Microsoft Technology Licensing, LLC

Advanced New Technologies Co., Ltd.

Alibaba Group Holding Limited

Yahoo! Inc.

Hangzhou Hikvision Digital Technology Co., Ltd.

Zhejiang Hisun Pharmaceutical Co., Ltd.

Palo Alto Networks, Inc.

Inphi Corporation

Linkedin Corporation

Juniper Networks, Inc.

Zhejianf Hisun Pharmaceutical Co., Ltd.

Liang Zhang

Deepak Agarwal

Yang Yang

Tian Chen

Guolai Ma

Bo Long

Sanjay Sureshchandra Dubey

Aman Grover

Zhiqing Yang

Ritesh Maheshwari

Xiangyang Zhang

Belle L Tseng

Yong He

Frank Emmanuel Astier

Dhruv Arya

David Q He

Ganesh Venkataraman

Anirban Dasgupta

Ruixuan Hou

Steven Scott Noble

Jieying Chen

Bei Liu

Jonathan David Traupman

Hongying Luo

Yicong Fan

Han Mei

Krishnaram Kenthapadi

Yang Chen

Peter Gregory Davis

Carl W Pobanz

Stuart MacDonald Ambler

Bee-Chung Chen

Raju Jain

Ning Guo

Min Ye

Achint Oommen Thomas

Kimberly Faith McManus

Kiran Kumar

Jian Chai

Toon Sripatanaskul

Zheng Yuan

Haifeng Zhao

Yizhe Liu

Maxim Gurevich

Song Yang

Dipesh Bhattarai

Jinyi Xu

Friedel Gerfers

Myoung Joon Choi

Vivek Gurumoorthy

Chienhsin Lee

Guang Qiu

Weidong Yin

Mingling Luo

Zhenjuan Shi

Yang Liu

Nitin Kumar

Di Wang

Jun Shi

Shaunak Chatterjee

Lin Zhu

Feng Yu

Sheng Zhao

Kun Liu

Brett Andrew Tomky

Jeffrey J Johnson

Huiji Gao

Sunanda L Kommula

Shu Kai Chen

Qing Duan

Abhimanyu Lad

Benjamin Hoan Le

Wen Pu

Yu Liu

Yitong Zhou

Yiming Ma

Ramesh Kandula

John P Moore

Xiaohai Zhang

Jeffrey V Johnson

Zaid A Kahn

Chencheng Wu

Xinyu Gu

Jiashuo Wang

Xingjun Ni

Hairong Luo

Michaeel M Kazi

Yu Gan

Gonzalo Jorge Aniano Porcile

Bonggwon Ji

Di Su

Aparna Krishnan

Anand Kishore

Surya Nimmagadda

Xiaoming Hu

Benjamin Graham

Zhifeng Deng

Dejin Fu

Ying Xiong

Xiaowei Liu

A communal computing device, such as an interactive digital whiteboard, can become unlocked if a user is near the device. The communal computing device may use a sensor such as a camera to capture images of a person and obtain an identifier from a personal device such as a smartphone. A cloud-based provider that is trusted by both the communal computing device and the personal device may associate both the image and the identifier of the personal device with the same user identity. Obtaining the user identity from multiple, different sources provides a secure technique for the communal computing device to recognize a user without the user directly interacting with the communal computing device. If the sensor no longer detects the user or the personal device is no longer detected, then the communal computing device may log off the user. The personal device may be used to confirm log off.

Proximity-based unlocking of communal computing devices

Computer-implemented techniques for enhanced tagging of natural language queries that are initially segmented and tagged by a named entity recognition system. By doing so, enhanced tagging of a natural language query that represents a deeper understanding of the query is provided. The enhanced tagging improves the operation of search engines that use the enhanced tags by enabling the search engine to identify and return more relevant search results in answers to natural language queries.

Enhanced natural language query segment tagging

A voice broadcast method includes: acquiring at least one piece of voice information; delivering the at least one piece of voice information to a voice broadcast device, wherein, the at least one piece of voice information includes voice identification information and a voice content; determining a first voice content to be broadcast by the voice broadcast device, wherein the first voice content is included in the at least one piece of voice information stored at the voice broadcast device; and sending, to the voice broadcast device, a first voice identification information corresponding to the first voice content, wherein the first voice identification information is used by the voice broadcast device to obtain the first voice content stored at the voice broadcast device, and to broadcast the first voice content when a preset voice broadcast condition is met.

Method and device for voice broadcast

A computer-implemented method includes: obtaining first environmental factor data of a first time period and first historical payment data of a target Internet of Things (IoT) device in the first time period, in which the first time period is before a first time point; obtaining second environmental factor data of a second time period that is after the first time point; and obtaining a prediction, using a neural network model, operating on at least one computing device, of an estimated statistical distribution of one or more users who execute transactions using the target IoT device in the second time period, in which the first environmental factor data, the first historical payment data, and the second environment factor data are inputs to the neural network model.

