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# System prepended metadata

title: Martin PhD meeting
tags: [PhD]

---

---
tags: PhD
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# Martin PhD meeting
2021-11-18

## Present:
Martin; Laurie; Alessandro

## Since the last meeting:

* Re-reviewed code, tested and rechecked
* Have workflow which can:
    * Extract full-text papers from ScienceDirect API (Creatting Corpus - based on a topic search term): XML
    * Remove body from abstract and discard the rest
    * Identify top n=3 key topics in each paper (LDA) [1]
    * Identify paragraphs which contain these topics
    * Run BERT based summarisation to create sample phrases from target paragraphs. Was an LSTM, still works but nastier.
    * (Graph summaries and their interconnection within Corpus)
    * (Walk graph to retrieve series of discrete summary sentences/phrases for a particular topic concentration within the Corpus. Do this meta-topic by meta-topic)
    * (From each meta-abstraction pass through eg. GPT-2 to create continuous prose)
    * ROUGE-type evaluation of summaries
    * Evaluation of 
    
    
    
## To-do

* Prepare **presentation** for December 3rd
* [1]Identify different techniques for topic extraction and compare ([LSA; pLSA; lda2vec](https://medium.com/nanonets/topic-modeling-with-lsa-psla-lda-and-lda2vec-555ff65b0b05
)). Still likely that LDA gives biggest bang for buck. See [1] above
* I've started to look at methods for creating and populating Knowledge Graphs([For example with Spacy](https://www.analyticsvidhya.com/blog/2019/10/how-to-build-knowledge-graph-text-using-spacy/)- less than happy with this so far. So I need a bigger and longer think about even the best way to do this. **Longer chat next time**
    * Need a better example of this 
* Literature review
* Technical notes on the bits of the methodology that work so far and overall workflow. With my rationalisation.

### Presentation

December 3rd: 1100-1200

Format? **45 mins + 15 mins** questions?

* Personal introduction
* Summary of research question
    * Create a one sentence summary of a paragraph > response via Google form
    * In closing, compare human summaries with automated summaries
* Key works in the field and a bit of back story?
* My proposed workflow.
* My reproducible tools and techniques
* Pick-and-mix of interesting bits (show and tell with code etc).
* Some results and summaries
* Bits that have worked well, bits that caused me problems
* Work yet to complete
* Stick it up on Figshare with a DOI.
* Questions?

Link on GH> Laurie & Alessandro

##  Next meeting?
2021-12-16 0900