16 results about "Social software" patented technology

This application provides a method, apparatus, device, medium, and program product for information processing, relating to the field of social software technology. The method displays a decision panel in response to a first trigger operation on a first message in a group chat interface. The decision panel includes a decision-making item obtained based on the first message and the initiator identifier of the decision-making item. In response to a second trigger operation on a second message in the group chat interface, the second message is added to the decision panel for display, serving as the user's decision opinion on the decision-making item. Therefore, when conducting decision-making discussions, users do not need to frequently browse group chat messages; they can simply view the decision-making item and opinion in the decision panel, improving decision-making efficiency and enhancing the user experience.

The invention provides a method and system for processing travel information in an online general social software chat interaction window based on a large model, and the method comprises the steps: monitoring the online general social software chat interaction window running on front-end equipment based on a monitoring agent disposed on a background server, obtaining travel information processing content represented by habitual description of the user from the travel information processing content, and generating a travel information processing request according to the travel information processing content; based on the travel information processing request, a travel information keyword model on a background server extracts travel information keywords from travel information processing content; based on the extracted travel information keyword, a processing agent on the background server sends a travel information processing request to a travel information server to return processed travel information; and the processing agent formats the returned travel information to generate a travel information processing result and displays the travel information processing result on an online general social software chat interaction window in a dialogue mode.

The invention discloses a wearable device social relation establishing method and system based on biomechanical recognition, and relates to the technical field of wearable devices and social contact. The system comprises a wearable device terminal and a social software client, wherein a biomechanical identification module, a wireless transmission module, a physical control module, a data storage module and a central processing module are arranged in the wearable device. The method is realized through the following steps: a user initializes social information and binds social software; the device enters a to-be-interacted state by pressing the'start key '; during handshaking, the equipment triggers wireless transmission through biomechanical identification, and bidirectional exchange of social information is realized; generating a friend request by the social software of the receiver; and the user completes friend addition through an enter key. Information interaction is triggered through handshake actions, the social relation establishing process is simplified, paper business cards and code scanning operation are replaced, efficiency and experience are improved, and meanwhile it is guaranteed that information is safe and controllable through physical keys.

The invention provides a social software dynamic relationship prediction method and system based on a time sequence knowledge graph. The method comprises the following steps: S1, collecting data in real time; s2, processing time sequence knowledge graph data in the time sequence knowledge graph data set by using a multi-relation time sequence graph attention network, and establishing a fine-grained model; s3, combining the fine-grained model with a GRU network to construct a time evolution path, and outputting user dynamic representation; s4, obtaining static semantic embedding of each user, and taking the static semantic embedding as semantic core representation of the user in a full time span; s5, obtaining a final user representation containing space-time semantic collaborative optimization; s6, judging whether the relation is abnormal or not through a preset abnormal threshold value, and obtaining a prediction result; according to the technical scheme, the problems that in the prior art, social recommendation cannot give consideration to time-space dynamic characteristics and semantic association of user interaction at the same time, and the accuracy of relation prediction in a dynamic scene is insufficient are effectively solved, and a new solution is provided for a social software recommendation system.

An intelligent meeting scheduling method and system based on social media conversations, for identifying meeting requirements in users'daily conversations and relevant participants and recommending suitable meeting times, includes: receiving and storing text messages including message content from a social software platform; scanning the message content to identify meeting-related terms and extract names and department names, and comparing them with organizational structure data to establish a participant list; accessing electronic calendar data of each participant in the participant list to read scheduled event information within a specified date and time range; calculating common available time slots for each participant within the specified date and time range, calculating suitability scores based on time slot scoring rules, and selecting time slots with the highest scores as suggested options; and receiving selection signals for the suggested options from participants and sending a resource reservation request to a conference room management system.

The present application relates to the technical field of data mining, and especially relates to a traffic safety public opinion analysis method based on an SQ-LDA topic model. The present application comprises the following steps: S1, obtaining traffic safety social software public opinion data; S2, preprocessing the traffic safety social software public opinion data; S3, extracting feature topics by using the SQ-LDA topic model; and S4, visualizing traffic safety social software public opinion hotspots. The sample quality negative sampling method in the SQ-LDA topic model of the present application calculates sample information quantity according to a gradient, so as to distinguish high and low quality negative samples, filter out low quality negative samples, maximize positive sample probability, minimize high quality negative sample probability, and further effectively mine and analyze traffic safety social software public opinion data. The present application sets a keyword frequency probability threshold value under a topic, and when the frequency probability of a keyword exceeds the set frequency probability threshold value, the keyword public opinion early warning under the topic will be triggered, thereby providing necessary technical support for social public opinion early warning.

The invention provides a risk detection method and device, a storage medium and electronic equipment, and the method is applied to the technical field of computers, and comprises the steps: detecting that a risk keyword exists in a social software window of a user and a first object, obtaining a social software account of the first object, and obtaining transaction data registration information of the first object in the transaction database based on the social software account, and if the transaction data registration information does not meet the transaction data exchange condition, outputting risk alarm prompt information. According to the method, the object possibly subjected to transaction data exchange can be determined by detecting the risk keyword, the transaction data registration information of the first object is searched and detected in the transaction data registration library, an alarm is given when the exchange condition is not met, prevention and control are carried out before a potential transaction data exchange event occurs, and the transaction data exchange efficiency is improved. And an unsafe transaction data exchange event is avoided.

According to the computer device disclosed by the invention, contact person information can be automatically copied after the display screen is touched due to an accident and the data interface is damaged, and the contact person information is transcribed into the second computer through voice or social software, so that the problem that a user needs to repair the touch display screen of the computer device firstly and then transcribe the contact person information is avoided.

