{"title":"基于递归神经网络的标题生成","authors":"Yuko Hayashi, H. Yanagimoto","doi":"10.1109/IIAI-AAI.2016.109","DOIUrl":null,"url":null,"abstract":"We proposed a title generation method with a recurrent neural network using concepts of machine translation. The title generator consists of an encoder and a decoder and they are constructed with Long Short Term Memory, which is one of the recurrent neural networks. We construct a distributed representation of an article in the encoder and the decoder generates a title without extraction of an article. In some evaluational experiments we confirmed that our proposed method could generate appropriate titles from articles but in some articles the method generate random titles.","PeriodicalId":272739,"journal":{"name":"2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Title Generation with Recurrent Neural Network\",\"authors\":\"Yuko Hayashi, H. Yanagimoto\",\"doi\":\"10.1109/IIAI-AAI.2016.109\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We proposed a title generation method with a recurrent neural network using concepts of machine translation. The title generator consists of an encoder and a decoder and they are constructed with Long Short Term Memory, which is one of the recurrent neural networks. We construct a distributed representation of an article in the encoder and the decoder generates a title without extraction of an article. In some evaluational experiments we confirmed that our proposed method could generate appropriate titles from articles but in some articles the method generate random titles.\",\"PeriodicalId\":272739,\"journal\":{\"name\":\"2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IIAI-AAI.2016.109\",\"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 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAI-AAI.2016.109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We proposed a title generation method with a recurrent neural network using concepts of machine translation. The title generator consists of an encoder and a decoder and they are constructed with Long Short Term Memory, which is one of the recurrent neural networks. We construct a distributed representation of an article in the encoder and the decoder generates a title without extraction of an article. In some evaluational experiments we confirmed that our proposed method could generate appropriate titles from articles but in some articles the method generate random titles.