An Empirical Evaluation of Document Embeddings and Similarity Metrics for Scientific Articles
The comparison of documents—such as articles or patents search, bibliography recommendations systems, visualization of document collections, etc.—has a wide range of applications in several fields. One of the key tasks that such problems have in common is the evaluation of a similarity metric. Many...
Main Authors: | Joaquin Gómez, Pere-Pau Vázquez |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-06-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/11/5664 |
Similar Items
-
A Semantic and Syntactic Similarity Measure for Political Tweets
by: Claire Little, et al.
Published: (2020-01-01) -
Graph Embedding with Similarity Metric Learning
by: Tao Tao, et al.
Published: (2023-08-01) -
Experimental Comparison of Pre-Trained Word Embedding Vectors of Word2Vec, Glove, FastText for Word Level Semantic Text Similarity Measurement in Turkish
by: Cagatay Neftali Tulu
Published: (2022-10-01) -
A Comparison of Approaches for Measuring the Semantic Similarity of Short Texts Based on Word Embeddings
by: Karlo Babić, et al.
Published: (2020-01-01) -
Evaluating keyphrase extraction algorithms for finding similar news articles using lexical similarity calculation and semantic relatedness measurement by word embedding
by: Talha Bin Sarwar, et al.
Published: (2022-07-01)