{"title":"利用自然语言数据库查询接口(NLDQ)实现数据检索的简单指南","authors":"Tameem Ahmad, Nesar Ahmad","doi":"10.1109/SMART46866.2019.9117501","DOIUrl":null,"url":null,"abstract":"Natural Language Database Query (NLDQ) Processing is to make the system able to understand queries in natural language like in English, French or any other language sentence, which is to be interpreted by the system and a corresponding action triggered on the underlying database. Asking queries or questions to databases in natural language provides the ease to the user to access and retrieve data, especially for those who are not comfortable with formal query language such as SQL. This paper presents a model that allows users to interact with the database in natural language (in English language) and retrieve information from the relational database. The method is based on the literals of the sentence. This proposed interface allows users to ask queries or questions in natural language (English), which will be transformed into formal query by the system itself, i.e. SQL, which will fire over the underlying Database. The task of NLDQ is to transform the natural language query or question into formal Query Language Statement for information access and retrieval. This task requires the parsing of the input with syntactic understanding by the system. Then the parsed data with syntactic comprehension can be combined with relational database theories for extract the contextual meaning from the query and transforming it into formal database query statement that returns the required information from the associated database. This proposed method does not require all language specifications and grammar rules in the input query.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Simple Guide to Implement Data Retrieval through Natural Language Database Query Interface (NLDQ)\",\"authors\":\"Tameem Ahmad, Nesar Ahmad\",\"doi\":\"10.1109/SMART46866.2019.9117501\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Natural Language Database Query (NLDQ) Processing is to make the system able to understand queries in natural language like in English, French or any other language sentence, which is to be interpreted by the system and a corresponding action triggered on the underlying database. Asking queries or questions to databases in natural language provides the ease to the user to access and retrieve data, especially for those who are not comfortable with formal query language such as SQL. This paper presents a model that allows users to interact with the database in natural language (in English language) and retrieve information from the relational database. The method is based on the literals of the sentence. This proposed interface allows users to ask queries or questions in natural language (English), which will be transformed into formal query by the system itself, i.e. SQL, which will fire over the underlying Database. The task of NLDQ is to transform the natural language query or question into formal Query Language Statement for information access and retrieval. This task requires the parsing of the input with syntactic understanding by the system. Then the parsed data with syntactic comprehension can be combined with relational database theories for extract the contextual meaning from the query and transforming it into formal database query statement that returns the required information from the associated database. This proposed method does not require all language specifications and grammar rules in the input query.\",\"PeriodicalId\":328124,\"journal\":{\"name\":\"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMART46866.2019.9117501\",\"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 8th International Conference System Modeling and Advancement in Research Trends (SMART)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMART46866.2019.9117501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Simple Guide to Implement Data Retrieval through Natural Language Database Query Interface (NLDQ)
Natural Language Database Query (NLDQ) Processing is to make the system able to understand queries in natural language like in English, French or any other language sentence, which is to be interpreted by the system and a corresponding action triggered on the underlying database. Asking queries or questions to databases in natural language provides the ease to the user to access and retrieve data, especially for those who are not comfortable with formal query language such as SQL. This paper presents a model that allows users to interact with the database in natural language (in English language) and retrieve information from the relational database. The method is based on the literals of the sentence. This proposed interface allows users to ask queries or questions in natural language (English), which will be transformed into formal query by the system itself, i.e. SQL, which will fire over the underlying Database. The task of NLDQ is to transform the natural language query or question into formal Query Language Statement for information access and retrieval. This task requires the parsing of the input with syntactic understanding by the system. Then the parsed data with syntactic comprehension can be combined with relational database theories for extract the contextual meaning from the query and transforming it into formal database query statement that returns the required information from the associated database. This proposed method does not require all language specifications and grammar rules in the input query.