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

In the present paper, we consider a graph mining problem of enumerating what we call connectors. Suppose that we are given a data set (G, I, σ) that consists of a graph G = (V,E), an item set I, and a function σ : V → 2I . For X ⊆ V , we define Aσ(X) ≜ ∩ v∈X σ(v). Note that, for X,Y ⊆ V , X ⊆ Y implies that Aσ(X) ⊇ Aσ(Y ). A vertex subset X is called a connector if (i) the subgraph G[X] induced from G by X is connected; and (ii) for any v ∈ V \X, G[X∪{v}] is disconnected or Aσ(X∪{v}) ⊊ Aσ(X). To enumerate all connectors, we propose a novel algorithm named COOMA (components overlaid mining algorithm). Interestingly, COOMA is a total-polynomial time algorithm, i.e., the running time is polynomially bounded with respect to the input and output size. We show the efficiency of COOMA in comparison with COPINE [Sese et al., 2010], a depth-first-search based algorithm.

COOMA: A Components Overlaid Mining Algorithm for Enumerating Connected Subgraphs with Common Itemsets