A Method to Improve Exact Matching Results in Compressed Text using Parallel Wavelet Tree

Abstract

The process of searching on the World Wide Web (WWW) is increasing regularly, and users around the world also use it regularly. In WWW the size of the text corpus is constantly increasing at an exponential rate, so we need an efficient indexing algorithm that reduces both space and time during the search process. This paper proposes a new technique that utilizes Word-Based Tagging Coding compression which is implemented using Parallel Wavelet Tree, called WBTC_PWT. WBTC_PWT uses the word-based tagging coding encoding technique to reduce the space complexity of the index and uses a parallel wavelet tree which reduces the time it takes to construct indexes. This technique utilizes the features of compressed pattern matching to minimize search time complexity. In this technique, all the unique words present in the text corpus are divided into different levels according to the word frequency table and a different wavelet tree is made for each level in parallel. Compared to other existing search algorithms based on compressed text, the proposed WBTC_PWT search method is significantly faster and it reduces the chances of getting the false matching result.