| 摘要 |
A cascading learning system as a semantic search is described. The cascading learning system has a request analyzer, a request dispatcher and classifier, a search module, a terminology manager, and a cluster manager. The request analyzer receives a request for search terms from a client application and determines term context in the request to normalize request data from the term context. The normalized request data are classified and dispatched to a corresponding domain-specific module. Each domain-specific module of a search module generates a prediction with a trained probability of an expected output. The terminology manager receives normalized request data from the request dispatcher and classifier, and manages terminology stored in a contextual network. The cluster manager controls data flow between the request dispatcher and classifier, the search module container, the terminology manager, and a business data source system. |
