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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper proposes a new approach for Multi-word Expression (MWE)extraction on the motivation of gene sequence alignment because textual sequence is similar to gene sequence in pattern analysis. Theory of Longest Common Subsequence (LCS) originates from computer science and has been established as affine gap model in Bioinformatics. We perform this developed LCS technique combined with linguistic criteria in MWE extraction. In comparison with traditional n-gram method, which is the major technique for MWE extraction, LCS approach is applied with great efficiency and performance guarantee. Experimental results show that LCS-based approach achieves better results than n-gram.

A bio-inspired approach for multi-word expression extraction