Storage Consumption Reduction using Improved Inverted Indexing for Similarity Search on LINGO Profiles

Millions of compounds which exist in huge datasets are represented using Simplified Molecular-Input Line- Entry System (SMILES) representation. Fragmenting SMILES strings into overlapping substrings of a defined size called LINGO Profiles avoids the otherwise time-consuming conversion process. One drawback of this process is the generation of numerous identical LINGO Profiles. Introduced by Kristensen et al, the inverted indexing approach represents a modification intended to deal with the large number of molecules residing in the database. Implementing this technique effectively reduced the storage space requirement of the dataset by half, while also achieving significant speedup and a favourable accuracy value when performing similarity searching. This report presents an in-depth analysis of results, with conclusions about the effectiveness of the working prototype for this study.

@article{Javeed2019,
  title     = {Storage Consumption Reduction using Improved Inverted Indexing for Similarity Search on LINGO Profiles},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {5},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Muhammad Jaziem bin Javeed and Nurul Hashimah Ahamed Hassain Malim},
  doi       = {10.14569/IJACSA.2019.0100505},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100505}
}