litstudy
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NLeSC
LitStudy: Using the power of Python to automate scientific literature analysis from the comfort of a Jupyter notebook
WoS (Web of Science) is a very popular database for scientific literature. There exists an Python wrapper for their API (https://pypi.org/project/wos/). It would be great if this was supported in...
Currently, the topic modeling methods require the user to select the number of topics. It would be great if the optimal number of topics was selected automatically. For example, this...
Currently, there is no way to export results after loading them into memory. On possibility would be to add the ability to export a `DocumentSet` to a RIS file.
Currently, there is no way to export results after loading them into memory. On possibility would be to add the ability to export a `DocumentSet` to a bibtex file.
Calculating the statistics requires fuzzy matching of names. Currently, this matching is not too aggressive since we do want to avoid incorrectly matching two different names. The matching algorithm should...
pyvis is very slow if the network being visualized is large (ie, >1000 nodes). The current solution is to disable interactivity in pyvis for large graph and calculate the graph...
Hi, first of all thanks for developing this clean and handy tool. When I call `nlp.train_lda_model()` I get the following error: ``` ModuleNotFoundError: No module named 'gensim.models.lda' ``` This makes...
This is the full error snippet. Please help me fix this. ``` Scopus400Error Traceback (most recent call last) ~\AppData\Local\Temp\ipykernel_11056\1525091348.py in () 2 logging.getLogger().setLevel(logging.CRITICAL) 3 ----> 4 docs_scopus, docs_notfound = litstudy.refine_scopus(docs_remaining)...
Hi, Is it possible to refine/process publications from Scopus limited to source titles containing a specified keyword? For example, my query (and variations thereof) gives me the above error after...
This PR implements the proposed persistant models as discussed in https://github.com/NLeSC/litstudy/discussions/82 .
