gensim-doc2vec
There are 27 repositories under gensim-doc2vec topic.
PengboLiu/Doc2Vec-Document-Similarity
利用Doc2Vec计算文本相似度
SOUMEE2000/Applicant_Tracking_System
This streamlitapp is built for employers looking to match best candidate resumes against a particular job description.
lordtt13/word-embeddings
Custom word embeddings created from latent features generated by gensim and hugging face models
meet5398/NLP-Natural-Language-Processing-
This repository is a collection of six minor projects focused on Natural Language Processing (NLP) along with relevant datasets. The projects are designed to help individuals gain a better understanding of NLP by applying concepts to real-world problems. Additionally, the repository includes a file that provides a comprehensive overview of NLP .
mihirsam/Information-Extraction-using-CNN
Extract the summary from the given text using Convolution Neural Network
KrishArul26/Text-Classification-DBpedia-ontology-classes-Using-LSTM
Text classification is the task of assigning a set of predefined categories to free text. Text classifiers can be used to organize, structure, and categorize pretty much anything. For example, new articles can be organized by topics, support tickets can be organized by urgency, chat conversations can be organized by language, brand mentions can be organized by sentiment, and so on.
luminoso/news-keywords-searcher
Proof of concept project that implements a keyword search (text similarity) over a corpus
levitation-opensource/LegalSearch
A prototype legal text search engine that uses a semantic search algorithm in order to find related keywords and sort the results by relevance.
pbellot/ANF-TDM
Code, données et documentations de l'atelier "Apprentissage automatique pour la classification textuelle" organisé dans le cadre de l'Action Nationale de Formation "Exploration documentaire et extraction d'information" CNRS-INRAE en 2020-21.
akshataupadhye/News-articles-clustering-A-comparative-approach
A project featuring the use of various NLP techniques and ML algorithms like the topic modelling and paragraph embeddings, for document clustering. 📰📚
jacksavage/DocClusterART
Cluster documents with Fuzzy-ART and PV-DM
ucals/bettertogether
This app uses Machine Learning NLP/topic modeling/document similarity techniques to group OMSCS CS-6460 Fall 2018 students by interests based on their essays/writing assignments
AmirMotefaker/Analysis-of-Hotel-Customer-Sentiments
Sentiment analysis is part of the NLP techniques that consists in extracting emotions related to some raw texts.
colurw/wiki_abstracts_NLP
Document-level semantic clustering. Unsupervised topic modelling.
rochimfn/question-answering-konstitusi
Indonesia Constitution Question Answering System (Telegram Bot, Streamlit Page, and HTTP API)
shinho123/1st-Author-Journal-KCI-Asia-Pacific-Journal-of-Business-Venturing-and-Entrepreneurship
2023년 7월 논문게재(한국벤처창업연구) : COVID-19에 따른 글로벌 창업 트렌드 분석: Cruchbase를 중심으로(Analysis of Global Entrepreneurship Trends Due to COVID-19: Focusing on Crunchbase, 1저자
somjit101/NLP-Star-Trek-Scripts
Using digital form of the actual scripts of the 'Star Trek' science fiction series to perform interesting NLP tasks and answering some questions on Topic Modelling, Character properties and the plot as a whole.
Alisaahy/Customer-Issue-Prediction
An end to end app to predict what issue customers have being faced with by analyzing customer complaints.
kumarnalinaksh21/kaggle
TCS Enterprise Intelligent Automation – ARITIFICIAL INTELLIGENCE Competition Repository for TCS Enterprise Intelligent Automation – ARITIFICIAL INTELLIGENCE Competition. datasets are taken from Kaggle Quora competition.
rayen03/RecruitFlow
Resume ranking model
SeanFlannery/NAR-Data-Discovery
Nucleic Acids Research Data Discovery
suchetsapre/automated-clinical-note-annotation
Georgetown University Medical Center ICBI summer 2019 research project involving the automation of the annotation of patients' clinical notes.
VarunB-17/Personality-Inferencing-ML
Personality Inferencing ML
yash111381/Data-Mining-to-Improve-Commercial-Movie-Success
Efficient Word2Vec vectors for Sentiment Analysis to improve Commercial Movie Success, done in two phases, involving machine learning and sentiment analysis.