Predicting future user transactions

The disclosed embodiments provide a system for performing a natural language search. During operation, the system applies a first machine learning model to a natural language query to predict one or more search intentions associated with the natural language query. Next, the system applies a second machine learning model to the natural language query to produce one or more search parameters associated with a first intention in the search intention(s), wherein the search parameter(s) include a field and a value of the field. The system then performs a first search of a first vertical associated with the first intention using the search parameter(s). Finally, the system generates a ranking containing a first set of search results from the first search of the first vertical and outputs at least a portion of the ranking in a response to the natural language query.

Vertical processing of natural language searches

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing voice data are provided. One of methods, implemented by an IoT device, includes: receiving voice data from a server, wherein the voice data is obtained through converting text data to voice data by the server; determining a content attribute associated with the voice data; determining a content attribute type of the content attribute associated with the voice data; determining a first play rule matching the content attribute type based on a matching relationship between content attribute types and respective first play rules, wherein the first play rule including a play starting time and a play mode; and automatically playing the voice data according to the play starting time and the play mode.

Information processing system, method, device and equipment

Entity resolution techniques for matching entity records from different data sources are provided. In one technique, an entity record from a source database is identified along with multiple data items included therein. Each data item corresponds to an attribute of multiple source attributes. For one of the data items that corresponds to a first source attribute, multiple target attributes are identified. A first query is generated that includes the data items and associates the data item with each of the multiple target attributes. A second query that is different than the first query is also generated. Two searches are performed of a target database: one based on the first query and the other based on the second query. A scoring model generates multiple scores, one for each search result. It is determined whether the entity record matches an entity record in the target database based on the set of scores.

Entity resolution techniques for matching entity records from different data sources

A signal transmission system comprises: a power supply, a power sourcing device and a powered device connected to each other through a coaxial cable; the power sourcing device comprises a first active inductor module for receiving a DC signal transmitted by the power supply, and transmitting the DC signal to the powered device through the coaxial cable, a first capacitor module for receiving a superposed signal transmitted through the coaxial cable, and transmitting the superposed signal to a signal processing module; and the powered device comprises a second active inductor module for receiving, through the coaxial cable, the DC signal, and transmitting the DC signal to a signal acquiring module for acquiring a superposed signal, a second capacitor module for transmitting the superposed signal to the power sourcing device through the coaxial cable, and the signal acquiring module is for transmitting the superposed signal to the second capacitor module.

Signal transmission system and signal transmission method

Techniques for predicting a user response to content are described. According to various embodiments, a configuration file is accessed, where the configuration file includes a user-specification of raw data accessible via external data sources and raw data encoding rules. In some embodiments, the raw data includes raw member data associated with a particular member and raw content data associated with a particular content item. Thereafter, source modules encode the raw data from the external data sources into feature vectors, based on the raw data encoding rules. An assembler module assembles one or more of the feature vectors into an assembled feature vector, based on user-specified assembly rules included in the configuration file. A prediction module performs a prediction modeling process based on the assembled feature vector and a prediction model, to predict a likelihood of the particular member performing a particular user action on the particular content item.

Systems and methods for content response prediction

Instead of a fixed fee for a particular job application, discussed in some examples are methods, systems, and machine readable mediums which provide for a job posting service that utilizes a pay-per-click model. That is, job posters pay a fee for each time the member selects the job posting for further inquiry when that posting is shown to a member (called an impression). The fee that is paid is determined by the job poster. Selecting a job posting may comprise clicking on or otherwise entering an input signifying an intention to view the job.

Electronic job posting marketplace

Methods, systems, and computer programs are presented for expanding a job search that includes an industry by adding other similar industries. A method identifies job titles of members in a social network and performs, utilizing a machine-learning program, semantic analysis of the job titles to identify similarity coefficients among the job titles. The machine-learning program utilizes social network data to identify the similarity coefficients. Further, the method includes an operation for receiving a job search query, from a first member, including a query job title, and for expanding the job search query with job titles that are similar to the query job title. The method further includes operations for executing the expanded job search query to generate a plurality of job results, and for causing presentation on a display of one or more of the top job results.

Determining similarities among job titles to enhance job searching

In an example, an anonymized set of confidential data data values of a first confidential data type is obtained. Then an anonymized set of confidential data data values of a second confidential data type is also obtained. A multiplier following a log-normal distribution is determined for the anonymized set of confidential data data values of the first confidential data type. Then smoothing is performed independently for the anonymized set of confidential data data values of the first confidential data type and the multiplier. Percentiles for the anonymized set of confidential data data values of the second confidential data type are then determined using the smoothed anonymized set of confidential data data values of the first confidential data type and the smoothed multiplier.

Ensuring consistency between confidential data value types

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Liang Zhang