Hierarchical text classification and evaluation

By Aixin Sun, Ee-Peng Lim. 2001

476 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems

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Citations in the corpus

Large-Scale Hierarchical Text Classification with Recursively Regularized Deep Graph-CNN (2018, background): “When there are many labels, hierarchical categorization of texts has been recognized as a natural and effective way to organize texts and it has been well studied in the past two decades [5, 6, 13, 30, 39, 43, 44].”
Support vector machines classification with a very large-scale taxonomy (2005, methodology): “Hierarchical SVMs refer to those methods that decompose the training tasks according to the structure of the taxonomy [4][5][6][10][ 17 ][19].”
Text Classification Algorithms: A Survey (2019, methodology): “Stacking Support Vector Machine (SVM) Stacking SVM is a hierarchical classification method used for category tree structure based on a top-down level-based approach [155].”
Incremental Algorithms for Hierarchical Classification (2004, background): “Learning algorithms for hierarchical classification have been investigated in, e.g., [8] [9] [10] [11] [12] [14] [15] [17] [20].”
Mining Multi-label Data (2010, background): “Several other measures for hierarchical (multi-label) classification are examined in [22, 68].”
A brief survey on sequence classification (2010, methodology): “Text classiflcation has various extensions such as multi-label text classiflcation [67], hierarchical text classiflcation [ 57 ] and semi-supervised text classiflcation [46].”
Concrete compressive strength analysis using a combined classification and regression technique (2012, background): “However, numerous studies show that a hierarchical structure outperforms a flat structure for solving not only classification problems [8,28,33], but also regression problems [1,13,32,38].”
Graph-based term weighting for text categorization (2015, background): “a) Text classification: TC is one of the most fundamental and well studied tasks in text analytics and a number of diverse approaches have been proposed [21], [35], [14], [15], [22], [37], [26], [16], [19].”
HDLTex: Hierarchical Deep Learning for Text Classification (2017, methodology): “The stacking SVM provides an ensemble of individual SVM classifiers and generally produces more accurate results than single-SVM models [29], [30].”