{"title":"基于长短期记忆递归神经网络的上下文深度搜索","authors":"Mohammad Arifur Rahman, Fahad Ahmed, Nafis Ali","doi":"10.1109/ICREST.2019.8644508","DOIUrl":null,"url":null,"abstract":"The internet is teeming with an ocean worth of information and combing through all that in order to find what one wants can become a daunting task if one does not possess the right tools and techniques. This paper explores one such technique, exploiting the rapidly responsive Long-Short Term Memory Recurrent Neural Networks (LSTM-RNNs) by harnessing the machine learning capabilities of neural networks and eventually, provides contextual search results at the finger tips of the user of the system.","PeriodicalId":108842,"journal":{"name":"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Contextual Deep Search using Long Short Term Memory Recurrent Neural Network\",\"authors\":\"Mohammad Arifur Rahman, Fahad Ahmed, Nafis Ali\",\"doi\":\"10.1109/ICREST.2019.8644508\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The internet is teeming with an ocean worth of information and combing through all that in order to find what one wants can become a daunting task if one does not possess the right tools and techniques. This paper explores one such technique, exploiting the rapidly responsive Long-Short Term Memory Recurrent Neural Networks (LSTM-RNNs) by harnessing the machine learning capabilities of neural networks and eventually, provides contextual search results at the finger tips of the user of the system.\",\"PeriodicalId\":108842,\"journal\":{\"name\":\"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)\",\"volume\":\"96 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICREST.2019.8644508\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICREST.2019.8644508","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Contextual Deep Search using Long Short Term Memory Recurrent Neural Network
The internet is teeming with an ocean worth of information and combing through all that in order to find what one wants can become a daunting task if one does not possess the right tools and techniques. This paper explores one such technique, exploiting the rapidly responsive Long-Short Term Memory Recurrent Neural Networks (LSTM-RNNs) by harnessing the machine learning capabilities of neural networks and eventually, provides contextual search results at the finger tips of the user of the system.