{"title":"基于机器学习模型的文本文档信息检索性能评价","authors":"Subhasish Chowdhury, Suresh Kumar","doi":"10.1109/ICDT57929.2023.10150858","DOIUrl":null,"url":null,"abstract":"Text mining is thought to have a high commercial potential due to the significant amounts of unstructured text data produced on the Internet. The practice of obtaining previously undiscovered, comprehensible, potentially useful patterns or knowledge from a corpus of text data is known as text mining. In this study, we attempt to extract the structured information from the text and then use various machine-learning models to categorize the data. We then look for the model that provides the highest level of classification accuracy.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance Evaluation of Text Document Using Machine Learning Models for Information Retrieval\",\"authors\":\"Subhasish Chowdhury, Suresh Kumar\",\"doi\":\"10.1109/ICDT57929.2023.10150858\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Text mining is thought to have a high commercial potential due to the significant amounts of unstructured text data produced on the Internet. The practice of obtaining previously undiscovered, comprehensible, potentially useful patterns or knowledge from a corpus of text data is known as text mining. In this study, we attempt to extract the structured information from the text and then use various machine-learning models to categorize the data. We then look for the model that provides the highest level of classification accuracy.\",\"PeriodicalId\":266681,\"journal\":{\"name\":\"2023 International Conference on Disruptive Technologies (ICDT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Disruptive Technologies (ICDT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDT57929.2023.10150858\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Disruptive Technologies (ICDT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDT57929.2023.10150858","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance Evaluation of Text Document Using Machine Learning Models for Information Retrieval
Text mining is thought to have a high commercial potential due to the significant amounts of unstructured text data produced on the Internet. The practice of obtaining previously undiscovered, comprehensible, potentially useful patterns or knowledge from a corpus of text data is known as text mining. In this study, we attempt to extract the structured information from the text and then use various machine-learning models to categorize the data. We then look for the model that provides the highest level of classification accuracy.