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Added a TODO list in the README
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rahulnyk committed Nov 12, 2023
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Expand Up @@ -81,3 +81,23 @@ This is a python library that makes dealing with graphs super easy
### Pyvis
[Pyvis python library](https://github.com/WestHealth/pyvis/tree/master) for visualisation. Pyvis generates Javascript Graph visualisations using python, so the final graphs can be hosted on the web. For example the [github link of this repo](https://rahulnyk.github.io/knowledge_graph/) is a graph generated by pyvis


# Looking for contributions
This project needs a lot more work. There are some wonderful ideas suggested by folks on medium and here on Github. If this interests you, Please join hands and lets' build this together. Here is a list of ideas

### Back End

- [ ] Use embeddings to deduplicate semantically similar concepts (**Suggested by William Claude on the [Medium Article](https://medium.com/towards-data-science/how-to-convert-any-text-into-a-graph-of-concepts-110844f22a1a)**)
- [ ] Avoid having similar concepts written differently by the LLM (eg: "doctor" and "doctors")
- [ ] Reinforce the clustering of strongly similar concepts (eg: "doctor" and "medical practitioner")?

- [ ] Filter out the redundant, or outlier concepts that may not be useful in understanding the text. For example, generic concepts that occur too often in the text. (**Suggested by Luke Chesley**)

- [ ] Better implement the concept of contextual proximity to avoide overweighting certain concepts that occur too frequently, or to weed out useless edges. (**Suggested by Luke Chesley**)

### Front End
- [ ] Create a Frontend for rendering Graph of Concepts in a more useful way. for example here is a flow. (**Suggested by David Garcia on the [Medium Article](https://medium.com/towards-data-science/how-to-convert-any-text-into-a-graph-of-concepts-110844f22a1a)**).
1. Provide a list concept/interest/topics
2. User selects what they're interested in
3. This expands to show sub-topics, sub-concepts, sub-x, etc.
4. This is how you get deep into a specialty
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