Description
Description of the problem
As in the tutorial description here, we say, "we plan to add some more examples showing usage of pydatastructs on real world data sets such as Stanford Large Network Dataset Collection and Urban Dictionary Words And Definitions". So, this issue is for completing the task of adding a jupyter notebook showing usage of string matching APIs in pydatastructs Urban Dictionary Words And Definitions. This is open ended. For example, you can just take the whole urban dictionary in a string and then query it on a million random inputs and show how different string matching algorithms work.
For reference you can see our current analysis of different shortest path algorithms here.
The urban dictionary dataset is available here. You can use Google colab and your Gdrive to do the analysis.