18 results about "Online chat" patented technology

Systems and methods for expanding chat communication groups based on a chat context are provided. In an example, a chat and video conference provider establishes a first chat communication group for exchanging chat messages between a plurality of client devices and generates a chat summary for a subset of the chat messages within the first chat communication group. The chat and video conference provider determines a relevant user of the first chat communication group based on the chat summary and provides a recommendation for inviting the relevant user a second chat communication group. The chat and video conference provider establishes the second chat communication group and presents the chat summary in the second chat communication group in response to the relevant user joining the second chat communication group.

Methods and systems are presented for providing automated online chat assistance in an online chat session. One or more utterances transmitted from a user device of a user via the online chat session are obtained. The one or more utterances are provided to a first prediction model to predict an intent of a user. If it is determined that the first prediction model is unable to predict the intent of the user based on the one or more utterances, the one or more utterances are provided to a second prediction model. After predicting the intent of the user by the second prediction model, the intent is used by a chat robot to provide a dialogue with the user via the online chat session. The one or more utterances and the predicted intent are used to re-train the first prediction model.

Systems and methods for increasing accuracy in an online chat interface are provided. Methods may be executed via a machine-learning (ML)-based chat monitoring engine. Methods may include intercepting a request utterance. Methods may include computing, via a trained ML model, an intent of the request utterance; generating a target response to the request utterance; intercepting a response utterance; and calculating a difference between the response utterance and the target response. In response to the difference being less than a threshold difference, methods may include releasing the response utterance to be transmitted as a response message. In response to the difference being more than a threshold difference, methods may include preventing the response utterance from being transmitted as a response message, generating a revised response utterance that is less than a threshold difference apart from the target response, and transmitting the revised response as a response message to a remote computing device.

The present invention relates to a robust text steganography method based on feature space and its application. The method converts a preset text into a specified image format, encodes it with the original carrier through separate encoders, and then combines it in the feature space. A decoder then obtains the carrier containing the encrypted steganographic information. After the carrier containing the encrypted steganographic information is transmitted to a recipient via a channel, an extractor retrieves the image currently corresponding to the preset text, and converts it to obtain the preset text. The method is applied to online chat scenarios. The method has a larger steganographic capacity, meets the purpose of text steganography, has a faster generation speed and better image quality, reduces model training pressure, reduces computing power requirements, and has good robustness to resist certain degrees of noise and carrier image influence, which is conducive to further commercial application.

Example methods and systems recommend and summarize unread messages for a user on an online chat platform. A client device accesses multiple unread messages associated with the user, and a machine learning (ML) model provided by the online chat platform. The client device selects one or more unread messages from the multiple unread messages using the ML model trained with historical chat data and user metadata. The client device also generates a summary of some or all of the unread messages using a second ML model trained with the historical chat data and the user metadata. The indication of the selected unread messages and the summary of unread messages are displayed on the client device.

There are provided systems and methods for dynamically rendered interface elements during online chat sessions. A user may engage in online communications with another user, such as a communication session between a customer and a customer representative or agent of a merchant. During this communication session, the agent may navigate to particular data on the agent's device, which may be desirable to provide to the customer. For example, the agent may view a particular item of interest to the customer. An application programming interface of the merchant may detect one or more actions or calls associated with this data and may dynamically provide an interface element to transmit data displayed on the agent's device to the customer's device during the communication session. The customer may view a dynamically rendered interface element that allows for processing data during the communication session with the agent.

Systems and methods for expanding chat communication groups based on a chat context are provided. In an example, a chat and video conference provider establishes a first chat communication group for exchanging chat messages between a plurality of client devices and generates a chat summary for a subset of the chat messages within the first chat communication group. The chat and video conference provider determines a relevant user of the first chat communication group based on the chat summary and provides a recommendation for inviting the relevant user a second chat communication group. The chat and video conference provider establishes the second chat communication group and presents the chat summary in the second chat communication group in response to the relevant user joining the second chat communication group.

The invention provides an anonymous online chat management interaction method and system, and relates to the technical field of computer network communication and information security, and the method comprises the steps: a user uploads a user attribute through a client, a server carries out the virtual portrait processing of the user attribute, and carries out the matching based on a virtual user portrait. And establishing a double-blind session channel based on a matching result, and identifying and judging a message sent by the user. According to the method, the performance of the anonymous chat system is remarkably improved through quadruple innovation: a virtual portrait noise injection mechanism is created for the first time, and the de-anonymization risk is reduced while the age / gender screening capability is kept; based on semantic matching of improved BERT, the accuracy is improved, and the efficiency is improved; the client deploys a lightweight multi-task model to realize sensitive content interception without privacy leakage; the dynamic permission matrix supports minute-level permission adjustment, the high-risk response time is compressed to the second level, and collaborative optimization of matching accuracy, management flexibility and communication efficiency is achieved on the premise that privacy is guaranteed.

The invention provides a memory conflict-based personification reply method for virtual human online chat, which belongs to the technical field of artificial intelligence virtual human interaction and comprises the following steps of: extracting important activities / events from historical chat input of a user as memory contents; generating conflict behaviors and corresponding reminding verbal skills based on the memory contents, and constructing a memory conflict library in a triple form of the memory contents, the memory conflict behaviors and the reminding verbal skills; performing semantic similarity matching on the current input of the user and conflict behaviors in the memory conflict library; and guiding the large language model to generate anthropomorphic reminding and exhorting verbal surgeries based on a matching result. Accurate triggering of conflict memory is achieved, virtual human reply fits the association between the historical intention of the user and the current behavior, and the anthropomorphic degree of interaction and the user experience are remarkably improved.

