{"title":"从自然语言到图形查询","authors":"Gaétan Hains, Y. Khmelevsky, Thibaut Tachon","doi":"10.1109/CCECE.2019.8861892","DOIUrl":null,"url":null,"abstract":"Automatic code generation can drastically improve software (SW) engineering and SW development projects. In the last decade we have been conducting research which has been advancing the field of code generators for small and mid-size Web-based DBMS systems [4], [5], [7]. We developed a number of tool prototypes for automatic source code debugging by the source-to-source code transformation for real C and C++ applications [8]. Additionally we investigated Natural Language Processing (NLP) for software code generation and application of it to Graph databases. Graph databases are becoming more and more popular for their applications in Artificial Intelligence (AI) systems, social analytics and many other fields. Query languages like Cypher allow users to search them without direct programming. But even queries of modest complexity like “relatives in a family & friends graph” require some skill to write. In this paper we describe the use of natural language as a more intuitive interface for untrained users and demonstrate 3 use-cases, where translation of typical English phrases to OpenCypher and/or specialized graph engines like Huawei EYWA.","PeriodicalId":352860,"journal":{"name":"2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"From natural language to graph queries\",\"authors\":\"Gaétan Hains, Y. Khmelevsky, Thibaut Tachon\",\"doi\":\"10.1109/CCECE.2019.8861892\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automatic code generation can drastically improve software (SW) engineering and SW development projects. In the last decade we have been conducting research which has been advancing the field of code generators for small and mid-size Web-based DBMS systems [4], [5], [7]. We developed a number of tool prototypes for automatic source code debugging by the source-to-source code transformation for real C and C++ applications [8]. Additionally we investigated Natural Language Processing (NLP) for software code generation and application of it to Graph databases. Graph databases are becoming more and more popular for their applications in Artificial Intelligence (AI) systems, social analytics and many other fields. Query languages like Cypher allow users to search them without direct programming. But even queries of modest complexity like “relatives in a family & friends graph” require some skill to write. In this paper we describe the use of natural language as a more intuitive interface for untrained users and demonstrate 3 use-cases, where translation of typical English phrases to OpenCypher and/or specialized graph engines like Huawei EYWA.\",\"PeriodicalId\":352860,\"journal\":{\"name\":\"2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCECE.2019.8861892\",\"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 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE.2019.8861892","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic code generation can drastically improve software (SW) engineering and SW development projects. In the last decade we have been conducting research which has been advancing the field of code generators for small and mid-size Web-based DBMS systems [4], [5], [7]. We developed a number of tool prototypes for automatic source code debugging by the source-to-source code transformation for real C and C++ applications [8]. Additionally we investigated Natural Language Processing (NLP) for software code generation and application of it to Graph databases. Graph databases are becoming more and more popular for their applications in Artificial Intelligence (AI) systems, social analytics and many other fields. Query languages like Cypher allow users to search them without direct programming. But even queries of modest complexity like “relatives in a family & friends graph” require some skill to write. In this paper we describe the use of natural language as a more intuitive interface for untrained users and demonstrate 3 use-cases, where translation of typical English phrases to OpenCypher and/or specialized graph engines like Huawei EYWA.
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