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

Recently, the community search problem has attracted significant attention,due to its wide spectrum of real-world applications such as event organization,friend recommendation, advertisement in e-commence, and so on. Given a queryvertex, the community search problem finds dense subgraph that contains thequery vertex. In social networks, users have multiple check-in locations,influence score, and profile information (keywords). Most previous studies thatsolve the CS problem over social networks usually neglect such information in acommunity. In this paper, we propose a novel problem, named community searchover spatial-social networks (TCS-SSN), which retrieves community with highsocial influence, small traveling time, and covering certain keywords. In orderto tackle the TCS-SSN problem over the spatial-social networks, we designeffective pruning techniques to reduce the problem search space. We alsopropose an effective indexing mechanism, namely social-spatial index, tofacilitate the community query, and develop an efficient query answeringalgorithm via index traversal. We verify the efficiency and effectiveness ofour pruning techniques, indexing mechanism, and query processing algorithmthrough extensive experiments on real-world and synthetic data sets undervarious parameter settings.

Topic-based Community Search over Spatial-Social Networks (Technical Report)