15. A computer program product for retrieving, organizing and displaying different classifications of sets of search results in response to a text string query, the computer program product comprising: a computer readable hardware storage device having computer readable program code embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the computer readable program code comprising instructions for execution by a computer processing unit that cause the computer processing unit to: retrieve search history data that is relevant to identity indicia of a user that is associated with a text string search query; identify search resources that are associated with the user identity indicia; classify the text string search query into constituent primary search terms as a function of the identified search resources and language, wherein the constituent primary search terms are words or phrases; determine as secondary search terms synonyms and antonyms of the primary search terms that are selected by users for search iterations subsequent to searches for the primary search terms at less than a threshold frequency rate; search network resources for the primary search terms to generate a primary set of search results; search the network resources for the secondary search terms to generate a secondary set of search results; and display the primary set of search results and the secondary set of search results in different, respective tabbed sheets that are nested on top of one another in a web-based interface dashboard.
15. A computer program product for retrieving, organizing and displaying different classifications of sets of search results in response to a text string query, the computer program product comprising: a computer readable hardware storage device having computer readable program code embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the computer readable program code comprising instructions for execution by a computer processing unit that cause the computer processing unit to: retrieve search history data that is relevant to identity indicia of a user that is associated with a text string search query; identify search resources that are associated with the user identity indicia; classify the text string search query into constituent primary search terms as a function of the identified search resources and language, wherein the constituent primary search terms are words or phrases; determine as secondary search terms synonyms and antonyms of the primary search terms that are selected by users for search iterations subsequent to searches for the primary search terms at less than a threshold frequency rate; search network resources for the primary search terms to generate a primary set of search results; search the network resources for the secondary search terms to generate a secondary set of search results; and display the primary set of search results and the secondary set of search results in different, respective tabbed sheets that are nested on top of one another in a web-based interface dashboard. 17. The computer program product of claim 15 , wherein the retrieved search history data comprises unique user search history data that is associated with identity indicia that is unique to the user, and generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having common same occupational identity indicia; and wherein the computer readable program code instructions for execution by the computer processing unit further cause the computer processing unit to classify the text string search query into the constituent primary search terms by weighting classifications determined as a function of the unique user search history data more highly than classifications determined as a function of the generic occupational identity search data, and weighting classifications determined as a function of the generic occupational identity search data more highly than any classifications generated by application of universal search history popularities common to all user histories.