Algorithm based on modified angle‐based outlier factor for open‐set classification of text documents

Walkowiak Tomasz; Datko Szymon; Maciejewski Henryk

摘要

Abstract >This paper presents a new method of open‐set classification of text documents, with respect to subject areas. Standard (closed‐set) approaches to text classification involve training classifiers on annotated text corpora, representing a fixed number of subject areas. Such classifiers assign a new document with unknown annotation to one of the trained classes, even if the new document is not related to any class. >We propose a two‐step procedure for open‐set classification. We first use a closed‐set classifier to assign a new document to one of the known classes. Then, we evaluate the (dis)similarity between the document and the chosen class using a novel criterion of outlierness named interquartile ranged angle‐based outlierness factors, which we find effective in high‐dimensional data. Based on this, we can avoid spurious assignment of documents to unrelated subject classes. >We demonstrate the feasibility of this procedure in the task of subject classification of a collection of Wikipedia documents. As compared to the standard closed‐set approach, our open‐set classifier realizes significantly better precision with only small decrease of the recall measure observed in recognition of the tested classes. </abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><abstract xmlns =“http://www.wiley.com/namespaces/wiley”type =“main”xml：lang =“en”zh“xml：id =”asmb2388-abs-abs-0001“> <标题类型=“main”>抽象</ title> >本文介绍了关于主题领域的文本文件的开放式分类的新方法。文本分类的标准（封闭式）方法涉及培训批评文本语料库的分类器，代表固定数量的主题领域。此类分类器为其中一个培训的类分配了一个未知注释的新文档，即使新文档与任何类无关。</ p> >我们提出了一个用于开放式分类的两步过程。我们首先使用封闭式分类器为其中一个已知类分配新文档。然后，我们使用名为基于角度范围的角度的异常因素的新颖性差异的新颖的差异的新标准评估文档和所选类之间的（DIS）相似性，我们在高维数据中找到有效。基于此，我们可以避免对不相关的主题类的文档的虚假分配。</ p> >我们展示了这个程序在主题分类的任务中的可行性维基百科文件。与标准闭合方法相比，我们的开放式分类器实现了明显更好的精度，仅在识别测试类中观察到的召回量度的少量减少。</ p> </摘要> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" >著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-19344/'>《Applied stochastic models in business and industry》</a> <b style="margin: 0 2px;">|</b><span>2018年第5期</span><b style="margin: 0 2px;">|</b><span>共12页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Walkowiak Tomasz&option=202" target="_blank" rel="nofollow">Walkowiak Tomasz;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Datko Szymon&option=202" target="_blank" rel="nofollow">Datko Szymon;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Maciejewski Henryk&option=202" target="_blank" rel="nofollow">Maciejewski Henryk;</a> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> <p>Department of Computer EngineeringWroc?aw University of Science and TechnologyWroc?aw Poland;</p> <p>Department of Computer EngineeringWroc?aw University of Science and TechnologyWroc?aw Poland;</p> <p>Department of Computer EngineeringWroc?aw University of Science and TechnologyWroc?aw Poland;</p> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li > <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span><a href="https://www.zhangqiaokeyan.com/clc/1147.html" title="应用数学">应用数学;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=high‐dimensional data&option=203" rel="nofollow">high‐dimensional data;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=machine learning&option=203" rel="nofollow">machine learning;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=open‐set classification&option=203" rel="nofollow">open‐set classification;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=outlier detection&option=203" rel="nofollow">outlier detection;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=text mining&option=203" rel="nofollow">text mining;</a> </p> <div class="translation"> 机译：高维数据;机器学习;开放式分类;异常检测;文本挖掘; </div> </li> </ul> </div> </div> <div class="literature cardcommon"> <div class="similarity "> <h3 class="all_title" id="enpatent66">相似文献</h3> <div class="similaritytab clearfix"> <ul> <li class="active" >外文文献</li> <li >中文文献</li> <li >专利</li> </ul> </div> <div class="similarity_details"> <ul > <li> <div> <b>1. </b><a class="enjiyixqcontent" href="/journal-foreign-detail/0704022680240.html">Algorithm based on modified angle‐based outlier factor for open‐set classification of text documents</a> <b>[J]</b> . <span> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Walkowiak Tomasz&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor">Walkowiak Tomasz,</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Datko Szymon&option=202" target="_blank" rel="nofollow" class="tuijian_auth tuijian_authcolor">Datko Szymon,</a> <a 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