Purpose–The purpose of this paper is to show how description logics(DLs)can be applied to formalizing the information bearing capability(IBC)of paths in entity-relationship(ER)schemata.Design/methodology/approach–Th...Purpose–The purpose of this paper is to show how description logics(DLs)can be applied to formalizing the information bearing capability(IBC)of paths in entity-relationship(ER)schemata.Design/methodology/approach–The approach follows and extends the idea presented in Xu and Feng(2004),which applies DLs to classifying paths in an ER schema.To verify whether the information content of a data construct(e.g.a path)covers a semantic relation(which formulates a piece of information requirement),the principle of IBC under the source-bearer-receiver framework is presented.It is observed that the IBC principle can be formalized by constructing DL expressions and examining constructors(e.g.quantifiers).Findings–Description logic can be used as a tool to describe the meanings represented by paths in an ER schema and formalize their IBC.The criteria for identifying data construct distinguishability are also discovered by examining quantifiers in DL expressions of paths of an ER schema.Originality/value–This paper focuses on classifying paths in data schemas and verifying their formalized IBC by using DLs and the IBC principle.It is a new point of view for evaluation of data representation,which looks at the information borne by data but not data dependencies.展开更多
Traditional Chinese text retrieval systems return a ranked list of documentsin response to a user''s request. While a ranked list of documents may be an appropriate response forthe user, frequently it is not. ...Traditional Chinese text retrieval systems return a ranked list of documentsin response to a user''s request. While a ranked list of documents may be an appropriate response forthe user, frequently it is not. Usually it would be better for the system to provide the answeritself instead of requiring the user to search for the answer in a set of documents. Since Chinesetext retrieval has just been developed lately, and due to various specific characteristics ofChinese language, the approaches to its retrieval are quite different from those studies andresearches proposed to deal with Western language. Thus, an architecture that augments existingsearch engines is developed to support Chinese natural language question answering. In this paper anew approach to building Chinese question-answering system is described, which is thegeneral-purpose, fully-automated Chinese quest ion-answering system available on the web. In theapproach, we attempt to represent Chinese text by its characteristics, and try to convert theChinese text into ERE (E: entity, R: relation) relation data lists, and then to answer the questionthrough ERE relation model. The system performs quite well giving the simplicity of the techniquesbeing utilized. Experimental results show that question-answering accuracy can be greatly improvedby analyzing more and more matching ERE relation data lists. Simple ERE relation data extractiontechniques work well in our system making it efficient to use with many backend retrieval engines.展开更多
基金This work has been funded by Scientific Research Common Program of Beijing Municipal Commission of Education(No.KM201311417011)the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions(No.CIT&TCD201404089)Funding project of Beijing Philosophy and Social Science Research Program(No.11JGB039).
文摘Purpose–The purpose of this paper is to show how description logics(DLs)can be applied to formalizing the information bearing capability(IBC)of paths in entity-relationship(ER)schemata.Design/methodology/approach–The approach follows and extends the idea presented in Xu and Feng(2004),which applies DLs to classifying paths in an ER schema.To verify whether the information content of a data construct(e.g.a path)covers a semantic relation(which formulates a piece of information requirement),the principle of IBC under the source-bearer-receiver framework is presented.It is observed that the IBC principle can be formalized by constructing DL expressions and examining constructors(e.g.quantifiers).Findings–Description logic can be used as a tool to describe the meanings represented by paths in an ER schema and formalize their IBC.The criteria for identifying data construct distinguishability are also discovered by examining quantifiers in DL expressions of paths of an ER schema.Originality/value–This paper focuses on classifying paths in data schemas and verifying their formalized IBC by using DLs and the IBC principle.It is a new point of view for evaluation of data representation,which looks at the information borne by data but not data dependencies.
文摘Traditional Chinese text retrieval systems return a ranked list of documentsin response to a user''s request. While a ranked list of documents may be an appropriate response forthe user, frequently it is not. Usually it would be better for the system to provide the answeritself instead of requiring the user to search for the answer in a set of documents. Since Chinesetext retrieval has just been developed lately, and due to various specific characteristics ofChinese language, the approaches to its retrieval are quite different from those studies andresearches proposed to deal with Western language. Thus, an architecture that augments existingsearch engines is developed to support Chinese natural language question answering. In this paper anew approach to building Chinese question-answering system is described, which is thegeneral-purpose, fully-automated Chinese quest ion-answering system available on the web. In theapproach, we attempt to represent Chinese text by its characteristics, and try to convert theChinese text into ERE (E: entity, R: relation) relation data lists, and then to answer the questionthrough ERE relation model. The system performs quite well giving the simplicity of the techniquesbeing utilized. Experimental results show that question-answering accuracy can be greatly improvedby analyzing more and more matching ERE relation data lists. Simple ERE relation data extractiontechniques work well in our system making it efficient to use with many backend retrieval engines.
