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

Generally, in the traditional multilingual topic discovery, it is the multilingual text for a single goal of the conversion and then clustering. On this basis, we have constructed a custom dictionary for the people with the highest percentage of Chinese, Japanese and English in this paper. At the same time, we have improved the single-pass clustering algorithm in single language. And considering the characteristics of news effectiveness, we have proposed a multilingual text composite clustering algorithm based on fusion time impact factor, which makes the clustering analysis results more reasonable, and better reflects the characteristics of the effectiveness of network news. 1. Information acquisition pretreatment Given the current, China’s public interest in the main stream media language has the highest rate of Chinese, English and Japanese, while the English itself has been separated by a space between words, and in Chinese and Japanese, the character and the character is adjacent to, the connection between different words, the different connection between the same word can have different meanings. Therefore, how to divide the whole sentence correctly so that each character can be divided into the correct phrase, and then get the correct phrase segmentation, which is the focus of the multilingual information gathering and preprocessing. 1.1The proper noun thesaurus construction Observation of Chinese and Japanese phrase structure, we will find that a large number of corpus will appear a large number of compound nouns,the commonly used word segmentation tools will separate these compound nouns into multiple nouns.The result is, although the identification of each phrase is accurate, ignoring that the original word is a compound noun. Obviously, it is not reasonable to have a long term to be divided into a compound noun, lost the meaning of the original word. In order to solve the above problems, in this paper, the long term compound noun is used as a phrase to be added to the dictionary supported by word segmentation tools, thus, the word segmentation tool will not divide it into a number of phrases. Use the crawler technology of Baidu encyclopedia, the English Wikipedia, and Japan's version of Wikipedia to crawl the data, the process of crawling strategy is shown in Fig.1. Start Import a topic & initialize the climber queue Is end of climb exit Remove the first entry Analyze entry links Add the links to the queue

Research on Document Clustering from Internet Public Opinions