ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
Data structures using C
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Parameterised compression for sparse bitmaps
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Self-indexing inverted files for fast text retrieval
ACM Transactions on Information Systems (TOIS)
Inverted files versus signature files for text indexing
ACM Transactions on Database Systems (TODS)
Compressed inverted files with reduced decoding overheads
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Information retrieval on the web
ACM Computing Surveys (CSUR)
Compression of inverted indexes For fast query evaluation
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Binary Interpolative Coding for Effective Index Compression
Information Retrieval
Indexing and Retrieval for Genomic Databases
IEEE Transactions on Knowledge and Data Engineering
Information Retrieval
Inverted file compression through document identifier reassignment
Information Processing and Management: an International Journal
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Inverted Index Compression Using Word-Aligned Binary Codes
Information Retrieval
| Hi-index | 0.00 |
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.