The N-Grams Based Text Similarity Detection Approach Using Self-Organizing Maps and Similarity Measures
In the paper the word-level n-grams based approach is proposed to find similarity between texts. The approach is a combination of two separate and independent techniques: self-organizing map (SOM) and text similarity measures. SOM’s uniqueness is that the obtained results of data clusterin...
Main Authors: | Pavel Stefanovič, Olga Kurasova, Rokas Štrimaitis |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-05-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/9/9/1870 |
Similar Items
-
Measurement of Text Similarity: A Survey
by: Jiapeng Wang, et al.
Published: (2020-08-01) -
The performance of text similarity algorithms
by: Didik Dwi Prasetya, et al.
Published: (2018-03-01) -
Greedy Texts Similarity Mapping
by: Aliya Jangabylova, et al.
Published: (2022-11-01) -
Unlabeled Short Text Similarity With LSTM Encoder
by: Lin Yao, et al.
Published: (2019-01-01) -
A Hierarchical Orthographic Similarity Measure for Interconnected Texts Represented by Graphs
by: Maxime Deforche, et al.
Published: (2024-02-01)