{"title":"Nearness as context-dependent expression: an integrative review of modeling, measurement and contextual properties","authors":"Marc Novel, R. Grütter, H. Boley, A. Bernstein","doi":"10.1080/13875868.2020.1754832","DOIUrl":null,"url":null,"abstract":"ABSTRACT Nearness expressions such as “near” are context-dependent spatial relations and are subject to the context variability effect. Depending on the provided context, “near” has a different semantic extension. We perform a literature review to identify the effect of context on “near”. To integrate the insights from different disciplines, we apply Turney’s contextualization framework which distinguishes between two types of features: primary and contextual. Primary features are the qualitative and quantitative distance measures and contextual features are the context factors used to determine a threshold on the nearness measurements. Additionally, we identify the appropriate features for different spatial tasks discussed in the literature. By doing so, we seek to build a foundation for a context-dependent model for “near”.","PeriodicalId":46199,"journal":{"name":"Spatial Cognition and Computation","volume":"13 1","pages":"161 - 233"},"PeriodicalIF":1.6000,"publicationDate":"2020-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spatial Cognition and Computation","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1080/13875868.2020.1754832","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
引用次数: 1
Abstract
ABSTRACT Nearness expressions such as “near” are context-dependent spatial relations and are subject to the context variability effect. Depending on the provided context, “near” has a different semantic extension. We perform a literature review to identify the effect of context on “near”. To integrate the insights from different disciplines, we apply Turney’s contextualization framework which distinguishes between two types of features: primary and contextual. Primary features are the qualitative and quantitative distance measures and contextual features are the context factors used to determine a threshold on the nearness measurements. Additionally, we identify the appropriate features for different spatial tasks discussed in the literature. By doing so, we seek to build a foundation for a context-dependent model for “near”.