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Context-aware devices may also try to make assumptions about the user's current situation. Dey (2001) define context as "any information that can be used to characterize the situation of an entity."

Context-aware devices may also try to make assumptions about the user's current situation. Dey (2001) define context as "any information that can be used to characterize the situation of an entity."

在计算机科学中，情景感知指的是计算机既能感知环境，又能根据环境做出反应。设备知道在什么情况下它们能够按照规则或智能刺激进行操作，从而做出相应的反应。在普适计算领域， Schilit 在1994年^[6-7]首次将情景感知引入普适计算领域。情景感知设备也可以尝试对用户的当前情况进行假设。Dey (2001)将情景定义为“可用于描述实体状况的任何信息”^[1]。

在计算机科学中，情景感知指的是计算机既能感知环境，又能根据环境做出反应。设备知道在什么情况下它们能够按照规则或智能刺激进行操作，从而做出相应的反应。在普适计算领域， Schilit 在1994年<ref name="schilit94">{{cite conference

| title = Context-aware computing applications

}}</ref> 首次将情景感知引入普适计算领域。情景感知设备也可以尝试对用户的当前情况进行假设。Dey (2001)将情景定义为“可用于描述实体状况的任何信息”。<ref name="dey2001">{{cite journal

| citeseerx = 10.1.1.31.9786

}}</ref>

While the computer science community initially perceived the context as a matter of user location, as Dey discuss,<ref name="dey2001"/> in the last few years this notion has been considered not simply as a state, but part of a process in which users are involved; thus, sophisticated and general context models have been proposed (see survey<ref name="curino-context2007">{{cite journal  

While the computer science community initially perceived the context as a matter of user location, as Dey discuss,<ref name="dey2001"/> in the last few years this notion has been considered not simply as a state, but part of a process in which users are involved; thus, sophisticated and general context models have been proposed (see survey<ref name="curino-context2007">{{cite journal  

情景相关的人类特征可以被分为3类:用户基本信息（习惯、情绪状态、生物心理状况）、用户社交环境（位置网、社交、群体动态）和用户任务（无意识活动、沉浸式任务、一般任务）。物理环境相关的情景也可以分为3类：位置（绝对位置、相对位置和位置网），设施（周围的计算资源、交流、任务表现）和物理条件（噪音、灯光、压力、空气质量）^[17-18]。'''【位置可能有问题】'''

情景相关的人类特征可以被分为3类:用户基本信息（习惯、情绪状态、生物心理状况）、用户社交环境（位置网、社交、群体动态）和用户任务（无意识活动、沉浸式任务、一般任务）。物理环境相关的情景也可以分为3类：位置（绝对位置、相对位置和位置网），设施（周围的计算资源、交流、任务表现）和物理条件（噪音、灯光、压力、空气质量）^[17-18]。'''【位置可能有问题】'''

== Relational context : dynamic and non-user-centric definitions==

== Relational context : dynamic and non-user-centric definitions==

Whereas early definitions of context tended to center on users, or devices interfaced directly with users, the oft-cited definition from Dey<ref name="dey2001"/> ("''any information that can be used to characterize the situation of an entity''") could be taken without this restriction. User-centric context, as may be used in the design of [[human-computer interaction|human-computer interfaces]], may also imply an overly clearcut, and partially arbitrary,  separation between "content" (anything which is ''explicitly'' typed in by users, or output to them), and context, which is ''implicit'', and used for [[context adaptation|adaptation]] purposes. A more dynamic and de-centered view, advocated by Dourish <ref> Dourish, Paul. "What we talk about when we talk about context." Personal and ubiquitous computing 8.1 (2004): 19-30.</ref> views context as primarily ''relational''. This was originally congruent with the move from desktop computing to [[ubiquitous computing]], but it does also fit with a broader understanding of [[ambient intelligence]] where the distinctions between ''context'' and ''content'' become relative and dynamic.<ref> https://www.researchgate.net/publication/230704197_Ambient_Intelligence Streitz, Norbert A., and Gilles Privat. "Ambient Intelligence" , ''Universal Access Handbook'' (2009)</ref> In this view, whichever sources of information (such as [[Internet of Things|IoT]] sensors) may be ''context'' for some uses and applications, might also be sources of primary ''content'' for others, and vice versa. What matters is the set of ''relationships'' that link them, together and with their environment. Whereas early descriptions of single-user-centric context could fit with classical [[Entity-attribute-value model|entity-attribute-value models]], more versatile graph-based information models, such as proposed with [[NGSI-LD]], are better adapted to capture the more relational view of context which is relevant for the  [[Internet of Things]], [[Cyber-Physical Systems]] and [[Digital Twins]]. In this broader acceptation, context is not only represented as a set of attributes attached to an entity, it is also captured by a graph that enmeshes this entity with others. Context awareness is the capability to account for this cross-cutting information from different sources.

Whereas early definitions of context tended to center on users, or devices interfaced directly with users, the oft-cited definition from Dey<ref name="dey2001"/> ("''any information that can be used to characterize the situation of an entity''") could be taken without this restriction. User-centric context, as may be used in the design of [[human-computer interaction|human-computer interfaces]], may also imply an overly clearcut, and partially arbitrary,  separation between "content" (anything which is ''explicitly'' typed in by users, or output to them), and context, which is ''implicit'', and used for [[context adaptation|adaptation]] purposes. A more dynamic and de-centered view, advocated by Dourish <ref> Dourish, Paul. "What we talk about when we talk about context." Personal and ubiquitous computing 8.1 (2004): 19-30.</ref> views context as primarily ''relational''. This was originally congruent with the move from desktop computing to [[ubiquitous computing]], but it does also fit with a broader understanding of [[ambient intelligence]] where the distinctions between ''context'' and ''content'' become relative and dynamic.<ref> https://www.researchgate.net/publication/230704197_Ambient_Intelligence Streitz, Norbert A., and Gilles Privat. "Ambient Intelligence" , ''Universal Access Handbook'' (2009)</ref> In this view, whichever sources of information (such as [[Internet of Things|IoT]] sensors) may be ''context'' for some uses and applications, might also be sources of primary ''content'' for others, and vice versa. What matters is the set of ''relationships'' that link them, together and with their environment. Whereas early descriptions of single-user-centric context could fit with classical [[Entity-attribute-value model|entity-attribute-value models]], more versatile graph-based information models, such as proposed with [[NGSI-LD]], are better adapted to capture the more relational view of context which is relevant for the  [[Internet of Things]], [[Cyber-Physical Systems]] and [[Digital Twins]]. In this broader acceptation, context is not only represented as a set of attributes attached to an entity, it is also captured by a graph that enmeshes this entity with others. Context awareness is the capability to account for this cross-cutting information from different sources.