Database Structures , Based on Tries , for Text

Digital trees, or tries, were introduced thirty years ago for sublinear-time retrieval of substrings from large texts. They were exploited for this, as a well-known example, by the University of Waterloo project to put the New Oxford English Dictionary onto CD-ROM. We have recently improved the performance of trie techniques for text and shown their use in searches for approximations to a given string. We have also shown that tries have excellent retrieval properties for spatial data. We have shown how to use tries to represent, without redundancy, spatial data which can be displayed to any resolution, retrieving from disk or from network only the amount of data that will nally be displayed. We have done this particularly for two-dimensional vector data, such as makes up very large maps, but have also established that the trie techniques apply to raster data and to data of other than two dimensions. These results are the basis for a claim that tries ooer the best storage representations for large-scale multimedia databases. We are presently pursuing this claim by developing trie techniques for general data and queries. We give some results for multikey data.