Abstract: A method, an apparatus, a device, a storage medium and a program product of performing a text matching are provided, which relate to a field of a computer technology, and in particular to natural language processing and deep learning technologies. The method includes: determining a word set and a plurality of semantic units from a text set, the word set is associated with a first predetermined attribute, and the text set contains a plurality of first texts indicating an object information and a plurality of second texts indicating an object demand information; generating a graph; and generating a final feature representation associated with the text set and the word set based on the graph and a graph convolution model, so as to perform the text matching.

Abstract: Provided are a training method and device for a heterogeneous generative adversarial network model, an equipment, a program and a storage medium. In the training method, measurement data of a heterogeneous station is acquired, the measurement data of the heterogeneous station is set as a training sample, and joint training is performed on the heterogeneous generative adversarial network model according to a total objective function. A generator is configured to predict environment data at a future occasion according to environment data of the heterogeneous station at a historical occasion so as to output predicted data. A discriminator is configured to be input the predicted data output by the generator and corresponding measurement data, and discriminate a similarity between the measurement data and the predicted data; a total objective function includes a first objective function of the generator and a second objective function of the discriminator.

Abstract: Embodiments of the disclosure provide a method and an apparatus for talent-post matching, a device and a medium, which relates to the field of information matching and recruitment. The method includes: determining a resume feature representing a resume to be predicted according to a post submitted and the resume to be predicted; and predicting a matching degree between the resume to be predicted and the post by using a pre-trained predictive model according to a post feature of the post and the resume feature. With the method and the apparatus for talent-post matching, the device and the medium provided in embodiments of the present disclosure, the resume and the post may be matched automatically.

Abstract: The present disclosure provides a skill word evaluation method for a resume, and relates to the technical field of machine learning. The method includes determining a to-be-evaluated first skill word list including a plurality of skill words, according to a resume document to be evaluated; and predicting, for each skill word in the first skill word list, a value of probability of presence of the skill word for representing importance of the skill word, by a pre-trained skill word evaluation model according to context information of the skill word in the first skill word list. The present disclosure further provides a skill word evaluation device, an electronic device and a non-transitory computer readable storage medium.

Abstract: An approach is provided for determining the context-aware similarity between applications. A similarity platform processes one or more context logs associated with one or more devices to determine one or more context intents. The similarity platform further determines one or more distributions of one or more applications executed at the one or more devices with respect to the one or more context intents. The similarity platform also determines a context-aware similarity between two or more applications based, at least in part, on the one or more application distributions.

Abstract: A weather parameter prediction model training method, a weather parameter prediction method, an electronic device and a storage medium are provided, and relate to the technical field of artificial intelligence, such as deep learning and big data. The method includes: establishing a weather parameter prediction model according to spatial correlation information among a plurality of monitoring stations; and adjusting the weather parameter prediction model according to observation values of a weather parameter for the plurality of monitoring stations and prediction values of the weather parameter for the plurality of monitoring stations output by the weather parameter prediction model. The present disclosure can improve an accuracy of predicting weather parameters.

Abstract: This application discloses a keyword generating method, an apparatus, a device and a storage medium, which relate to the field of natural language processing in the field of artificial intelligence. A specific implementation scheme includes: inputting a target text into a text processing model, obtaining a word sequence corresponding to the target text, and generating a semantic representation sequence corresponding to the word sequence; making prediction about each semantic representation vector in the semantic representation sequence respectively to obtain a prediction result; and if the prediction result indicates that a word corresponding to the semantic representation vector is capable of triggering a generation of a keyword, outputting the keyword based on the semantic representation vector and the prediction result. This method improves the accuracy of generating keywords.

Abstract: A method, an apparatus, a device and a medium for generating a recruitment position description text are provided. The method may include: obtaining the original text related to the target position; and generating a target recruitment position description text corresponding to the target position based on the original text and a pre-trained deep neural network model.

Abstract: A method and apparatus for forecasting a talent demand, a device and a storage medium are provided. An implementation of the method may include: determining, based on historical recruitment data, a target talent demand time series and an auxiliary talent demand time series; fusing the target talent demand time series and the auxiliary talent demand time series, to obtain a forward demand time series; and determining, based on the forward demand time series, new demand information for the target talent.

Abstract: The present disclosure provides a method, and an apparatus for detecting a regional event based on a search engine, a search engine, a computer device, and a storage medium. The method includes: obtaining key search data related to the regional event based on search data of the search engine; performing regional event detection based on the key search data related to the regional event; and when the regional event is detected, estimating a location of the detected regional event based on geographical distribution of the key search data related to the regional event.

