Abstract: A classifier voice interface of a user terminal may receive a query, may parse the query to identify an attribute, and may process the query to select a first domain-specific voice interface of a plurality of domain-specific voice interfaces based on the attribute, wherein each of the domain-specific voice interfaces comprises specialized information to process queries of different types. The classifier voice interface may further instruct the first domain-specific voice interface to process the query.

Abstract: Methods and systems for providing a voice interface are disclosed. A classifier voice interface of a user terminal may receive a query, may parse the query to identify an attribute, and may process the query to select a first domain-specific voice interface of a plurality of domain-specific voice interface based on the attribute, wherein each of the domain-specific voice interface comprises specialized information to process queries of different types. The classifier voice interface may further instruct the first domain-specific voice interface to process the query.

Abstract: A computer method and apparatus determines keywords of documents. An initial document by term matrix is formed, each document being represented by a respective M dimensional vector, where M represents the number of terms or words in a predetermined domain of documents. The dimensionality of the initial matrix is reduced to form resultant vectors of the documents. The resultant vectors are then clustered such that correlated documents are grouped into respective clusters. For each cluster, the terms having greatest impact on the documents in that cluster are identified. The identified terms represent key words of each document in that cluster. Further, the identified terms form a cluster summary indicative of the documents in that cluster.

Abstract: A model-based reasoning system for diagnosing faults in a computer network has an information base that stores information about the computer network. This information includes the topology of the network, a class hierarchy containing a component library and diagnostic expertise, and a diagnosis episode. A diagnosis engine receives a pointer to a situation. Each situation includes a focus role and a most general class for the focus role. Based upon this situation, the diagnosis engine creates a diagnosis episode, using the information stored in the information base.