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Adding analysis of string matching APIs using Urban dictionary #445

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czgdp1807 opened this issue Dec 2, 2021 · 7 comments
Open

Adding analysis of string matching APIs using Urban dictionary #445

czgdp1807 opened this issue Dec 2, 2021 · 7 comments
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algorithms documentation Improvements or additions to documentation good first issue Good for newcomers strings.algorithms strings website

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@czgdp1807
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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.

Example of the problem

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@czgdp1807 czgdp1807 added documentation Improvements or additions to documentation good first issue Good for newcomers algorithms website strings strings.algorithms labels Dec 2, 2021
@soma2000-lang
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@czgdp1807 Can I work on this issue??

@czgdp1807
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Sure go ahead.

@onnhyd
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onnhyd commented Mar 4, 2022

I want to work on this under GSSOC2022. Here is my discord profile DHANANJOY DEY | Contributor#7903

@czgdp1807
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@sceary-expert Feel free to start working on this issue.

@nishtha981
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Can I work on this issue as a GSSOC'23 contributor?

@het-dave
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Is this issue still open? I want to start working on this issue

@czgdp1807
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sure.

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Labels
algorithms documentation Improvements or additions to documentation good first issue Good for newcomers strings.algorithms strings website
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