A blackboard architecture for control
Artificial Intelligence
Organizing information: principles of data base and retrieval systems
Organizing information: principles of data base and retrieval systems
Generality in artificial intelligence
Communications of the ACM
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Blackboard systems for knowledge-based signal understanding
Symbolic and knowledge-based signal processing
Contexts: a formalization and some applications
Contexts: a formalization and some applications
Coordinating context building in heterogeneous information systems
Journal of Intelligent Information Systems - Special issue on next generation information technologies
Share the ontology in XML-based trading architectures
Communications of the ACM
Hierarchical classification of Web content
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Concise, intelligible, and approximate profiling of multiple classes
International Journal of Human-Computer Studies - Special issue on Machine Discovery
The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty
ACM Computing Surveys (CSUR)
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Context Mediation on Wall Street
COOPIS '98 Proceedings of the 3rd IFCIS International Conference on Cooperative Information Systems
Estimating the Quality of Databases
FQAS '98 Proceedings of the Third International Conference on Flexible Query Answering Systems
Dynamic Classificational Ontologies for Discovery in Cooperative Federated Databases
COOPIS '96 Proceedings of the First IFCIS International Conference on Cooperative Information Systems
Internet as a knowledge base for medical diagnostic assistance
Expert Systems with Applications: An International Journal
Circular context-based semantic matching to identify web service composition
Proceedings of the 2008 international workshop on Context enabled source and service selection, integration and adaptation: organized with the 17th International World Wide Web Conference (WWW 2008)
Using a new relational concept to improve the clustering performance of search engines
Information Processing and Management: an International Journal
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Context recognition is an important component of the common sense knowledge problem, which is one of the key research areas in the field of Artificial Intelligence. The paper develops a model of context recognition using the Internet as a knowledge base. The use of the Internet as a database for context recognition gives a context recognition model immediate access to a nearly infinite amount of data in a multiplicity of fields. Context is represented here as any textual description that is most commonly selected by a set of subjects to describe a given situation. The model input is based on any aspect of the situation that can be translated into text (such as: voice recognition, image recognition, facial expression interpretation, and smell identification). The research model is based on the streaming in text format of information that represents situations--Internet chats, e-mails, Shakespeare plays, or article abstracts. The comparison of the results of the algorithm with the results of human subjects yielded a very high agreement and correlation. The results showed there was no significant difference in the determination of context between the algorithm and the human subjects.