Abstract
Retrieving of relevant information from a large corpus is a challenging task nowadays. Wavelet tree is an accomplished data structure to store and retrieve text, image, audio, and video data in efficient space and time. It has turn to be a leading tool in modernized full-text indexing or in its proficiency in compression. This study presents the contribution of wavelet trees to design indexing to retrieve information in the field of web, healthcare, agriculture, bioinformatics, and earthquake detection. In this paper, we proposed a technique of LZW compression on wavelet tree. It performs compression on the wavelet tree. This paper consists of several concepts of wavelets which show about the indexing procedure, empirical measures, wavelet packets, wavelet entropy, wavelet matrix, and complexity of wavelets. Further, the literature discusses the open issues where wavelet trees can be used to design indexing of other databases.
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This research is supported by Council of Science and Technology, Lucknow, Uttar Pradesh via Project Sanction letter number CST/D-3330.
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Gupta, S., Katiyar, N., Yadav, A.K., Yadav, D. (2022). Index Optimization Using Wavelet Tree and Compression. In: Gupta, D., Polkowski, Z., Khanna, A., Bhattacharyya, S., Castillo, O. (eds) Proceedings of Data Analytics and Management . Lecture Notes on Data Engineering and Communications Technologies, vol 90. Springer, Singapore. https://doi.org/10.1007/978-981-16-6289-8_66
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