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

As a trending approach for social event detection, graph neural network(GNN)-based methods enable a fusion of natural language semantics and thecomplex social network structural information, thus showing SOTA performance.However, GNN-based methods can miss useful message correlations. Moreover, theyrequire manual labeling for training and predetermining the number of eventsfor prediction. In this work, we address social event detection via graphstructural entropy (SE) minimization. While keeping the merits of the GNN-basedmethods, the proposed framework, HISEvent, constructs more informative messagegraphs, is unsupervised, and does not require the number of events given apriori. Specifically, we incrementally explore the graph neighborhoods using1-dimensional (1D) SE minimization to supplement the existing message graphwith edges between semantically related messages. We then detect events fromthe message graph by hierarchically minimizing 2-dimensional (2D) SE. Ourproposed 1D and 2D SE minimization algorithms are customized for social eventdetection and effectively tackle the efficiency problem of the existing SEminimization algorithms. Extensive experiments show that HISEvent consistentlyoutperforms GNN-based methods and achieves the new SOTA for social eventdetection under both closed- and open-set settings while being efficient androbust.

Hierarchical and Incremental Structural Entropy Minimization for Unsupervised Social Event Detection