N-gram indexing is used in many practical applications. Spam detection, plagiarism detection or comparison of DNA reads. There are many data structures that can be used for this purpose, each with different characteristics. In this article the ternary search tree data structure is used. One improvement of ternary tree that can save up to 43% of required memory is introduced. In the second part new data structure, named ternary forest, is proposed. Efficiency of ternary forest is tested and compared to ternary search tree and two-level indexing ternary search tree.
['Daniel Robenek', 'Jan Platos', 'Vaclav Snasel']
Ternary Tree Optimalization for n-gram Indexing