This is live on Flask: rwilfong.pythonanywhere.com
This program takes a list of DOI's from user input, retrieves their abstracts, and generates a pair of summaries and keywords based on the text in the abstract. It has a content-based recommender system based on the generated keywords for each paper. It was created for BIOL 595: Practical Biocomputing at Purdue University.
Flask:
- Flask
- render_template
- request
- redirect
- url_for
- session
Datetime:
- datetime
Collections:
- defaultdict
scikit-learn:
- sklearn.feature_extraction.text: CountVectorizer, TfidfVectorizer
- sklearn.metrics.pairwise: cosine_similarity
NLTK:
- nltk.tokenize: sent_tokenize
- nltk.collocations: BigramAssocMeasures, BigramCollocationFinder
- nltk.corpus import stopwords
NetworkXNumPyxml.etree.ElementTreesqlite3Biopython:
- Entrez
string:
- punctuation