Abstract: A user of a network-based system may correspond to a user profile that describes the user. The user profile may describe the user using one or more descriptors of items that correspond to the user (e.g., items owned by the user, items liked by the user, or items rated by the user). In some situations, such a user profile may be characterized as a “taste profile” that describes an array or distribution of one or more tastes, preferences, or habits of the user. Accordingly, the user profile machine within the network-based system may generate the user profile by accessing descriptors of items that correspond to the user, clustering one or more of the descriptors, and generating the user profile based on one or more clusters of the descriptors.

Abstract: The technology described herein is directed to generating prompts for a language model, such as a large language model. In this regard, an enterprise interpretation model may receive a request for assistance with an enterprise application record. In response to receiving the request for assistance, the enterprise interpretation model may determine data corresponding to the record. Based on the determined data, the enterprise interpretation model may generate a query corresponding to the record. The query may include at least a subset of the data corresponding to the record. The query may then be provided to the language model for a response to be generated.

Abstract: A hybrid artificial intelligence (AI) agent balances use of a plurality of predefined decision tree flows and one or more large language model (LLM) chatbots. A query is received from a user client device that is associated with a user. A routing LLM of the hybrid AI agent determines an intent of the user based in part on context associated with the query. The routing LLM selects a response model from the plurality of predefined decision tree flows and the one or more LLM chatbots based in part on the intent. The selected response model is used to determine a response to the query. The response is provided to the user client device.

Abstract: A data management system may maintain a total-size counter for the file system. The total-size counter represents a sum of data size related to snapshots backed up to the file system. The data management system may perform data operation cycles to the file system. Each data operation cycle corresponds to a snapshot that includes files. Each data operation cycle may include incrementing the total-size counter by the data size of the files in the snapshot exchanged with the file system and adding, to a snapshot record, the amount of increment in incrementing the total-size counter as an increment-size counter. A data management system may perform a correction operation to correct the total-size counter. The correction operation may change the total-size counter by a difference between the total of the increment-size counters in the snapshot records and the total data size of file data exchanged with the file system.

Abstract: Automated content recommendation is used in conferencing. In one embodiment, a system receives a list of content recommendation actions. The system receives a number of utterances associated with the participants in real time. For each utterance, the system determines whether a prediction of relatedness is present between the utterance and one or more trigger phrases associated with a content recommendation action. Upon determining that a prediction of relatedness is present, the system performs the associated content recommendation action by transmitting, to one or more client devices, one or more pieces of content to be recommended.

Abstract: In one aspect, a query management module executing on a processor receives, from a large language model (LLM), a graph query generated by the LLM based on a natural language query (NLQ). A validation module identifies an error in the graph query. The query management module provides an indication of the error to the LLM. The query management module receives a modified graph query from the LLM. The validation module validates the modified graph query. Based on the validation of the modified graph query, the query management module executes the modified graph query against a knowledge graph to return a result as a response to the NLQ.

Abstract: A request for information (RFI) system is provided for use in communications networks including broadcast networks and the Internet. In one implementation, a code identifying an item of media content of interest (e.g. television, newspaper, magazines, billboards, radio) is captured and input to an RFI system that includes stored media tags and a search tool for matching inputs to the stored media tags. Upon receipt of the captured code, the RFI system matches the captured code with the stored media tags and provides a response to the user based on the match. The response may include or relate to follow-on or premium information relating to the content of interest. Using this information, an RFI data center or an RFI platform may credit value to a rewards account established for the network user based on the user's verified consumption of assets and/or data requests.

Abstract: A method of latent intent clustering is provided. The method comprises encoding identified features in a number of electronic user reports in a database. A binary matrix is created, wherein each row of the binary matric represents a different report and each column represents a different available feature. A 1 is placed in each cell of the matrix that matches a feature present in a user report. Cosine similarities are calculated for the user reports, and a similarity matrix is created, wherein each row and column of the binary matrix represents a different report, and wherein the cosine similarities of the reports are placed in corresponding cells of the matrix. The reports are clustered according to the cosine similarities. Features common to reports in each cluster are identified, and an intent of each report cluster is labeled according to the common features.

Abstract: Disclosed is an approach to autonomously abort a lower priority transaction that is blocking a higher priority transaction, where the lower priority transaction is holding a lock on a resource for which there is contention. Some approaches also provide an efficient way to implement identification of a blocker transaction, which drastically reduces the response time to abort the blocker transaction.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a source independent query language. One of the methods includes receiving, by a computer system, a statement to perform operations on data stored in a data storing application, the data including fields. The method includes identifying a query language based on the data store. The method includes transforming the received statement into a query language specific statement. The method includes identifying at least one operation of the operations that is not supported by the query language specific statement. The method includes obtaining a function to replace the unsupported operation. The method includes applying the function to the query language specific statement. The method also includes providing the query language specific statement to the data storing application for processing.

