Statements (46)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Python
|
| gptkbp:application |
gptkb:machine_learning
gptkb:Data_Science Information Retrieval Text Mining Natural Language Processing (NLP) |
| gptkbp:community |
Active user community
|
| gptkbp:dependency |
gptkb:tqdm
gptkb:Sci_Py gptkb:Cython gptkb:Num_Py pandas smart_open |
| gptkbp:developed_by |
gptkb:Radim_Řehůřek
|
| gptkbp:example |
Sentiment analysis
Text classification Language modeling Semantic search Chatbot development Analyzing customer reviews Building recommendation systems Clustering documents Feature extraction for machine learning Topic discovery in large datasets |
| gptkbp:features |
Integration with other libraries
Streaming data processing Memory-efficient algorithms Support for large text corpora |
| gptkbp:has_documentation |
https://radimrehurek.com/gensim/
|
| https://www.w3.org/2000/01/rdf-schema#label |
Gensim
|
| gptkbp:latest_version |
4.1.2
|
| gptkbp:license |
gptkb:GNU_General_Public_License
|
| gptkbp:platform |
Cross-platform
|
| gptkbp:programming_language |
gptkb:Python
|
| gptkbp:release_date |
gptkb:2009
|
| gptkbp:repository |
https://github.com/ Ra Re-Technologies/gensim
|
| gptkbp:supports |
gptkb:Word2_Vec
gptkb:Doc2_Vec gptkb:Fast_Text Latent Dirichlet Allocation (LDA) Latent Semantic Analysis (LSA) |
| gptkbp:used_for |
topic modeling
document similarity word embedding |
| gptkbp:bfsParent |
gptkb:Natural_Language_Processing
|
| gptkbp:bfsLayer |
4
|