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

With the popularity of the Internet, Internet Protocol Television (IPTV) has been replacing traditional TV and recommendation systems can help IPTV users to choose programs that may interest them. Compared with other recommendations (e.g., movies), IPTV recommendation suffers from a multi-member problem — more than one family members in a household share TV. Because family members can have different tastes, this problem makes recommendations less accurate for IPTV. We propose a virtual user approach to solve this problem. We virtualize two virtual users in a household — Kid and Adult. We have integrated virtual users into both content-based and collaborative filtering recommendation approaches. Experimental results on a real IPTV dataset show that the proposed approaches perform better than the recommendation algorithms without virtual users.

Tackling Multi-member Problem in IPTV Recommendation with Virtual Users