A Random Set and Prototype Theory Model of Linguistic Query Evaluation

Scalable Fuzzy Algorithms for Data Management and Analysis Pub Date : 1900-01-01 DOI:10.4018/978-1-60566-858-1.CH006

J. Lawry, Yongchuan Tang

{"title":"A Random Set and Prototype Theory Model of Linguistic Query Evaluation","authors":"J. Lawry, Yongchuan Tang","doi":"10.4018/978-1-60566-858-1.CH006","DOIUrl":null,"url":null,"abstract":"The term computing with words was introduced by Zadeh (Zadeh 1996), (Zadeh 2002) to refer to computation involving natural language expression and queries. Such an approach allows for a high-level and intuitive representation of information which is vital for the development of transparent humanunderstandable decision making software tools. Zadeh proposed a methodology for computing with words incorporating fuzzy set theory and fuzzy quantifiers. Label semantics (Lawry 2004), (Lawry 2006) is an alternative framework for linguistic modeling based on random set theory and where emphasis is given to decisions concerning the appropriateness of labels to describe a particular instance or object. Recent work has demonstrated a clear and natural link between label semantics and the prototype theory of concepts. In this paper we will propose a new methodology for evaluating queries about a database which involve both linguistic expressions and generalized (linguistic) quantifiers. This approach will be based on the combination of prototype theory and random set theory underlying the interpretation of AbsTRACT","PeriodicalId":293388,"journal":{"name":"Scalable Fuzzy Algorithms for Data Management and Analysis","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scalable Fuzzy Algorithms for Data Management and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-60566-858-1.CH006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

Abstract

The term computing with words was introduced by Zadeh (Zadeh 1996), (Zadeh 2002) to refer to computation involving natural language expression and queries. Such an approach allows for a high-level and intuitive representation of information which is vital for the development of transparent humanunderstandable decision making software tools. Zadeh proposed a methodology for computing with words incorporating fuzzy set theory and fuzzy quantifiers. Label semantics (Lawry 2004), (Lawry 2006) is an alternative framework for linguistic modeling based on random set theory and where emphasis is given to decisions concerning the appropriateness of labels to describe a particular instance or object. Recent work has demonstrated a clear and natural link between label semantics and the prototype theory of concepts. In this paper we will propose a new methodology for evaluating queries about a database which involve both linguistic expressions and generalized (linguistic) quantifiers. This approach will be based on the combination of prototype theory and random set theory underlying the interpretation of AbsTRACT

查看原文本刊更多论文

语言查询评价的随机集和原型理论模型

单词计算这个术语是由Zadeh (Zadeh 1996)， (Zadeh 2002)引入的，指的是涉及自然语言表达式和查询的计算。这种方法允许高层次和直观的信息表示，这对于开发透明的人类可理解的决策软件工具至关重要。Zadeh提出了一种结合模糊集理论和模糊量词的词计算方法。标签语义(Lawry 2004)， (Lawry 2006)是基于随机集理论的语言建模的另一种框架，重点是关于标签描述特定实例或对象的适当性的决策。最近的研究表明，标签语义和概念原型理论之间存在着清晰而自然的联系。在本文中，我们将提出一种新的方法来评估关于数据库的查询，它涉及语言表达式和广义(语言)量词。这种方法将基于原型理论和随机集理论的结合来解释抽象

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Scalable Fuzzy Algorithms for Data Management and Analysis

自引率

0.00%

发文量