초록 ▼

Processing automatically information in a document to be incorporated into databases to be searched, retrieved and learned. This would significantly enhance categorizing information in the domain so that information can be systematically and efficiently retrieved when needed. In one approach, first,

Processing automatically information in a document to be incorporated into databases to be searched, retrieved and learned. This would significantly enhance categorizing information in the domain so that information can be systematically and efficiently retrieved when needed. In one approach, first, the context or the domain of the document is determined. Then, domain-specific phrases in the document are automatically extracted based on grammar and dictionaries. From these phrases, categories in a category hierarchy are identified, and the document is linked to those categories. Phrases in the document that cannot be categorized are identified to be analyzed. If these new phrases are relevant, new categories may be created based on suggestions provided to categorize them. Later when a user asks a question that is related to the categorized phrases, the corresponding categories are identified, with the document retrieved to respond to the question. In one approach, the question is in natural-language.

대표청구항 ▼

Processing automatically information in a document to be incorporated into databases to be searched, retrieved and learned. This would significantly enhance categorizing information in the domain so that information can be systematically and efficiently retrieved when needed. In one approach, first,

Processing automatically information in a document to be incorporated into databases to be searched, retrieved and learned. This would significantly enhance categorizing information in the domain so that information can be systematically and efficiently retrieved when needed. In one approach, first, the context or the domain of the document is determined. Then, domain-specific phrases in the document are automatically extracted based on grammar and dictionaries. From these phrases, categories in a category hierarchy are identified, and the document is linked to those categories. Phrases in the document that cannot be categorized are identified to be analyzed. If these new phrases are relevant, new categories may be created based on suggestions provided to categorize them. Later when a user asks a question that is related to the categorized phrases, the corresponding categories are identified, with the document retrieved to respond to the question. In one approach, the question is in natural-language. signals, including using said first and second error indications to mask errors arising during wireless transmission from said one of said subscribers to said first wireless network station or arising during transmission from said second wireless network station to said other subscriber. 43. The method of claim 42 wherein coding comprises encryption using a secret key followed by error detection coding. 44. The method of claim 43 further including error correction coding. 45. The method of claim 42 wherein said first vocoder produces at least two unused output bits for each predetermined number of output bits representing speech. 46. The method of claim 45 wherein said digitized speech is enciphered independently of said at least two unused bits. 47. The method of claim 42 wherein reformatting of said decoded speech and said first error indication comprises combining said first error indication with a decoded bit corresponding to a first of said at least two unused bits. 48. The method of claim 45 wherein combinin