1. A method of merging results in distributed information retrieval, comprising: dividing a full query as input by a user into a multiplicity of sub-queries, wherein the sub-queries each comprise a set of keywords of the full query; submitting the full query and the multiplicity of sub-queries to each of a plurality of components, wherein a component comprises a search engine operating on a hardware processor and working on a document collection stored in one or more databases; receiving results of the full query and sub-queries from each component in the form of a list of documents, wherein the results for the full query and the results for the sub-queries from each component have document scores (DS) to which a merit score is applied; estimating a success of the components in handling the full query to generate the merit score for a component per query, wherein estimating the success includes determining an extent of overlap between results for the full query and results for the sub-queries for each of the components, wherein determining the extent of overlap comprises generating a binary histogram of an overlap vector of the extent of overlap; and multiplying a per search engine tuning vector with a ranked version of the binary histogram; applying the merit score to the results for the full query for the components, respectively, wherein the merit score is applied if the variance is above a predetermined threshold level; merging the results for the full query produced by the plurality of components by ranking the results for the full query in order of the applied merit scores.
1. A method of merging results in distributed information retrieval, comprising: dividing a full query as input by a user into a multiplicity of sub-queries, wherein the sub-queries each comprise a set of keywords of the full query; submitting the full query and the multiplicity of sub-queries to each of a plurality of components, wherein a component comprises a search engine operating on a hardware processor and working on a document collection stored in one or more databases; receiving results of the full query and sub-queries from each component in the form of a list of documents, wherein the results for the full query and the results for the sub-queries from each component have document scores (DS) to which a merit score is applied; estimating a success of the components in handling the full query to generate the merit score for a component per query, wherein estimating the success includes determining an extent of overlap between results for the full query and results for the sub-queries for each of the components, wherein determining the extent of overlap comprises generating a binary histogram of an overlap vector of the extent of overlap; and multiplying a per search engine tuning vector with a ranked version of the binary histogram; applying the merit score to the results for the full query for the components, respectively, wherein the merit score is applied if the variance is above a predetermined threshold level; merging the results for the full query produced by the plurality of components by ranking the results for the full query in order of the applied merit scores. 5. A method according to claim 1 , wherein the sub-queries are at least one of the following: keywords, lexical affinities, synonyms and dictionary definitions.