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/

Zendy Plus

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

Zendy Tools

Zendy Open

Large quantifies of online user activity data, such as weekly web searchvolumes, which co-evolve with the mutual influence of several queries andlocations, serve as an important social sensor. It is an important task toaccurately forecast the future activity by discovering latent interactions fromsuch data, i.e., the ecosystems between each query and the flow of influencesbetween each area. However, this is a difficult problem in terms of dataquantity and complex patterns covering the dynamics. To tackle the problem, wepropose FluxCube, which is an effective mining method that forecasts largecollections of co-evolving online user activity and provides goodinterpretability. Our model is the expansion of a combination of twomathematical models: a reaction-diffusion system provides a framework formodeling the flow of influences between local area groups and an ecologicalsystem models the latent interactions between each query. Also, by leveragingthe concept of physics-informed neural networks, FluxCube achieves highinterpretability obtained from the parameters and high forecasting performance,together. Extensive experiments on real datasets showed that FluxCubeoutperforms comparable models in terms of the forecasting accuracy, and eachcomponent in FluxCube contributes to the enhanced performance. We then showsome case studies that FluxCube can extract useful latent interactions betweenqueries and area groups.

Mining Reaction and Diffusion Dynamics in Social Activities