Improved Compressed Indexes for Full-Text Document Retrieval

摘要

We give new space/time tradeoffs for compressed indexes that answer document retrieval queries on general sequences. On a collection of D documents of total length n, current approaches require at least |CSA| + O(n(lg D)/(lglg D)) or 2|CSA| + o(n) bits of space, where CSA is a full-text index. Using monotone minimum perfect hash functions, we give new algorithms for document listing with frequencies and top-k document retrieval using just |CSA| + O(n lglglg D) bits. We also improve current solutions that use 2|CSA| + o(n) bits, and consider other problems such as colored range listing, top-k most important documents, and computing arbitrary frequencies.