1. A method of merging search results, comprising: identifying a query from a user; splitting the query into sub-queries; for each of the sub-queries, determining a user importance value for said each sub-query to quantify how important said each sub-query is to the user relative to how important the others of the sub-queries are to the user, executing said each sub-query to obtain a search result for said each sub-query, and using the user importance value determined for said each sub-query to assign a user relevance score to the search result obtained for said each sub-query; and combining the search results for the sub-queries based on the user relevance scores assigned to the search results to obtain merged search results; and wherein: the execution of each of the sub-queries includes identifying a multitude of search results for at least one of the sub-queries; the combining includes grouping said multitude of search results into a plurality of clusters, and computing a relevance score for each of said clusters, wherein each cluster represents a high level entity; the determining a user importance value for said each sub-query includes identifying one of the sub-queries as a primary focus, and identifying another of the sub-queries as providing context, computing a probability p(Q) of each of the sub-queries, and computing information content of each of the sub-queries as log p(Q); and the combining the search results further includes, once the information content of the sub-queries are computed, merging the search results.
1. A method of merging search results, comprising: identifying a query from a user; splitting the query into sub-queries; for each of the sub-queries, determining a user importance value for said each sub-query to quantify how important said each sub-query is to the user relative to how important the others of the sub-queries are to the user, executing said each sub-query to obtain a search result for said each sub-query, and using the user importance value determined for said each sub-query to assign a user relevance score to the search result obtained for said each sub-query; and combining the search results for the sub-queries based on the user relevance scores assigned to the search results to obtain merged search results; and wherein: the execution of each of the sub-queries includes identifying a multitude of search results for at least one of the sub-queries; the combining includes grouping said multitude of search results into a plurality of clusters, and computing a relevance score for each of said clusters, wherein each cluster represents a high level entity; the determining a user importance value for said each sub-query includes identifying one of the sub-queries as a primary focus, and identifying another of the sub-queries as providing context, computing a probability p(Q) of each of the sub-queries, and computing information content of each of the sub-queries as log p(Q); and the combining the search results further includes, once the information content of the sub-queries are computed, merging the search results. 4. The method according to claim 1 , wherein: the combining includes determining the cluster relevance score for each of the clusters based on the relevance scores of the search results which form the cluster.