Method for maintaining language model base by using network and system

Abstract

The invention relates to an input method realized through network assistance and an input system. The language model base is maintained by using a network server and input is finished by calling the corresponding language model base by a user. The system comprises at least one piece of user equipment, the network server and a language model synchronizing device, wherein the user equipment is configured to be used by a user to enter characters and is configured to establish a local language model base according to the user input; the network server is configured to establish a network language model base on the basis of the received at least one local language model base and statistical analysis on other language materials; and the language model synchronizing device is configured to synchronize the local language model base and the network language model base. The invention also relates to the input method realized by using the system.

Description

technical field [0001] The invention relates to the field of text input, in particular to an input method and system which are implemented with network assistance and improve the maintenance of language model databases. Background technique [0002] Currently popular input methods, such as Sogou and Google Input Methods, have built-in statistical language model algorithms to analyze text input data to generate results that meet user expectations. The statistical language model uses the method of probability and statistics to reveal the inherent statistical laws of language units, among which N-Gram is simple and effective, and is widely used. The N-Gram model is based on the assumption that the appearance of the Nth word is only related to the previous N-1 words, but not to any other words, and the probability of the entire sentence is the product of the occurrence probabilities of each word. These probabilities can be obtained by counting the number of simultaneous occurre...

AI Technical Summary

Problems solved by technology

Even if such a large corpus is only stored on the network side as the Sogou input method seeks, it is difficult or delayed to search for matching terms directly from the network side based on such a massive corpus

More importantly, the use of such a large corpus follows everyone's input habits, which is not associated with the user's personal language model, so it cannot provide the efficiency brought by calling a specific language model for a specific user

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