A system and a method for responding to user messages during an online chat conversation include: a computing system including a processor executing computer-readable instructions stored in a storage device; a chatbot; an AI server; and a network connection operatively connecting a user device to the computing system. The computing system performs steps of: establishing a chat conversation between the chatbot and the user device; receiving a chat message from the user device, the chatbot then sending chat history contextual data to the AI server and requesting quick replies from the server; the server responding to the request by sending to the chatbot at least one of the quick replies including a matching intent; and the chatbot sending to the user device the quick replies; and the quick replies being displayed by the user device on a display screen visual representation of a portion of the chat conversation.

Provided is a method for providing a pickup service using a plan position indicator, wherein, after checking the appearance of the counterpart offline, the user can determine whether to meet same through an online chat. This method for providing a pickup service comprises the steps of: receiving first situation information, a first GPS location, and a first search radius from a first terminal; displaying a plan position indicator on the screen of the first terminal upon receiving a search request from the first terminal, and displaying at least one second terminal located within a first search radius around a first GPS location on the plan position indicator according to the distance and azimuth; transmitting second situation information regarding the selected second terminal to the first terminal if a terminal selection event regarding one of at least one second terminal occurs from the first terminal, and transmitting a first notification to the selected second terminal; transmitting a second notification to the selected second terminal if a chat request event occurs from the first terminal in response to the second situation information; and generating a chat room for direct communication between the first terminal and the selected second terminal if an acceptance event occurs from the selected second terminal in response to the second notification.

The invention provides a cross-channel abnormal information aggregation management method and device, equipment and a medium. The method comprises the following steps: acquiring different types of customer service system data information in different regions; based on the obtained customer service system data information of different regions and different types, key information which is related to the abnormity and meets preset requirements is extracted; performing anomaly judgment on the extracted key information which is related to the anomaly and meets a preset requirement by utilizing a detection model to obtain anomaly information; and associating and aggregating different abnormal information belonging to the same client request through the unique identifier of the client request. According to the invention, through a unified data access layer and distributed database storage, unified collection of data of different regions such as national outlets, provincial companies, headquarters and the like and different types of systems such as telephone customer service, online chat, mail customer service and the like is realized, and a traditional collaboration barrier caused by independent storage and incapability of intercommunication of data of each system is avoided.

A method includes receiving a plurality of textual data from one or more users within an online chat group. The method also includes rendering the plurality of textual data for each user of the online chat group. The method includes further enabling one user from the online chat group to edit a textual data originated by another user from the online chat group. A notification is rendered on a graphical user interface (GUI) that the textual data originated by the another user has been edited. In response to a user selection thereof, the edit is accepted, rejected, or further edited.

The invention relates to the technical field of the Internet, in particular to an AR-based card interaction method and a related device, which are used for improving the interactivity and playability of an entity card in an online chat scene. The method comprises the following steps: presenting a chat interface containing an interactive control; the interaction control is used for arousing an AR card interaction function; in response to an interaction operation triggered by the initiator object for the interaction control, presenting a card interaction area in the chat interface; when a first card input by the initiator object is recognized in the card interaction area, presenting an initiator AR picture including a first virtual character corresponding to the first card, and sharing the initiator AR picture to at least one receiver object of the initiator object; the first virtual character is a virtual content generated in combination with an AR technology after entity identification is performed on the first card. In the online chat scene, the card is combined with the AR technology to generate the corresponding virtual character, so that the interactivity and playability of the entity card in the online chat scene are improved.

A method includes receiving a user indication to create an online collaborative team within an online chat environment. The method further includes receiving a user selection of members for the online collaborative team. The online collaborative team enables the selected members of the online collaborative team to communicate with one another. The online chat environment maintains communication of the members and activities of the members of the online collaborative team. The online chat environment makes the activities and the communication available to the members when the members are within the online chat environment. The method further includes accessing attributes associated with the members of the online collaborative team. The method, responsive to the accessing the attributes associated with the members, determines a privacy setting of the online collaborative team.

Example methods and systems facilitate user actions during a chat session on an online chat platform. A client device is installed with a chat and video conference application. The chat and video conference application includes a machine learning (ML) model. The client device receives a chat message during a chat session and identifies an action item from the chat message using the ML model. One or more GUI elements can be generated associated with a functionality of an application corresponding to the action item. A GUI element can be activated to invoke the functionality of the application.

System and method facilitating real-time communication between users through an online chat interface. An application allows users to create an account and interact through a touch screen user interface. A real-time list of online users is created, and a primary user live chats with a selected chat partner displayed in a chat window. The user interface allows the primary user to select a new chat partner by swiping on the interface. Video quality may be adjusted using an adaptive bandwidth management system, providing a tactile response when the user interacts with the interface, implementing a multi-layered security protocol for safe data transmission, and running a load forecasting algorithm to predict user activity. A dummy version of the new chat partner is created and presented to the primary user before establishing a live chat.

A question is posed by a user of a user device as part of an online chat session with an online system. An intake artificial intelligence (AI) agent interacts with the user via the online chat session in one or more rounds of messaging to gather information that may be used by a human agent to respond to the question. At some point, the online system may identify in an output of the intake AI agent an indication that there is sufficient context regarding the question to transfer the question to the human agent. The online system provides session information (e.g., the question and gathered context) to a user device associated with the human agent. The human agent may use the session information to develop a response to the question that may be provided to the user.