# Bonding Period Update - Week 3

**URL:** https://discourse.joplinapp.org/t/bonding-period-update-week-3/38299
**Category:** Summarize with AI
**Created:** [27 May 2024 00:08 UTC](https://discourse.joplinapp.org/t/bonding-period-update-week-3/38299 "2024-05-27T00:08:38Z")
**Posts on this page:** 1
**Page:** 1

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### Author: ![HahaBill](https://yyz2.discourse-cdn.com/flex028/user_avatar/discourse.joplinapp.org/hahabill/32/20339_2.png) [@HahaBill](https://discourse.joplinapp.org/u/HahaBill)
#### Post date: [27 May 2024 00:08 UTC](https://discourse.joplinapp.org/t/bonding-period-update-week-3/38299/1 "2024-05-27T00:08:38Z")

</div>

# Progress

- new plugin set up: [GitHub - joplin/plugin-ai-summarisation: 🤖 Joplin AI - Summarisation: The project aims to create note summaries to help users synthesize main ideas and arguments to identify salient points. This means that users will have a clear idea of what the note is about in a short piece of text with less mental effort.](https://github.com/joplin/plugin-ai-summarisation)
- created and added a idea for the summarisation feature: Allow users to summarise particular part of the note by highlighting the text
- implemented single note summarisation with TextRank
- explored more algorithms for extractive summarisation: LexRank, LSU, Luhn, TD-IDF, KL-Sum, BERTSUM
- experimented with Tensorflow.js in a plugin
  - used and tested pre-trained qna model for the summarisation feature
  - with 1000 characters, it takes 1 min for a model to give an answer =\> very slow for large notes

# Plans

- implementing "summarising multiple notes simultaneously" feature
- learn more about webpack
- making a table of all extractive summarisations and discover their strengths and weaknesses
  - TextRank could be enhanced:
    - [Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and Summarisation] ([[1911.10183] Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and Summarisation](https://arxiv.org/abs/1911.10183)) [[1911.10183] Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and Summarisation](https://arxiv.org/abs/1911.10183)
    - [The enhancement of TextRank algorithm by using word2vec and its application on topic extraction] ([Redirect Notice](https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://iopscience.iop.org/article/10.1088/1742-6596/887/1/012028/pdf%23:~:text%3DWord%2520embedding%2520(CBOW%2520and%2520Skip,miss%2520selection%2520of%2520vital%2520keywords.&ved=2ahUKEwi8gsjGwqyGAxVKQkEAHZtUA2UQFnoECA8QAw&usg=AOvVaw0R71v9jdTT9iBAQ8ObGGgb))
    - [Enhancement of TextRank Algorithm using Coreference Resolution] ([https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://ijrp.org/filePermission/fileDownlaod/4/be915dd3ab99f5f1ed933e0765edbfe2/2&ved=2ahUKEwi8gsjGwqyGAxVKQkEAHZtUA2UQFnoECCEQAQ&usg=AOvVaw3KVBOsJ9jXwSOHtLZikBln](https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://ijrp.org/filePermission/fileDownlaod/4/be915dd3ab99f5f1ed933e0765edbfe2/2&ved=2ahUKEwi8gsjGwqyGAxVKQkEAHZtUA2UQFnoECCEQAQ&usg=AOvVaw3KVBOsJ9jXwSOHtLZikBln))[https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://ijrp.org/filePermission/fileDownlaod/4/be915dd3ab99f5f1ed933e0765edbfe2/2&ved=2ahUKEwi8gsjGwqyGAxVKQkEAHZtUA2UQFnoECCEQAQ&usg=AOvVaw3KVBOsJ9jXwSOHtLZikBln](https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://ijrp.org/filePermission/fileDownlaod/4/be915dd3ab99f5f1ed933e0765edbfe2/2&ved=2ahUKEwi8gsjGwqyGAxVKQkEAHZtUA2UQFnoECCEQAQ&usg=AOvVaw3KVBOsJ9jXwSOHtLZikBln)

  - Algorithms that need to be written from scratch: Luhn, LSU, KL-Sum and BERTSUM. (For improving TextRank, we might have to write that from scratch too)

# Problems

- I am still having issues with setting up Transformers.js in a plugin