An Innovative Graph-Based Approach to Advance Feature Selection from Multiple Textual Documents

机译：一种基于图的创新方法，可以从多个文本文档中选择特征

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摘要

This paper introduces a novel graph-based approach to select features from multiple textual documents. The proposed solution enables the investigation of the importance of a term into a whole corpus of documents by utilizing contemporary graph theory methods, such as community detection algorithms and node centrality measures. Compared to well-tried existing solutions, evaluation results show that the proposed approach increases the accuracy of most text classifiers employed and decreases the number of features required to achieve 'state-of-the-art' accuracy. Well-known datasets used for the experimentations reported in this paper include 20Newsgroups. LingSpam, Amazon Reviews and Reuters.

机译：本文介绍了一种基于图形的新颖方法，可以从多个文本文档中选择特征。所提出的解决方案能够通过利用当代的图论方法（例如社区检测算法和节点中心度度量）来研究术语在整个文档集中的重要性。与经过充分验证的现有解决方案相比，评估结果表明，该方法提高了大多数采用的文本分类器的准确性，并减少了实现“最先进”准确性所需的功能数量。本文报道的用于实验的著名数据集包括20个新闻组。 LingSpam，亚马逊评论和路透社。

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《IFIP WG 12.5 International workshops on artificial intelligence applications and innovations;Mining Humanistic Data Workshop;Workshop on 5G-Putting Intelligence to the Network Edge》|2020年|96-106|共11页
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Nikolaos Giarelis; Nikos Kanakaris; Nikos Karacapilidis;
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Feature selection; Graph-based text representation; Document clustering; Text mining; Natural Language Processing;

机译：功能选择;基于图的文本表示;文档聚类;文本挖掘;自然语言处理;

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专利

1. Graph-based low complexity detection algorithms in multiple-input-multiple-out systems: an edge selection approach [J] . Lv, T., Long, Communications, IET . 2013,第12期

机译：多输入多输出系统中基于图的低复杂度检测算法：一种边缘选择方法
2. A new approach for textual feature selection based on N-composite isolated labels [J] . Natural language engineering . 2020,第PTa2期

机译：基于N个复合隔离标签的文本特征选择新方法
3. A graph-based approach for feature selection from higher order correlations [J] . Sunanda Das, Asit Kumar Das International journal of computational systems engineering . 2018,第1期

机译：基于图的方法从高阶相关中选择特征
4. An approach to graph-based analysis of textual Documents [C] . Antoon Bronselaer, Gabriella Pasi Conference of the European Society for Fuzzy Logic and Technology . 2013

机译：基于图形的文本文档分析方法
5. XML document classification using structural and textual features. [D] . Khabbazhaye Tajer, Mohammad. 2008

机译：使用结构和文本功能对XML文档进行分类。
6. An Innovative Graph-Based Approach to Advance Feature Selection from Multiple Textual Documents [O] . Nikolaos Giarelis, Nikos Kanakaris, Nikos Karacapilidis -1

机译：一种基于图的创新方法可以从多个文本文档中选择特征
7. An Innovative Graph-Based Approach to Advance Feature Selection from Multiple Textual Documents [O] . Nikolaos Giarelis, Nikos Kanakaris, Nikos Karacapilidis 2020

机译：一种基于图形的基于图形的方法，可以从多个文本文档前进的功能选择
8. Rough Set Feature Selection Algorithms for Textual Case-Based Classification. [R] . Gupta, K. M., Aha, D. W., Moore, P. 2006

机译：基于文本案例分类的粗糙集特征选择算法。

An Innovative Graph-Based Approach to Advance Feature Selection from Multiple Textual Documents

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