Beijing, China
Beijing, China

Baidu百度, Inc. , incorporated on January 18, 2000, is a Chinese web services company headquartered in the Baidu Campus in Haidian District in Beijing.Baidu offers many services, including a Chinese language-search engine for websites, audio files, and images. Baidu offers 57 search and community services including Baidu Baike and a searchable, keyword-based discussion forum. Baidu was established in 2000 by Robin Li and Eric Xu. Both of the co-founders are Chinese nationals who studied and worked overseas before returning to China. In May 2014, Baidu ranked 5th overall in the Alexa Internet rankings. During Q4 of 2010, it is estimated that there were 4.02 billion search queries in China of which Baidu had a market share of 56.6%. China's Internet-search revenue share in second quarter 2011 by Baidu is 76%. In December 2007, Baidu became the first Chinese company to be included in the NASDAQ-100 index. In December 2014, Baidu was expected to invest in the company Uber.Baidu provides an index of over 740 million web pages, 80 million images, and 10 million multimedia files. Baidu offers multimedia content including MP3 music, and movies, and is the first in China to offer Wireless Application Protocol and personal digital assistant -based mobile search.Baidu Baike is similar to Wikipedia as an encyclopedia; however, unlike Wikipedia, only registered users can edit the articles. While access to Wikipedia has been intermittently blocked or certain articles filtered in China since June 2004, there is some controversy about the degree to which Baidu cooperates with Chinese government censorship. Wikipedia.


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Disclosed are systems and methods that implement efficient engines for computation-intensive tasks such as neural network deployment. Various embodiments of the invention provide for high-throughput batching that increases throughput of streaming data in high-traffic applications, such as real-time speech transcription. In embodiments, throughput is increased by dynamically assembling into batches and processing together user requests that randomly arrive at unknown timing such that not all the data is present at once at the time of batching. Some embodiments allow for performing steaming classification using pre-processing. The gains in performance allow for more efficient use of a compute engine and drastically reduce the cost of deploying large neural networks at scale, while meeting strict application requirements and adding relatively little computational latency so as to maintain a satisfactory application experience.


A method for determining behaviour information corresponding to a dangerous file in a computer device. The method comprises: when a dangerous file is detected, running the dangerous file in a virtual environment of the computer device, wherein the virtual environment comprises at least one virtual API identical to at least one real API in a real environment of the computer device; and monitoring the behaviour of the dangerous file in the virtual environment to obtain behaviour information corresponding to the dangerous file. According to the method, the behaviour information about the dangerous file can be rapidly obtained in the virtual environment without needing to artificially analyse the destructive behaviour of the dangerous file, so as to rapidly and comprehensively repair a real system of the computer device.


Patent
Baidu | Date: 2017-03-15

A search recommendation method and device. The search recommendation method comprises: receiving a search term and acquiring recommended contents according to the search term (S11); generating a title of the recommended contents according to the search term and the recommended contents, wherein the title contains information associated with the search term and information associated with the recommended contents (S12); and displaying the recommended contents and the title of the recommended contents (S13).The method can better satisfy a users needs.


A method and system for providing translation information. The method for providing translation information comprises: S1, receiving a source language statement input by a user, and acquiring, according to the source language statement, a current target language statement; S2, displaying the current target language statement and a pre-set control at a current interface; and S3, receiving an operation executed by the user on the pre-set control, acquiring, according to the operation, another target language statement, and displaying the other target language statement at the current interface. Various translation results of a complete sentence are provided by means of a rapid and convenient way, and the situation of multiple candidate options that words or phrases are reselected one by one is avoided, so that more translation results can be viewed, thereby effectively improving the translation accuracy, and improving the satisfactory of the user; and additionally, the method and system can be applied to small-screen terminals such as a mobile phone, thereby being high in practicability.


An object of the present invention is to provide a method and apparatus for predicting a characteristic information change, wherein the method according to the present invention comprises: obtaining historical characteristic data in at least one computation period and current incremental data of multiple pieces of first characteristic information corresponding to a pre-estimation model, wherein the current incremental data is used for indicating a ratio of characteristic data on a day immediately before a forecasting day of each of the first characteristic information to the historical characteristic data in the at least one computation period of each of the first characteristic information; obtaining first change information on the forecasting day of second characteristic information, wherein the first change information on the forecasting day of the second characteristic information is determined by a forecasting process using the pre-estimation model based on the historical characteristic data and the current incremental data of each of the first characteristic information corresponding to the pre-estimation model; and determining, based on the first change information, change pre-estimation information on the forecasting day of the second characteristic information in order to prompt a user to execute a corresponding operation based on the change pre-estimation information.


The present invention provides a method and a device for recommending a solution based on a user operation behavior. The method comprises: monitoring a second window object that is triggered after a user performs an operation on a first window object; if the second window object is an abnormal window, determining a type of the abnormal window by extracting text information in the second window object; and recommending, according to the type of the abnormal window and monitored an operation behavior of the user on the second window object, a solution to a problem corresponding to the second window object. By means of the method, when it is analyzed, according to a user operation behavior, that a user needs to obtain a solution to a corresponding problem, a corresponding solution can be provided to the user, and a process in which the user manually searches for a solution is no longer required, so as to implement a humanized intelligent recommendation function, and effectively help the user to resolve various problems that occur in a process of using a computer, thereby improving use experience of the user.


The embodiments of the present invention provide a method of navigation, smart terminal device and wearable device. The method comprises: establishing a connection with a navigation application; acquiring navigation data from the navigation application; and publishing the navigation data to a specified data service interface, so as to allow an application device connected to the data service interface to acquire navigation data. The solutions of the present invention provides a method for data transmission for navigation service between the existing navigation APP and an application device, and thus provide navigation data in a convenient and low-cost way.


A map query method, device, equipment and computer storage medium, the method comprising: receiving a query statement inputted by a user; conducting word segmentation on the received query statement; extracting from the word segmentation result the particular information related to user requirements; and querying in the map a route and/or a point of interest related to the particular information extracted.


The present invention provides a method for building a speech feature library, a method, an apparatus, and device for speech synthesis. Because the speech feature library used in the present invention saves at least one context corresponding to each piece of personalized textual information and at least one piece of textual information semantically identical to the personalized textual information, when performing speech synthesis, even if the provided textual information is not personalized textual information corresponding to the desired personalized speech, personalized textual information semantically identical to the textual information to be subject to speech synthesis may be first found in the speech feature library to thereby achieve personalized speech synthesis, such that use of the personalized speech will not be restricted by aging, sickness, and death of a person.


Described herein are systems and methods for determining how to automatically answer questions like Where did Harry Potter go to school? Carefully built knowledge graphs provide rich sources of facts. However, it still remains a challenge to answer factual questions in natural language due to the tremendous variety of ways a question can be raised. Presented herein are embodiments of systems and methods for human inspired simple question answering (HISQA), a deep-neural-network-based methodology for automatic question answering using a knowledge graph. Inspired by humans natural actions in this task, embodiments first find the correct entity via entity linking, and then seek a proper relation to answer the question-both achieved by deep gated recurrent networks and neural embedding mechanism.

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