5 results about "Discussion group" patented technology

1. The name of the design product: related data display graphical user interface for electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the interface is used to display ongoing data, completed data, quick join, etc. 7. The human-computer interaction mode of the graphical user interface: in the design 1 front view, the user can click the data card of the "in progress" module to quickly rejoin the corresponding discussion group and participate in the chat; can click the data card of the "completed" module to quickly rejoin the corresponding discussion group to view the chat content; can also click any control in the interface to perform the corresponding operation. The human-computer interaction descriptions of design 2, design 3 and design 5 are the same as design 1. In the design 4 front view, the user can click the data card of the "in progress" module to quickly rejoin the corresponding discussion group and participate in the chat; can also click any control in the interface to perform the corresponding operation.

The invention discloses a video conference grouping method and a video conference system. The method comprises the steps that user performance information of participants participating in a video conference is acquired, and the user performance information of the participants comprises first video information, first voice information and operation record information of the participants; and conference content information of the video conference is acquired, and the conference content information comprises second video information and second voice information. And based on a preset user attribute analysis model, determining a user attribute analysis result according to the conference participant user performance information and the conference content information. And under the condition that the video conference needs to perform grouping discussion on the participants, performing grouping processing on the participants according to the user attribute analysis result. Thus, the user attribute analysis result is determined by collecting related information and combining the preset user attribute analysis model, grouping is performed, and the member structure in each discussion group is rationalized, so that the participation degree and discussion depth of participants in each discussion group are improved.

This application discloses an AI-based multi-user science popularization knowledge interaction method and system, relating to the field of intelligent question-answering technology. The method includes: acquiring historical input content from all users in a discussion group to construct a semantic graph; identifying consensus patterns by scanning the semantic graph and generating consensus proposals for each pattern; pushing the consensus proposals to all users in the discussion group for consensus feedback operations and determining the status of the consensus proposals; parsing real-time input content to detect whether there is a conflict between the input content and active consensus; if a conflict exists, determining the conflict pattern, confirming the conflict confidence level, and generating an early warning; evaluating the input content through a deviation analyzer to calculate the deviation concentration and diffusion rate; triggering a risk warning when the deviation concentration exceeds a deviation concentration threshold and the diffusion rate exceeds a diffusion rate threshold, scheduling an AI role model as a virtual participant to publish guiding content for corrective intervention, and calculating a correction effect index.

1. The name of the design product: recommended card display graphical user interface for electronic devices. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the interface is used to display recommended cards, card information preview, etc. 7. The human-computer interaction mode of the graphical user interface: in the design 1 front view, the user can swipe up and down the card to switch and view more recommended cards; can click on the card to enter the discussion group to watch or participate in the discussion. In the design 2 front view, the user can click on the card to enter the discussion group to watch or participate in the discussion. In the design 3 front view, the user can swipe left the card to switch and view more recommended cards; can swipe left the comment at the bottom of the card to view more comment content; can click on the card to enter the discussion group to watch or participate in the discussion. The human-computer interaction description of design 4 and design 5 is the same as design 1.

This application relates to a method and system for generating user topic tags based on WeChat Work discussion groups. The method includes: a word vector training step, where different discussion tags are preset according to industry type, and corresponding external word vectors are obtained by filtering them; the external word vectors are combined with conversation archives to train word vectors; a priority word acquisition step, where the similarity between the word vectors and the discussion tags is calculated, and word vectors that meet preset conditions are added to a priority word list; a conversation tagging step, where conversation archives are scanned using a word segmentation system and tagged according to priority words and preset stop words; and a topic tag generation step, where the tagging results are processed to obtain user topic tags. This application enables the rapid construction of user discussion topic tags from massive amounts of user conversation information.