objects matching the query for temporality analysis of the query;
• analyze the distribution over time of the objects to provide a classification of the query;
• generate a search result including the objects that are not only based on matching of the objects to the query but also based on the classification of the query;
• select a preferred time window based on the time distribution of the objects matching the query, the selection of the preferred time window based on at least a comparison of an actual number of objects matching the query within the time window and an expected number of the objects matching the query within a time window for each time window in the set of time windows and the expected number of objects for this time window is based on a ratio of a number of objects matching the query and a length of the time window, wherein the preferred time window is a time interval that encompasses at least some timestamps associated with the objects;
• determine a temporality of the query to generate a search result of a list of objects that are based on objects matching the query and the classification of the query within the preferred time window based on timestamp metadata of the objects matching the query;
• and
• rank the list of objects.