Tencent Technology (shenzhen) Company Limited

Shenzhen Red Brick Technology Co., Ltd.

Qiang Cheng

Bo Song Chen

Xiang Zhang

Li Hui Lu

Feng Rao

Duling Lu

Shuai Yue

Lu Li

Lou Li

Jianxiong Ma

The present disclosure relates to the technical field of Internet, and provides a user registration method, a user login method and a device corresponding thereto. In these methods, a passport or the user card records identity information of the autonomous identity of a user, and the user can use the passport or the user card to access an application website, which is unlike the conventional method of performing the accessing through the account and the password. Moreover, the present disclosure further implements a series of mechanisms from the application to the use, concerning the passport and the user card.

User registration method, user login method and corresponding device

Disclosed are a blockchain system and a consensus method for use in a miner node in a blockchain system. A specific embodiment of the method includes: acquiring a lower-limit accumulative unused duration; executing, in a trusted execution environment associated with the miner node, a bookkeeping right determination operation including: determining a current accumulative unused duration for the miner node; determining whether the current accumulative unused duration is more than the lower-limit accumulative unused duration; and, in response to the determination that the current accumulative unused duration is more than the lower-limit accumulative unused duration, determining that the miner node has won a bookkeeping right, and updating the current accumulative unused duration with a difference between the current accumulative unused duration and the lower-limit accumulative unused duration. This embodiment allows for reduced electric power consumption in a blockchain system.

Consensus method used for miner node in blockchain system and blockchain system

A method is performed at a computer for automatically correcting typographical errors. The computer selects a target word in a target sentence and identifies a target word therein as having a typographical error and first and second sequences of words separated by the target word as context. After identifying, among a database of grammatically correct sentences, a set of sentences having the first and second sequences of words, each sentence including a replacement word, the computer selects a set of candidate grammatically correct sentences whose corresponding replacement words have similarities to the target word above a pre-set threshold, Finally, the computer chooses, among the set of candidate grammatically correct sentences, a fittest grammatically correct sentence according to a linguistic model and replaces the target word in the target sentence with the replacement word within the fittest grammatically correct sentence.

Model-based automatic correction of typographical errors

A method is implemented at a computer to determine that certain information content is composed or compiled in a specific language selected among two or more similar languages. The computer integrates a first vocabulary list of a first language and a second vocabulary list of a second language into a comprehensive vocabulary list. The integrating includes analyzing the first vocabulary list in view of the second vocabulary list to identify a first vocabulary sub-list that is used in the first language, but not in the second language. The computer then identifies, in the information content, a plurality of expressions that are included in the comprehensive vocabulary list, and a subset of expressions that are included in the first vocabulary sub-list. Upon a determination that a total frequency of occurrence of the subset of expressions meets predetermined occurrence criteria, the computer determines that the information content is composed in the first language.

Language recognition based on vocabulary lists

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Shenzhen, China

Qiang Cheng