Hashing Trie: A New Way to Search

With the ever-growing quantity of data, there is a need to handle it efficiently. Several approaches have been introduced in the literature to enhance search efficiency. The existing methods use different data structures, such as Hashes and Trees, to reduce the computational complexity. However, Hashes-based methods may perform poorly if a collision occurs, and tree-based methods take longer if the data is present at the last level. Therefore, this paper introduces a hybrid method based on the capabilities of hash and trie. The proposed method defines a custom hash function to encode and decode the key string to and from hash numbers for inner hashes. The proposed method creates an inverted index of large text corpora using text-document mapping to improve search efficiency. The performance of the proposed method has been validated in terms of computational time for different input text data split sizes. Besides, the proposed method has also been statistically validated using the Friedman test.