Md. Kowsher, M. A. Alam, M. J. Uddin, Md. Rafiqul Islam, Nuruzzaman Pias, Abu Rayhan Md Saifullah
{"title":"孟加拉语信息聊天机器人","authors":"Md. Kowsher, M. A. Alam, M. J. Uddin, Md. Rafiqul Islam, Nuruzzaman Pias, Abu Rayhan Md Saifullah","doi":"10.1109/IC4ME247184.2019.9036585","DOIUrl":null,"url":null,"abstract":"Bengali Informative Chatbot (BIC) is an effective technique that helps a user to trace relevant information by Natural Language Processing (NLP). In this research paper, we introduce an algorithmic Bengali Informative Chatbot (BIC) based on information that is significant mathematically and statistically. This paper is demonstrated by two algorithms for finding out the lemmatization of Bengali words such as Trie and Dictionary Based Search by Removing Affix (DBSRA) as well as compared with Edit Distance for the exact lemmatization. We present the Bengali Anaphora resolution system using the Hobbs’ algorithm to get the correct expression of information. As the actions of chatbot replying algorithms, the TF-IDF and Cosine Similarity are developed to find out the accurate answer from the documents. In this study, we introduce a Bengali Language Toolkit (BLTK) and Bengali Language Expression (BRE) that make the easiest implication of our task. We have also developed Bengali root word’s corpus, synonym word’s corpus, stop word’s corpus and gathered 672 articles as questions and answers form the popular Bengali newspapers ‘The Daily Prothom Alo’ is our inserted information. For testing this system, we have created 19334 questions from the introduced information and got 97.22% accurate answer by proposed BIC.","PeriodicalId":368690,"journal":{"name":"2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)","volume":"222 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Bengali Informative Chatbot\",\"authors\":\"Md. Kowsher, M. A. Alam, M. J. Uddin, Md. Rafiqul Islam, Nuruzzaman Pias, Abu Rayhan Md Saifullah\",\"doi\":\"10.1109/IC4ME247184.2019.9036585\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bengali Informative Chatbot (BIC) is an effective technique that helps a user to trace relevant information by Natural Language Processing (NLP). In this research paper, we introduce an algorithmic Bengali Informative Chatbot (BIC) based on information that is significant mathematically and statistically. This paper is demonstrated by two algorithms for finding out the lemmatization of Bengali words such as Trie and Dictionary Based Search by Removing Affix (DBSRA) as well as compared with Edit Distance for the exact lemmatization. We present the Bengali Anaphora resolution system using the Hobbs’ algorithm to get the correct expression of information. As the actions of chatbot replying algorithms, the TF-IDF and Cosine Similarity are developed to find out the accurate answer from the documents. In this study, we introduce a Bengali Language Toolkit (BLTK) and Bengali Language Expression (BRE) that make the easiest implication of our task. We have also developed Bengali root word’s corpus, synonym word’s corpus, stop word’s corpus and gathered 672 articles as questions and answers form the popular Bengali newspapers ‘The Daily Prothom Alo’ is our inserted information. For testing this system, we have created 19334 questions from the introduced information and got 97.22% accurate answer by proposed BIC.\",\"PeriodicalId\":368690,\"journal\":{\"name\":\"2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)\",\"volume\":\"222 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC4ME247184.2019.9036585\",\"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 Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC4ME247184.2019.9036585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bengali Informative Chatbot (BIC) is an effective technique that helps a user to trace relevant information by Natural Language Processing (NLP). In this research paper, we introduce an algorithmic Bengali Informative Chatbot (BIC) based on information that is significant mathematically and statistically. This paper is demonstrated by two algorithms for finding out the lemmatization of Bengali words such as Trie and Dictionary Based Search by Removing Affix (DBSRA) as well as compared with Edit Distance for the exact lemmatization. We present the Bengali Anaphora resolution system using the Hobbs’ algorithm to get the correct expression of information. As the actions of chatbot replying algorithms, the TF-IDF and Cosine Similarity are developed to find out the accurate answer from the documents. In this study, we introduce a Bengali Language Toolkit (BLTK) and Bengali Language Expression (BRE) that make the easiest implication of our task. We have also developed Bengali root word’s corpus, synonym word’s corpus, stop word’s corpus and gathered 672 articles as questions and answers form the popular Bengali newspapers ‘The Daily Prothom Alo’ is our inserted information. For testing this system, we have created 19334 questions from the introduced information and got 97.22% accurate answer by proposed BIC.