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

In this paper,we proposed novel method that is ProMiSH (Projection and Multi Scale Hashing) that uses random projection and hash-based index structure. Consider object that are embedded in vector space and tagged with keywords. By using this algorithm we find tightest group of keyword as well as we use five different method i.e Euclidean Distance, Jaccard Distance, Cosine Similarity and correlation Distance for finding more accurate result. ProMiSH has up to 60 time faster as compare to the State-of-the art tee-based techniques. In this system study nearest keyword queries on text reach multidimensional dataset. Keywords— Multi-dimensional data, Indexing, Hashing, Querying, projection

Using Novel Method ProMiSH Search Nearest Keyword Set In Multidimensional Dataset