{"title":"基于特征提取模型的改进文档向量空间性能的反馈方法","authors":"Kosuke Takano, Chen Xing, K. Masuda","doi":"10.1109/PACRIM.2007.4313225","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a basic algorithm for an automatic feedback method to reconstruct the document vector space that is developed based on a method referred to as feature extraction model (FEM). In the feedback method, we add and remove some terms that are used to construct the vector space so that retrieval results are improved, because the distributions of document vectors are arranged properly according to purposes of searchers. The efficiency and the feasibility of the proposed method are confirmed by several experiments.","PeriodicalId":395921,"journal":{"name":"2007 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Feedback Method of Improving the Performance of a Document Vector Space Developed on a Feature Extraction Model\",\"authors\":\"Kosuke Takano, Chen Xing, K. Masuda\",\"doi\":\"10.1109/PACRIM.2007.4313225\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a basic algorithm for an automatic feedback method to reconstruct the document vector space that is developed based on a method referred to as feature extraction model (FEM). In the feedback method, we add and remove some terms that are used to construct the vector space so that retrieval results are improved, because the distributions of document vectors are arranged properly according to purposes of searchers. The efficiency and the feasibility of the proposed method are confirmed by several experiments.\",\"PeriodicalId\":395921,\"journal\":{\"name\":\"2007 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACRIM.2007.4313225\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACRIM.2007.4313225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Feedback Method of Improving the Performance of a Document Vector Space Developed on a Feature Extraction Model
In this paper, we propose a basic algorithm for an automatic feedback method to reconstruct the document vector space that is developed based on a method referred to as feature extraction model (FEM). In the feedback method, we add and remove some terms that are used to construct the vector space so that retrieval results are improved, because the distributions of document vectors are arranged properly according to purposes of searchers. The efficiency and the feasibility of the proposed method are confirmed by several experiments.