Improving Recall and Precision in Unsupervised Multi-Label Document Classification Tasks by Combining Word Embeddings with TF-IDF.
Stefan HirschmeierJohannes Werner MelsbachDetlef SchoderSven StahlmannPublished in: ECIS (2020)
Keyphrases
- tf idf
- multi label
- text categorization
- term frequency
- term weighting
- text documents
- text classification
- vector space model
- feature selection
- image annotation
- semi supervised learning
- statistical topic models
- unsupervised learning
- knn
- information retrieval
- k nearest neighbor
- document clustering
- vector space
- semi supervised
- image classification
- graph cuts
- co occurrence
- retrieval model
- n gram
- dimensionality reduction
- supervised learning
- distance measure
- keywords
- class labels
- low dimensional
- natural language processing
- topic models
- web documents
- unlabeled data
- support vector machine
- average precision
- computer vision