DocSum | automatically summarize documents | Natural Language Processing library
kandi X-RAY | DocSum Summary
kandi X-RAY | DocSum Summary
A tool to automatically summarize documents (or plain text) using either the BART or PreSumm Machine Learning Model. BART (BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension) is the state-of-the-art in text summarization as of 02/02/2020. It is a "sequence-to-sequence model trained with denoising as pretraining objective" (Documentation & Examples). PreSumm (Text Summarization with Pretrained Encoders) applies BERT (Bidirectional Encoder Representations from Transformers) to text summarization by using "a novel document-level encoder based on BERT which is able to express the semantics of a document and obtain representations for its sentences." BERT represented "the latest incarnation of pretrained language models which have recently advanced a wide range of natural language processing tasks" at the time of writing (Documentation & Examples).
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Top functions reviewed by kandi - BETA
- Forward computation
- Returns a TransformerDecoderState
- Evaluate the rouge model
- Translate a batch
- Create a list of translations from a given translation
- Translate a single batch
- Process a tqdm xml file
- Return a list of all pages that are not close together
- Summarize a document
- Summarize a folder of documents
- Collate tokens into a single batch
- Build data loader from documents
- Translate the given batch
- Check if a directory exists
- Calculate the probability score for a beam
- Returns the length of the weight penalty
- Parse an XML file
DocSum Key Features
DocSum Examples and Code Snippets
Community Discussions
Trending Discussions on DocSum
QUESTION
I'm working with a project where we are web-scraping PubMed research abstracts and detecting if any researchers from our organization have authorship on any new publications. When we detect a match, we want to add a bold HTML tag. For example, you might see something like this is PubMed: Sanjay Gupta 1 2 3, Mehmot Oz 3 4, Terry Smith 2 4 (the numbers denote their academic affiliation, which corresponds to a different field, but I've left this out for simplicity. If Mehmot Oz and Sanjay Gupta were in my list, I would add a bold tag before their first name and a tag to end the bold at the end of their name.
One of my challenges with PubMed is the authors sometimes only show their first and last name, other times it includes a middle initial (e.g., Sanjay K Gupta versus just Sanjay Gupta). In my list of people, I only have first and last name. What I tried to do is import my list of names, split first and last name, and then bold them in the list of authors. The problem is that my code will bold anyone with the first name or anyone with the last name (example: Sanjay Smith 1 2 3, Sanjay Gupta 1 3 4, Wendy Gupta 4 5 6, Linda Oz 4, Mehmet Jones 5, Mehmet Oz 1 4 6.) gets bolded. I realize the flaw in my code, but I'm struggling for how to get around this. Any help is appreciated.
Bottom Line: I have a list of people by first name and last name, I want to find their publications in PubMed and bold their name in the author credits. PubMed sometimes has their first and last name, but sometimes their middle initial.
To make things easier, I denoted the section in all caps for the part in my code where I need help.
...ANSWER
Answered 2021-Jan-29 at 19:50Here is the modification that needs to be done in the section you want help with. Here is the algorithm:
- Create list of authors by splitting on
,
- For each author in authors, check if au_l and au_f are present in author.
- If true, add
tags
QUESTION
I want to extract research abstracts on PubMed. I will have multiple URLs to search for publications and some of them will have the same articles as others. Each article has a unique ID called a PMID. Basically, the abstract of each URL is a substring + the PMID (example: https://pubmed.ncbi.nlm.nih.gov/ + 32663045). However, I don't want to extract the same article twice for multiple reasons (i.e., takes longer to complete the entire code, uses up more bandwidth), so once I extract the PMID, I add it to a list. I'm trying to make my code only extract information from the abstract just once, however my code is still extracting duplicate PMIDs and publication titles.
I know how to get rid of duplicates in Pandas in my output, but that's not what I want to do. I want to basically skip over PMIDs/URLs that I already scraped.
Current Output
Title| PMID
COVID-19 And Racial/Ethnic Disparities In Health Risk | 32663045
The Risk Of Severe COVID-19 | 32941086
COVID-19 And Racial/Ethnic Disparities In Health Risk | 32663045
The Risk Of Severe COVID-19 | 32941086
Desired Output
Title| PMID
COVID-19 And Racial/Ethnic Disparities In Health Risk | 32663045
The Risk Of Severe COVID-19 | 32941086
Here's my code:
...ANSWER
Answered 2021-Jan-22 at 02:24Just an indentation error, or more accurately, where you are running your two for loops. If it isn't just an overlooked mistake, read the explanation. If it is just a mistake, unindent your second for loop.
Because you are searching all_pmids
within your larger search_url
loop without resetting it after each search, it finds the first two pmids
, adds them to all_pmids
, then runs the next loop for those two.
In the second run of the outer loop, it finds the next two pmids
, sees they're already in ```all_pmids`` so doesn't add them, but still runs the inner loop on the first two still stored in the list.
You should run the inner loop separately, as such:
QUESTION
I am trying to get href
data for the below url
ANSWER
Answered 2020-Apr-05 at 18:20Try something like:
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