Microsoft Technology Licensing, LLC

Alibaba Group Holding Limited

Matsushita Electric Industrial Co., Ltd.

Tongji University

Shanghai Pulmonary Hospital

Mu Li

Ming Zhou

Jianfeng Gao

Lei Zhang

Jian Qiao Sun

Dongdong Zhang

Gregory Nicholas Hullender

Long Wang

Matthew Robert Scott

Zhiqiang Zhang

Jin Shi

Yue Ma

Jinhong K Guo

Kun Jing

Weipeng Liu

Chang-Ning Huang

Xiong Zheng

Xi Chen

Janine Crumb

Yinguang Chen

Yongliang Wang

Chi-Ho Li

Haining Huang

Haoyong Zhang

Yuqi Chen

Tian-shun Yao

Yu-kun Tong

Donglai Chen

XierMaiMaiTi Kadeer

Jing-bo Zhu

Yawei Gu

Yangjian Chen

Ziwen Fan

Jianxing Xiao

Qunmeng Zheng

Yinglong Su

Lijuan Wu

Limin Cheng

Qibu Luo

Ming Lester Alexander Zhou

Chang Chen

Elliott K Olds

Zeyao Li

Yajuan Lv

Embodiments of the present application disclose a content generation method and apparatus. The method includes: acquiring product description information; selecting, by using a deep neural network model component, a content phrase matched with the product description information, wherein the deep neural network model component is obtained by training according to a plurality of pieces of historical product description information and historical content of the historical product description information; and generating content corresponding to the product description information based on the selected content phrase.

Content generation method and apparatus

An input method editor (IME) configured to provide language assistance across a plurality of applications is disclosed. In one example, the IME is adapted for use by English-as-a-second-language (ESL) users. In a specific example, language assistance may be provided by first detecting a need to suggest a substitute word to a user who is typing within an application. The detection may be based on a probability that a current word is in error. If a need is detected, a suggestion may be obtained for the word, such as from a cloud linguistic service or from a local lexicon and language-model, if network connectivity is poor. Once obtained, the suggestion may be displayed to the user in a non-intrusive manner by user interface element(s). Interaction with the user allows the user to accept or reject the suggestion, and perform other functions, such as relocating user interface elements utilized by the display.

Input method editor providing language assistance

The present invention discloses a method for precise localization and treatment of a target site, which builds a 3D digital model of an anatomical structure of a patient in accordance with tomographic image data of the patient; a structure model for locating a target site which comprises a template model for locating a target site and an angle locating auxiliary unit model is customized, and a position and an angle for loading and treating a target site are designed according to 3D position of the target site; then a target site locating structure is printed by 3D printing technology, and the target site locating structure is utilized to treat the target site.

Method for precise localization and treatment of a target site and a medical auxiliary apparatus

Some examples include generating a personal language model based on linguistic characteristics of one or more files stored at one or more locations in a file system. Further, some implementations include predicting and presenting a non-Latin character string based at least in part on the personal language model, such as in response to receiving a Latin character string via an input method editor interface.

Personal language model for input method editor

A method for reducing release of resistance genes during sludge anaerobic treatment includes controlling concentration of to-be-treated sludge in a concentration tank to be 12-20 g/L by sedimentation under gravity. The concentrated sludge is transferred to a supersonic pre-treatment device to proceed with supersonic pre-treatment. The supersonic pre-treatment is conducted for 5-30 minutes at a power of 0.1-0.5 kW and a frequency of 10-40 kHz. The pre-treated sludge is then transferred to an anaerobic treatment device for anaerobic treatment. The anaerobic treatment is conducted for 4-12 days at a temperature of 20-37&#xb0; C. The release amount of resistance genes in the residual sludge and the supernatant liquid in the anaerobic treatment device is detected. A feedback dosage of an alkali liquid is fed into the anaerobic treatment device according to the release amount of the resistance genes, controlling a pH value to be 9.0-11.0 during the anaerobic treatment.