Abstract: Embodiments of the present disclosure provide a method and apparatus for recommending a test question, and an intelligent device. The method includes: acquiring a plurality of skill entities of a post; calculating, according to the data of the post, a weight value of each of the plurality of skill entities; and acquiring, according to the weight value of each skill entity, a recommended test question of the post from a question bank.

Abstract: An approach is provided for determining the context-aware similarity between applications. A similarity platform processes one or more context logs associated with one or more devices to determine one or more context intents. The similarity platform further determines one or more distributions of one or more applications executed at the one or more devices with respect to the one or more context intents. The similarity platform also determines a context-aware similarity between two or more applications based, at least in part, on the one or more application distributions.

Abstract: This application provides a method and system for detecting a leading session of an application. The method comprises: a leading event detection step of detecting leading events of the application based on historical ranking information; and a leading session detection step of combining adjacent leading events to form the leading session. The method and system in this application can automatically detect, from information about an application leaderboard, application leading sessions in which an application is popular with users so as to provide a data basis for analyzing and processing an application service.

Abstract: The present disclosure provides a computer-assisted interview method and a computer-assisted interview device. The method includes: receiving description information of a job; receiving description information of each of a plurality of applicants; based on a pre-trained assisted interview model, determining a first parameter distribution corresponding to the description information of the job and determining a second parameter distribution corresponding to the description information of each of the plurality of applicants; determining a matching degree between the job and each of the plurality of applicants based on the first parameter distribution and the second parameter distribution; and filtering out an applicant corresponding to a matching degree meeting a first preset condition as a target applicant.

Abstract: An application recommendation method and a recommendation apparatus are disclosed. A method comprises: acquiring a popularity value and a security risk value of each application in multiple applications; and ranking the multiple applications according to the popularity value and the security risk value. In a technical solution of embodiments of the present application, multiple applications are ranked according to popularities and security risk vales of the applications to preferentially recommend, to a user, an application that better meets popularity and security preferences of a user, to cause the user being protected in terms of security and/or privacy while enjoying the application having abundant functions.

Abstract: Embodiments of the disclosure provide a method and an apparatus for talent-post matching, a device and a medium, which relates to the field of information matching and recruitment. The method includes: determining a resume feature representing a resume to be predicted according to a post submitted and the resume to be predicted; and predicting a matching degree between the resume to be predicted and the post by using a pre-trained predictive model according to a post feature of the post and the resume feature. With the method and the apparatus for talent-post matching, the device and the medium provided in embodiments of the present disclosure, the resume and the post may be matched automatically.

Abstract: An application recommendation method and a recommendation apparatus are disclosed. A method comprises: acquiring a popularity value and a security risk value of each application in multiple applications; and ranking the multiple applications according to the popularity value and the security risk value. In a technical solution of embodiments of the present application, multiple applications are ranked according to popularities and security risk vales of the applications to preferentially recommend, to a user, an application that better meets popularity and security preferences of a user, to cause the user being protected in terms of security and/or privacy while enjoying the application having abundant functions.

Abstract: The present application provides a method for determining a ranking threshold for applications and a system for determining a ranking threshold for applications. The method comprises: a user attention behavior detection step: detecting an attention behavior of a user towards an application leaderboard to obtain user attention behavior data; and a ranking threshold determining step: determining a ranking threshold according to the user attention behavior data. According to the method and the system in the present application, an actual user attention application quantity on an application leaderboard can be determined effectively, which provides a determination basis for detection of ranking fraud and increases efficiency and accuracy of detection of ranking fraud.

Abstract: This application provides a method and system for detecting a leading session of an application. The method comprises: a leading event detection step of detecting leading events of the application based on historical ranking information; and a leading session detection step of combining adjacent leading events to form the leading session. The method and system in this application can automatically detect, from information about an application leaderboard, application leading sessions in which an application is popular with users so as to provide a data basis for analyzing and processing an application service.

Abstract: The present application provides a ranking fraud detection method and a ranking fraud detection system for an application. The method comprises: a leading session detection step: detecting a leading session of the application based on historical ranking information; and a ranking fraud detection step: detecting the leading session based on at least one piece of evidence, to obtain a ranking fraud detection result. According to the method and the system of the present application, a ranking fraud act related to an application can be automatically identified, thereby allowing an application user to obtain real application ranking information.