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

Multi-Sentence Compression (MSC) aims to generate a short sentence with thekey information from a cluster of similar sentences. MSC enables summarizationand question-answering systems to generate outputs combining fully formedsentences from one or several documents. This paper describes an Integer LinearProgramming method for MSC using a vertex-labeled graph to select differentkeywords, with the goal of generating more informative sentences whilemaintaining their grammaticality. Our system is of good quality and outperformsthe state of the art for evaluations led on news datasets in three languages:French, Portuguese and Spanish. We led both automatic and manual evaluations todetermine the informativeness and the grammaticality of compressions for eachdataset. In additional tests, which take advantage of the fact that the lengthof compressions can be modulated, we still improve ROUGE scores with shorteroutput sentences.

A Multilingual Study of Multi-Sentence Compression using Word Vertex-Labeled Graphs and Integer Linear Programming