Method for reducing release of resistance genes during sludge anaerobic treatment

Method and system of processing cross-domain cookies in order to allow a first website to access a cookie of a second website are provided. In one aspect, a method includes: providing a flash cookie of a first website in a user's local computer; reading an ordinary cookie of a second website that is stored in the user's local computer; and writing the ordinary cookie of the second website into the flash cookie of the first website. Based on this method, it is achievable to access and store cookies across domains in the user's local computer. Accordingly, the method enables e-commerce websites to have a more comprehensive collection of user information to provide more reliable references for the e-commerce websites to analyze user information.

Method and system of processing cookies across domains

Disclosed is a method for displaying an advertisement. The method displays a present advertisement, determines whether the present advertisement has been displayed completely, and adds an identifier of the present advertisement to a priority advertisement list if the present advertisement has not been displayed completely. The method sends the priority advertisement list to the advertisement engine when requesting the advertisement engine for displaying a next advertisement. Using the priority advertisement list, the advertisement engine may give priority to the present advertisement in next advertisement assignment. Using an optimized advertisement display strategy, the disclosed method may increase coverage rates of advertisement contents to audiences, thereby improving advertisement effectiveness for advertisers and increasing cash flow return for website owners.

Displaying online advertisements

A method of statistical machine translation (SMT) is provided. The method comprises generating reordering knowledge based on the syntax of a source language (SL) and a number of alignment matrices that map sample SL sentences with sample target language (TL) sentences. The method further comprises receiving a SL word string and parsing the SL word string into a parse tree that represents the syntactic properties of the SL word string. The nodes on the parse tree are reordered based on the generated reordering knowledge in order to provide reordered word strings. The method further comprises translating a number of reordered word strings to create a number of TL word strings, and identifying a statistically preferred TL word string as a preferred translation of the SL word string.

Technologies for statistical machine translation based on generated reordering knowledge

Candidate suggestions for correcting misspelled query terms input into a search application are automatically generated. A score for each candidate suggestion can be generated using a first decoding pass and paths through the suggestions can be ranked in a second decoding pass. Candidate suggestions can be generated based on typographical errors, phonetic mistakes and/or compounding mistakes. Furthermore, a ranking model can be developed to rank candidate suggestions to be presented to a user.

Query speller

A distributional similarity between a word of a search query and a term of a candidate word sequences is used to determine an error model probability that describes the probability of the search query given the candidate word sequence. The error model probability is used to determine a probability of the candidate word sequence given the search query. The probability of the candidate word sequence given the search query is used to select a candidate word sequence as a corrected word sequence for the search query. Distributional similarity is also used to build features that are applied in maximum entropy model to compute the probability of the candidate word sequence given the search query.

Distributional similarity-based models for query correction

A method and apparatus for segmenting text is provided that identifies a sequence of entity types from a sequence of characters and thereby identifies a segmentation for the sequence of characters. Under the invention, the sequence of entity types is identified using probabilistic models that describe the likelihood of a sequence of entities and the likelihood of sequences of characters given particular entities. Under one aspect of the invention, organization name entities are identified from a first sequence of identified entities to form a final sequence of identified entities.

Using source-channel models for word segmentation

A method and data structure are provided for efficiently storing asymmetric clustering models. The models are stored by storing a first level record for a word identifier and two second level records, one for a word identifier and one for a cluster identifier. An index to the second level word record and an index to the second level cluster record are stored in the first level record. Many of the records in the data structure include both cluster sub-model parameters and word sub-model parameters.

Method and apparatus for compressing asymmetric clustering language models

A method of post-processing character data from an optical character recognition (OCR) engine and apparatus to perform the method. This exemplary method includes segmenting the character data into a set of initial words. The set of initial words is word level processed to determine at least one candidate word corresponding to each initial word. The set of initial words is segmented into a set of sentences. Each sentence in the set of sentences includes a plurality of initial words and candidate words corresponding to the initial words. A sentence is selected from the set of sentences. The selected sentence is word disambiguity processed to determine a plurality of final words. A final word is selected from the at least one candidate word corresponding to a matching initial word. The plurality of final words is then assembled as post-processed OCR data.

Post-processing system and method for correcting machine recognized text

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Beijing, China

Mu Li