in reply to Comparing sets of phrases stored in a database?
As a slight parenthetical comment to BrowserUK’s excellent (and heavily up-voted) advice, I have also found it useful in some situations to create an additional mathematical set (bit-string ...) which represents “categories” of words that are present in the result. (The word, “category,” meaning precisely whatever-it-makes-sense-to-you for it to mean.) The idea is that a phrase could therefore quickly be eliminated from consideration if its set of categories-present is not the same. (If the category taxonomy contained, say, less than 32 bits, it could be represented as an integer.) The idea being to reduce the search-space, if say some kind of database I/O is required.
The notion is 150% dependent upon the needs of this application scenario. First of all, the notion of creating a digest at all must “make sense” in terms of the application spec ... there must be a “natural taxonomy” that the app can usefully exploit “for free.” Then, it must be shown to called-for, and beneficial. For instance, in some high-performance critical scenarios, it might well be contra-indicated to store the bit-strings in any sort of database at all: even a brute-force search of data, if known to entirely fit within the process’s projected resident working-set, avoids all I/O operations entirely. But if the data were much larger, the notion of creating a lookup digest might apply.