A Parametric Network Approach for Concepts Hierarchy Generation in Text Corpus

Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica

Parpalea M. M.¹  Sângeorzan L. S.²  Parpalea M.³ 

[1] Faculty of Letters, Transilvania University of Brasov, Eroilor blvd 25, 500030 Brasov, Romania;Faculty of Mathematics and Computer Science, Transilvania University of Brasov, Eroilor blvd 25, 500030 Brasov, Romania;National College Andrei Şaguna, Şaguna str. 1, 590000, Brasov, Romania;

关键词: parametric maximum ow;    bipartite network;    preflow bipush-relabel algorithm;    text corpus;    concepts hierarchy;    taxonomy;    primary 90b10;    90c35;    secondary 90c47;    05c35;    68r10;   

DOI  :  10.1515/auom-2016-0022

来源: DOAJ

【 摘 要 】

The article presents a preflow approach for the parametric maximum flow problem, derived from the rules of constructing concepts hierarchy in text corpus. Just as generating a taxonomy can be equivalently reduced to ranking concepts within a text corpus according to a defined criterion, the proposed preflow bipush-relabel algorithm computes the maximum flow - the optimum ow that respects certain ranking constraints. The parametric preflow algorithm for generating two level concepts hierarchy in text corpus works in a parametric bipartite association network and, on each step, the maximum possible amount of ow is pushed along conditional augmenting two-arcs directed paths in the parametric residual network, for the maximum interval of the parameter values. The obtained parametric maximum ow generates concepts hierarchies (taxonomies) in text corpus for different degrees of association values described by the parameter values.

【 授权许可】

Unknown