Abstract: This application relates to a technique that enables efficient indexing and querying of a set of documents stored at a computing device. The technique assigns a rank to each term of a set of terms based on a historical occurrence of each term to produce a set of ranked terms. The technique also creates subsets that include terms from the set of ranked terms to produce ranked term subsets that are encoded in accordance with an allocated bit size. The technique generates an index for each document of the set of documents through: (1) the identification of the ranked term subsets within the document, (2) the generation of arrays to store each ranked term subset identified within the document, and (3) the embedding of metadata within the document. The metadata includes: (i) one or more arrays and (ii) one or more counts corresponding to each array.

Abstract: This application relates to a technique that enables efficient indexing and querying of a set of documents stored at a computing device. The technique assigns a rank to each term of a set of terms based on a historical occurrence of each term to produce a set of ranked terms. The technique also creates subsets that include terms from the set of ranked terms to produce ranked term subsets that are encoded in accordance with an allocated bit size. The technique generates an index for each document of the set of documents through: (1) the identification of the ranked term subsets within the document, (2) the generation of arrays to store each ranked term subset identified within the document, and (3) the embedding of metadata within the document. The metadata includes: (i) one or more arrays and (ii) one or more counts corresponding to each array.