{"title":"利用自然语言的核心属性来优化信息处理的原因","authors":"A. Sciullo","doi":"10.1109/SoMeT.2013.6645660","DOIUrl":null,"url":null,"abstract":"We focus on a property of natural language enabling the processing of information conveyed by linguistic expressions: structural asymmetry. We provide evidence that structural asymmetry is a property of argument structure. We focus on Information Retrieval and Question Answering systems and we provide evidence that these systems fail to recover natural language argument structure asymmetrical relations and thus they may fail to retrieve relevant documents from large databases and to provide relevant answers to questions. The processing of the underlying asymmetric relations will contribute to the optimization of Information Retrieval and Question Answering systems.","PeriodicalId":447065,"journal":{"name":"2013 IEEE 12th International Conference on Intelligent Software Methodologies, Tools and Techniques (SoMeT)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A reason to optimize information processing with a core property of natural language\",\"authors\":\"A. Sciullo\",\"doi\":\"10.1109/SoMeT.2013.6645660\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We focus on a property of natural language enabling the processing of information conveyed by linguistic expressions: structural asymmetry. We provide evidence that structural asymmetry is a property of argument structure. We focus on Information Retrieval and Question Answering systems and we provide evidence that these systems fail to recover natural language argument structure asymmetrical relations and thus they may fail to retrieve relevant documents from large databases and to provide relevant answers to questions. The processing of the underlying asymmetric relations will contribute to the optimization of Information Retrieval and Question Answering systems.\",\"PeriodicalId\":447065,\"journal\":{\"name\":\"2013 IEEE 12th International Conference on Intelligent Software Methodologies, Tools and Techniques (SoMeT)\",\"volume\":\"191 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 12th International Conference on Intelligent Software Methodologies, Tools and Techniques (SoMeT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SoMeT.2013.6645660\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 12th International Conference on Intelligent Software Methodologies, Tools and Techniques (SoMeT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SoMeT.2013.6645660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A reason to optimize information processing with a core property of natural language
We focus on a property of natural language enabling the processing of information conveyed by linguistic expressions: structural asymmetry. We provide evidence that structural asymmetry is a property of argument structure. We focus on Information Retrieval and Question Answering systems and we provide evidence that these systems fail to recover natural language argument structure asymmetrical relations and thus they may fail to retrieve relevant documents from large databases and to provide relevant answers to questions. The processing of the underlying asymmetric relations will contribute to the optimization of Information Retrieval and Question Answering systems.