RESEARCH ARTICLE MergedTrie: Efficient textual indexing Antonio FerraÂndez1, Jesu s Peral2* 1 GPLSI Research Group, Department of Software and Computing Systems, University of Alicante, Alicante, Spain, 2 Lucentia Research Group, Department of Software and Computing Systems, University of Alicante, Alicante, Spain *
[email protected] a1111111111 Abstract a1111111111 a1111111111 The accessing and processing of textual information (i.e. the storing and querying of a set of a1111111111 strings) is especially important for many current applications (e.g. information retrieval and a1111111111 social networks), especially when working in the fields of Big Data or IoT, which require the handling of very large string dictionaries. Typical data structures for textual indexing are Hash Tables and some variants of Tries such as the Double Trie (DT). In this paper, we pro- pose an extension of the DT that we have called MergedTrie. It improves the DT compres- OPEN ACCESS sion by merging both Tries into a single and by segmenting the indexed term into two fixed Citation: FerraÂndez A, Peral J (2019) MergedTrie: length parts in order to balance the new Trie. Thus, a higher overlapping of both prefixes Efficient textual indexing. PLoS ONE 14(4): and suffixes is obtained. Moreover, we propose a new implementation of Tries that achieves e0215288. https://doi.org/10.1371/journal. better compression rates than the Double-Array representation usually chosen for imple- pone.0215288 menting Tries. Our proposal also overcomes the limitation of static implementations