Patent Document ID: 9971769
Application ID: 15673694

Base Claim:
1. A translation result providing method using a computer, the method comprising: generating, by a processor, candidate translation sentences by translating a source sentence of a source language into a target language using a machine translation model; classifying, by the processor, the candidate translation sentences into semantic categories, respectively, based on attributes of the candidate translation sentences; generating, by the processor, information regarding a personality of a user by analyzing user information on Internet, the personality of the user being a service type or a writing style suitable for the user; predicting and automatically setting, by the processor, a specific semantic category, from among the semantic categories, based on the analyzed user information; and providing, by the processor, at least one of the classified candidate translation sentences as a translation result, wherein the providing includes displaying a first classified candidate translation sentence, from among the classified candidate translation sentences, which corresponds to the information in a first region of a screen and displaying a second classified candidate translation sentence, from among the classified candidate translation sentences, which does not correspond to the information in a second region of the screen, and the first region and the second region are visually distinguished from each other on the screen.

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Claim 14:
14. The method of claim 1 , wherein when the generating candidate translation sentences uses a statistics-based machine translation model, the method further includes a translation probability table constructing process, a translation probability table constructing process including, receiving large translation pair data between the source language and the target language, estimating translation probabilities between words from the large translation pair data, determining a phrase section based on the estimated translation probabilities, and constructing a translation probability table including candidate phrase data and respective ones of the estimated translation probabilities.