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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

With the rapid development of big data , various big data applications are now in service in different fields. Typical big data applications , such as online shopping and retailing platform , face recognition system , intelligent decision system,self-help service system,medical treatment system make daily life more convenient. Search system is one of the most used big data applications. However , search system varies in different platforms , and there are few standards for it. The quality of search system is hard to assure and validate. Search engine for online shopping systems combines text search and classification-based retrieval comparing to common text search engines. It is harder to validate and e飞raluate quality of it. Through studying on search system of online shopping platform, some quality factors and relational implementation algorithm were provided in this paper to validate and evaluate shopping system search engines. Experiments were also carried out to assure the correctness of the quality index.

网购平台搜索功能的质量评估方法研究 (Research on Quality Evaluation Approaches for Search Function of Online Shopping Platforms).