The invention provides a social software health mode intelligent detection system and method, and relates to the technical field of image recognition and brain-like cognition inspiration artificial intelligence. According to the method, the interface image and the text content are subjected to multi-modal fusion analysis, by means of a brain-like memory and attention mechanism, whether the health mode of the social software meets the standard requirement or not is automatically judged through a brain-inspired brain-like pre-training large model, the detection intelligence degree is high, and the detection efficiency is high. Health mode prompt features in various forms such as characters, icons, interface layout and color themes can be recognized, and the detection accuracy is effectively improved; the system is high in adaptability, can adapt to different social software interface styles and hidden prompts by means of a context-guided attention mechanism and a long-term memory dynamic learning mechanism, has good generalization ability, supports real-time batch detection, and can remarkably reduce the cost of manual auditing.

The invention provides an intelligent assistant system for assisting social software dialogues and a method thereof. According to the system, a text message of a community software platform is received through a dialogue recording module, the content of the message is divided into a plurality of semantic units by a content processing module by applying a natural language processing technology, and the semantic units are converted into a newly added knowledge graph. The system is provided with a knowledge graph database for storing a preloaded knowledge graph and a newly added knowledge graph, a knowledge retrieval module queries the preloaded knowledge graph according to a semantic unit to obtain a related knowledge graph, and a reference data module generates a reference data message with relevance according to the related knowledge graph. According to the method and the device, the user can be assisted to obtain related reference information in the community conversation, and the reference information can comprise at least one of related information prompt, suggested reply content or historical related information, so that the communication efficiency is improved.

This invention relates to a time-weighted difference-aware response generation method and system based on auto-step learning. The method includes the following steps: Step A: Collect natural, open-domain dialogues from social media software, and use a retrieval system to search for relevant background knowledge of the dialogue in an encyclopedia, and label real responses and real knowledge to construct a training dataset. DE Step B: Using the training dataset DE Step C involves training a time-weighted difference-aware deep learning network model M based on a self-synchronizing learning strategy. This model selects necessary background knowledge and generates responses based on the selected background knowledge. Step C involves inputting the dialogue context and background knowledge base into the trained deep learning network model M to generate corresponding responses. This method and system help improve the accuracy of generated responses.

This invention relates to the technical field of teaching scheduling management, and discloses a method and system for visualized intelligent scheduling of student learning courses based on big data. The system includes a student preset timetable management module, a student customized timetable management module, and a student timetable comprehensive creation module. It dynamically creates personalized blank timetables for student groups based on table text processing, enabling students to rationally and scientifically arrange their course order according to their personal learning plans. Based on the blank timetable text information and contact information of target students, and combined with a course management platform and social software, it autonomously and efficiently performs the task of creating and collecting timetable text information for the target student group at specific times. Simultaneously, it combines data analysis to comprehensively analyze the existence of timetable customization results for the student group, achieving reliable timetable creation based on both preset and customized timetables, thus improving the scientific nature and personalization of scheduling management.

The invention discloses a method and system for adding entertainment content in a video call, and the method comprises the steps: S1, enabling a user to initiate a call, and carrying out the call to build a video call; s2, in the call process, waiting for an entertainment content embedding starting instruction of each terminal of the video call, and starting a video call entertainment content embedding process; s3, identifying the type of a video call entertainment content embedding process, and processing to generate an entertainment content embedding streaming media material; and S4, embedding the entertainment content embedded streaming media material into an audio and video media stream of a corresponding video call party, and putting the audio and video media stream on a corresponding terminal screen. According to the method, a technical architecture related to a new call service is utilized, the specific entertainment content embedded streaming media material is embedded into the audio and video media stream of the corresponding video call party, and the audio and video media stream is displayed on the screen of the corresponding terminal in a mixed superposition manner, so that the two call parties do not need to be based on any social software and game software; and abundant interactive entertainment behaviors can be carried out.

The invention relates to the technical field of teaching course arrangement management, and discloses a visual intelligent course arrangement method and system for student learning courses based on big data, and the system comprises a student preset course schedule management module, a student customized course schedule management module, and a student course schedule comprehensive making module. A personalized blank course schedule oriented to student group objects is dynamically established based on table text processing, so that course arrangement students can reasonably and scientifically arrange a personal course sequence based on a personal learning plan; based on target course arrangement student blank course schedule text information and target course arrangement student contact information, in combination with a course management platform and social software, autonomously and efficiently executing course schedule text information formulation and collection homework of a target student group at a specific time point; and meanwhile, whether the class schedule customization result of the student group exists or not is integrally analyzed in combination with data analysis, so that the class schedule is comprehensively and reliably formulated based on the preset class schedule and the customized class schedule, and the scientificity and individuation of class arrangement management are improved.

The invention provides a content recommendation method, device and equipment, a computer program product and a computer readable storage medium. The embodiment of the invention can be applied to content recommendation scenes of social software, video software, shopping software and the like. The method comprises the following steps: respectively carrying out feature extraction on at least two pieces of description information of to-be-recommended content in at least two modes to obtain content description features in each mode; performing common feature mapping on the content description features in each mode to obtain common description features in each mode; carrying out feature mapping on the content description features in each mode to obtain feature description features in each mode; and when a content recommendation request is received, determining target recommendation content of the content recommendation request from the to-be-recommended content based on the common description feature and the characteristic description feature of the to-be-recommended content in each mode and the object feature corresponding to the content recommendation request. According to the invention, the accuracy of content recommendation can be improved.