Abstract: A face recognition method and apparatus, and a storage medium are provided. The method includes: performing attribute feature extraction on an image to be processed including a target object to obtain N attribute features of the target object, N being an integer greater than 1; performing attention feature extraction on the image to be processed based on an attention mechanism to obtain N attention features of the target object; clustering the N attention features to obtain M clustered attention features, M being a positive integer and M<N; and determining the face recognition result of the target object according to the N attribute features and the M clustered attention features.

Abstract: A face recognition method and apparatus, and a storage medium are provided. The method includes: performing attribute feature extraction on an image to be processed including a target object to obtain N attribute features of the target object, N being an integer greater than 1; performing attention feature extraction on the image to be processed based on an attention mechanism to obtain N attention features of the target object; clustering the N attention features to obtain M clustered attention features, M being a positive integer and M<N; and determining the face recognition result of the target object according to the N attribute features and the M clustered attention features.

Abstract: Techniques for generating an assessment question about content of an educational course include obtaining, by processing circuitry of a computer, an electronic document of content of the course and generating a parsable text version of the electronic document. Importance scores for sentences of the parsable text version of the electronic document are generated and a sentence having an importance score that exceeds a first threshold value is identified. A key phrase in the identified sentence is identified, where the identified key phrase has a key phrase score that exceeds a second threshold value, and an assessment question about the content of the course related to the identified sentence is generated, where the assessment question is based on the identified sentence but where the identified key phrase is not present in the assessment question.

Abstract: In one general aspect, a method can include identifying a current user state, associating a first action and a second action with the current user state, associating a first value and a first probability with a first new user state based on a possible performing of the first action in the current user state, associating a second value and a second probability with a second new user state based on a possible performing of the second action in the current user state, calculating a first overall value for the first action based on the first value and the first probability, calculating a second overall value for the second action based on the second value and the second probability, and providing the first action to the computing device based on determining that the first overall value is greater than the second overall value.

Abstract: Techniques for generating an assessment question about content of an educational course include obtaining, by processing circuitry of a computer, an electronic document of content of the course and generating a parsable text version of the electronic document. Importance scores for sentences of the parsable text version of the electronic document are generated and a sentence having an importance score that exceeds a first threshold value is identified. A key phrase in the identified sentence is identified, where the identified key phrase has a key phrase score that exceeds a second threshold value, and an assessment question about the content of the course related to the identified sentence is generated, where the assessment question is based on the identified sentence but where the identified key phrase is not present in the assessment question.

Abstract: Techniques of providing references to students of massive open online courses (MOOCs) involve automatically providing references based on semantic content of queries generated within a MOOC. Along these lines, a computer browser in which a user interacts with a MOOC may generate queries for additional reference material to supplement its content. For example, the browser may generate a query based on the results of an exam taken by a student in order to provide additional help in areas where the student did not do well. When the query is received by a reference generating server, the reference generating server computes similarity scores indicating a measure if similarity between keyword elements of the query and keyword elements of reference documents. The reference generating server then sends references to the student based on the similarity scores.

Abstract: A method includes receiving, by a computer, a video file containing audio content and or visual content. The method further involves, based on a determination of the rates at which information is communicated by different temporal segments of the video file when played back at a default playback speed, assigning a respective target playback speed to each the different temporal segments of the video file. The video file is edited and marked in a format to be played back on a video player so that each of the different temporal segments of the video file can be played back at its respective assigned target playback speed.

Abstract: A method includes receiving, by a computer, a video file containing audio content and or visual content. The method further involves, based on a determination of the rates at which information is communicated by different temporal segments of the video file when played back at a default playback speed, assigning a respective target playback speed to each the different temporal segments of the video file. The video file is edited and marked in a format to be played back on a video player so that each of the different temporal segments of the video file can be played back at its respective assigned target playback speed.