| 摘要 |
An intelligent content assistance system generates context-sensitive content recommendation during business processes. Information needs of a user in context are dynamically monitored and detected. Content-recommendation templates are retrieved to match the detected information needs, and instantiated using information from user input, context, interaction history, system-learned query and content models, and external sources. Context, interaction history, and system-learned models are dynamically updated for learning and adaptation. The system and methods are applicable to multiple domains and applications.
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