Abstract: Data records are searched by use of a taxonomy comprising search terms having associated respective metadata wherein, for each search term, the associated metadata includes a measure of relatedness based on co-occurrences of search terms in at least one data record of a body of data records. A set of one or more search terms is selected and the taxonomy is referred to so as to extend the set of one or more selected search terms by including any different search terms having a significant measure of relatedness in relation to the one or more selected search terms.

Abstract: A set of search results obtained by searching a body of data records is ranked, the set of search results identifying respective data records containing one or more search terms in a first category. At least one search term of a taxonomy is selected, the taxonomy including search terms having associated metadata which, for at least some search terms, identifies a second category and includes any positive measure of relatedness to at least one different search term in the second category, the measure of relatedness being based on co-occurrences of the search terms in individual ones of a plurality of data records. The search results are then ranked, at least partially, according to the measure of relatedness to the selected search term(s) of one or more search terms in the second category which are contained in the respective data records of the search results.

Abstract: A weighting processor and a method for ranking search results obtained by searching a body of data records. The ranking is carried out in relation to at least one selected search term contained in a taxonomy in which search terms have associated metadata which, for each search term, identifies a category and includes any measure of relatedness to at least one different search term in the same category, the measure being based on co-occurrences of the search terms in individual ones of a plurality of data records. The search results identify data records containing one or more search terms from the taxonomy and the results are ranked by summing, for each data record of the results, the measures of relatedness of search terms present in the data record to the selected search term(s).

Abstract: A taxonomy is built by associating metadata with search terms. A body of data records is analyzed to identify pairs of search terms co-occurring in individual data records and to obtain an observed measure of the frequency of such co-occurrences between identified pairs. A taxonomy is then built by constructing metadata and associating the search terms with respective metadata, the metadata for each co-occurring search term identifying at least one other search term with which it co-occurs, together with a measure of relatedness based on the observed co-occurrence frequency measure between the co-occurring pair.