Unique-order interpolative coding for fast querying and space-efficient indexing in information retrieval systems

Abstract

This paper presents a size reduction method for the inverted file, the most suitable indexing structure for an information retrieval system (IRS). We notice that in an inverted file the document identifiers for a given word are usually clustered. While this clustering property can be used in reducing the size of the inverted file, good compression as well as fast decompression must both be available. In this paper, we present a method that can facilitate coding and decoding processes for interpolative coding using recursion elimination and loop unwinding. We call this method the unique-order interpolative coding. It can calculate the lower and upper bounds of every document identifier for a binary code without using a recursive process, hence the decompression time can be greatly reduced. Moreover, it also can exploit document identifier clustering to compress the inverted file efficiently. Compared with the other well-known compression methods, our method provides fast decoding speed and excellent compression. This method can also be used to support a self-indexing strategy. Therefore our research work in this paper provides a feasible way to build a fast and space-economical IRS.