Abstract.We design and analyze integrated ways of applying the signature file approach for text and attributes simultaneously. In traditional signature file methods, the records are stored sequentially in the "main file"; for every record, a hash-coded abstraction of it ("record signature") is created and stored in the signature file (usually, sequentially). To resolve a query, the signature file is scanned : the signatures retrieved correspond to all the qualifying records, plus some "false drops".Here, we extend some signature file methods, namely superimposed coding and disjoint coding, to handle text and attributes. We develop a mathematical model and derive formulas for the optimal choice of parameters. The proposed methods achieve significant performance improvements, because they can take advantage of the skewed distribution of the queries. Depending on the query frequencies, the false drop probability can be reduced 40-45 times (~ 97% savings), for the same overhead.