Some papers

1． Using the Object-Oriented Paradigm to Model Context in Computer Go

(1) Using OOP to model contextual information, temporal, goal, spatial and global;

(2) A general class with specialized classes, a master slot of a class and slave slots, a list of goals that depend on each other. A master slot fixes the context and the usefulness of the slave slots.

2. An ontology-based context model in intelligent environment

Based on ontology, the paper uses owl to model context, semantic context representation, context reasoning and knowledge sharing, context classification, context dependency and quality of context. Classification -> capture various contexts: (1) direct   -> from a context provider (sensed, derived); (2) indirect: aggregation and reasoning.

Dependency tag to the property associated with a specific context class -> capture relationship between context information.

 Annotating sensed context with extensible quality constraints -> quality

(1) Analyze existing contextual models and classify then into three types: application-oriented, model-oriented, ontology-oriented.

(2) Describe characteristics of context information: great variety, varying in different sub-domains, interrelated, inconsistent.

(3) Domain-specific: a collection low-level ontology defining the details of general concepts and their properties in each sub-domain; Upper ontology: a high level ontology capturing general context knowledge about the physical world

Advantages: domain-specific shares the load of the whole system; upper ontology shares common understanding, semantic interoperability, reuse of domain knowledge, formal analysis.

(4) Classification: to perform context reasoning based on confidence level of each type of context;

(5) Quality: based on attributes. Quality (quality indicators of owl properties) constraints are associated with a number of quality parameters, which capture the dimensions of quality relevant to the attributes of entities and relationships between entities.

3. Experiences in using CC/PP in context-aware systems

Contextual models describe: 1) the features of the whole computing environment (user, computing devices, network, OS, distributed computing platform); 2) user’s computing applications, requirements and preferences; 3) computing application’s requirements; 4) information about how the requirement are currently met by the computing environment; 5) constraints and relationships existing in the computing environment; 6) dependencies between context information.

Goal: Extend CC/PP vocabulary: user context information, device capabilities, and application requirement and their current status. A large amount of research about context and pervasive computing is similar to AI, whose goal is to å°½å?¯èƒ½å‡?少用户干预，æ?•æ?‰æ›´å¤šçš„环境信æ?¯ï¼Œ å?‘用户æ??供最å?¯é? ï¼Œå‡†ç¡®çš„ä¿¡æ?¯å’Œå¸®åŠ©ã€‚收集信æ?¯Â -> 分æž? -> æ??供（å?¯é? ï¼Œå‡†ç¡®ï¼Œå®‰å…¨ï¼‰ã€‚ 如何筛选，表示，组织，集æˆ?ä¸?å?Œçš„ä¿¡æ?¯åˆ™ä¾?æ?®ä¸?å?Œçš„æ?¥æº?和目的。