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 ╚══╝╚══╝ ╚═╝╚══════╝╚═╝     	2.0s - supporting CLI only
                                JIMUT(TM) 

Wisp : A preference based location finder app

Papers With Code

Abstract

The work of finding the best place according to user preference is a tedious task. It needs manual research and lot of intuitive process to find the best location according to some earlier knowledge about the place. It is mainly about accessing publicly available spatial data, applying a simple algorithm to summarize the data according to given preferences, and visualizing the result on a map. We introduced JJCluster to eliminate the rigorous way of researching about a place and visualizing the location in real time. This algorithm successfully finds the heart of a city when used in Wisp application. The main purpose of designing Wisp application is used for finding the perfect location for a trip to unknown place which is nearest to a set of preferences. We also discussed the various optimization algorithms that are pioneer of today's dynamic programming and the need for visualization to find patterns when the data is cluttered. Yet, this general clustering algorithm can be used in other areas where we can explore every possible preference to maximize its utility.

Usage for version - 2.0 (Supporting CLI only)

$ git clone https://github.com/Jimut123/wisp
$ sudo pip install -r requirements.txt
$ python wisp_v2.py

Using JJ-CLUSTER

Documentations

[abs/2002.05886 Research paper | B.Sc. Thesis | Old-Slide]

Video

These are some of the recent vizualisations generated by the clustering algorithm.

• Kolkata with 8 preference
• Berlin with 6 preference
• Tokyo with 15 preference
• Chicago with 7 preference
• Delhi with 5 preference
• Hyderabad with 5 preference
• Islamabad with 5 preference
• Jaipur with 5 preference
• London with 7 preference
• Moscow with 6 preference
• Mumbai with 9 preference
• New York with 7 preference
• Singapore with 7 preference
• Srinagar with 4 preference
• Vadodara with 5 preference

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Contribution

Please feel free to raise issues and fix any existing ones. Further details can be found in our code of conduct.

While making a PR, please make sure you:

• Always start your PR description with "Fixes #issue_number", if you're fixing an issue.
• Briefly mention the purpose of the PR, along with the tools/libraries you have used. It would be great if you could be version specific.
• Briefly mention what logic you used to implement the changes/upgrades.
• Provide in-code review comments on GitHub to highlight specific LOC if deemed necessary.
• Please provide snapshots if deemed necessary.
• Update readme if required.

LICENSE

 GNU GENERAL PUBLIC LICENSE
                       Version 3, 29 June 2007

 Copyright (C) 2019-20 Jimut Bahan Pal, <https://jimut123.github.io/>
 Everyone is permitted to copy and distribute verbatim copies
 of this license document, but changing it is not allowed.

BibTeX and citations

@article{DBLP:journals/corr/abs-2002-05886,
  author    = {Jimut Bahan Pal},
  title     = {How to cluster nearest unique nodes from different classes using JJCluster
               in Wisp application?},
  journal   = {CoRR},
  volume    = {abs/2002.05886},
  year      = {2020},
  url       = {https://arxiv.org/abs/2002.05886},
  archivePrefix = {arXiv},
  eprint    = {2002.05886},
  timestamp = {Mon, 02 Mar 2020 16:46:06 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2002-05886.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

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