English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The similarity and correlation analysis of word concepts has a wide range of applications in natural language processing, and has important research significance in information retrieval, text classification, data mining, and other application fields. This paper analyzes and summarizes the information of sememes relationship through the definition of words in HowNet and proposes a method to distinguish the similarity and correlation of words. Firstly, using a combination of the part of speech and sememes to distinguish the similarity and correlation between words concept. Secondly, the similarity and correlation calculation results between vocabulary concepts are used to further optimize the judgment results. Finally, the similarity and correlation distinction and discrimination between vocabulary concepts are realized. The experimental results show that the method reduces the complexity of the algorithm and greatly improves the work efficiency. The semantic similarity and correlation judgment results are more in line with the human intuitive experience and improve the accuracy of computer understanding of natural language. which provides an important theoretical basis for the development of natural language.

A conceptual similarity and correlation discrimination method based on HowNet