Compression Using Huffman Coding for Enhanced Performance

Abstract

Due to the expansion of the size of data in the information recovery applications and the rising number of customers for these applications, the information retrieval system is facing numerous problems. The performance of IRS has been raised by compressing inverted index, which is a data structure for large scale search engines that is actually a group of sorted integer pattern called Inverted Index Compression. Due to the misuse of computer memory for speedy query processing along with the decrease in the number of machines used for storage, it has focused on minimizing the index size for quick interactive searching.In this research paper the technique proposed is the Huffman Coding technique to compress the Inverted Index and have shown analytically that Huffman Coding requires least storage space as well as enlarge the keyword search performance and lower the time to analyse the query.