基于投影ART神经网络的文本处理

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI:10.1109/NTSP.2016.7747780

R. Forgác, R. Krakovsky

{"title":"基于投影ART神经网络的文本处理","authors":"R. Forgác, R. Krakovsky","doi":"10.1109/NTSP.2016.7747780","DOIUrl":null,"url":null,"abstract":"This paper presents the summary of experience obtained with the modified clustering algorithm of Projective Adaptive Resonance Theory. The algorithm was proposed by authors, and was tested for text processing. Possible usage of the algorithm is exemplified by text document clustering, and generation of keyword dictionaries from text documents.","PeriodicalId":232837,"journal":{"name":"2016 New Trends in Signal Processing (NTSP)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Text processing by using projective ART neural networks\",\"authors\":\"R. Forgác, R. Krakovsky\",\"doi\":\"10.1109/NTSP.2016.7747780\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the summary of experience obtained with the modified clustering algorithm of Projective Adaptive Resonance Theory. The algorithm was proposed by authors, and was tested for text processing. Possible usage of the algorithm is exemplified by text document clustering, and generation of keyword dictionaries from text documents.\",\"PeriodicalId\":232837,\"journal\":{\"name\":\"2016 New Trends in Signal Processing (NTSP)\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 New Trends in Signal Processing (NTSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NTSP.2016.7747780\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 New Trends in Signal Processing (NTSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NTSP.2016.7747780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 5

摘要

本文总结了射影自适应共振理论改进聚类算法的经验。该算法由作者提出，并在文本处理中进行了测试。通过文本文档聚类和从文本文档生成关键字字典来举例说明该算法的可能用途。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Text processing by using projective ART neural networks

This paper presents the summary of experience obtained with the modified clustering algorithm of Projective Adaptive Resonance Theory. The algorithm was proposed by authors, and was tested for text processing. Possible usage of the algorithm is exemplified by text document clustering, and generation of keyword dictionaries from text documents.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2016 New Trends in Signal Processing (NTSP)

自引率

0.00%

发文量