Abstract: Name caching can be used external to a distributed file system (DFS), such as a network file system (NFS), to reduce the complexity of facilitating a file operation at the DFS. A system that can use the name caching and request the file operation of the DFS can comprise a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. The operations can comprise, in response to a lookup operation or a file operation performed by a DFS, storing, using the processor, a name cache entry for each directory element accessed during the lookup operation or the file operation. The operations further can comprise sending, to the DFS, a single request that comprises a compound command comprising requests for a set of lookup operations and for a file operation.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer-readable media that more accurately determine matches between data identifiers based on data identifier reconstruction. For example, the disclosed systems determine a cognate dataset which can include a data identifier associated with a source individual along with data identifiers of individuals related to the source individual. From the cognate dataset, the disclosed systems can reconstruct a data identifier for a precursor entity of the source individual. In some embodiments, the disclosed systems can determine a data link between a target individual and the source individual by determining a data link between the reconstructed data identifier and the target individual and by modifying the data link based on a relationship between the precursor entity and the source individual.

Abstract: Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support generative artificial intelligence (AI)-assisted analytics of structured data sets. For example, a system may receive a prompt that includes information associated with a structured data set which includes at least some numerical data. The system may provide the prompt as input to an agent orchestrator to select one or more generative AI agents to perform analytics tasks corresponding to the information. The agent orchestrator includes a trained AI classifier configured to select the one or more generative AI agents from a plurality of generative AI agents. The system may execute an ensemble model to generate a response to the prompt based on the structured data set. The ensemble model includes the one or more generative AI agents. The system may output a graphical user interface (GUI) that includes one or more elements based on the response.

Abstract: Methods and systems are described herein for novel uses and/or improvements to artificial intelligence applications for data-sparse environments. As one example, methods and systems are described herein for overcoming the problem of determining an appropriate digital asset to recommend to a user in real-time based on training data that may be shared between multiple intents (e.g., as would be found in responses to textual, verbal, and/or other real-time communications). In particular, the methods and systems overcome this technical problem by using an artificial intelligence trained to identify specific verbiage of a user to display digital assets corresponding to a user's intent thereby increasing productivity, organization, and collaboration, and reducing frustration.

Abstract: Systems and methods are disclosed for implementing a low-latency data stream monitoring system. The data stream monitoring system may obtain raw data from a data source as soon after the data is generated, and may classify the data according to different topics. The topics may be published in a publish-subscribe messaging model, and data enrichment systems may subscribe to the topics to receive data for enrichment. The data enrichment systems may supplement or replace the raw data with additional information, and may further classify or reclassify the enriched data into different topics. The enriched data may then be published to an alert generation system, which may apply various criteria to the enriched data to determine that alerts should be generated, generate the alerts, and publish or transmit the alerts to client devices. Individual data streams, topics, enrichments, criteria, and alarms may be added, removed, or modified as required.

Abstract: A device for providing tourism information and a method thereof are proposed. The method of operating an electronic device configured to provide the tourism information about a cultural heritage includes obtaining user information, providing first tourism information corresponding to the user information from a pre-stored tourism database, and providing second tourism information on the basis of the user information, wherein the second tourism information is information related to the first tourism information.

Abstract: Embodiments of the present disclosure relate to an information presentation method and an apparatus, a device, and a medium. The method includes the steps described below. Collection information of at least one collection is acquired. The collection information includes title information of each collection and attribute information of multiple entities in the each collection. Attribute information of each entity matches the title information of the each collection. All or part of the collection information of the at least one collection is presented.

Abstract: A user interface of an online system is generated based on search for relevant items that match ingredients of a recipe. After receiving, from a device associated with a user of the online system, a query for an ingredient of a recipe, the online system identifies, based on one or more attributes in the query, a set of candidate items for the ingredient. The online system generates a recipe relevance score for each candidate item by applying a weighted sum of scores, ranks the identified candidate items based on their recipe relevance scores, and selects one or more items for presentation to the user. The online system then generates a user interface of the device with a recipe page including the ingredient of the recipe and the one or more items that match the ingredient of the recipe.

Abstract: Techniques are described for automatically converting a standard operating procedure (SOP) into a simulatable non-ambiguous single state machine (SSM) architecture in which a given input (transition condition) necessarily and unambiguously moves the system from a first state to a predictable second state. By converting a written SOP into a simulatable non-ambiguous SSM architecture, the techniques described herein reduce the possibility of errors and improve the safety, efficiency, and operational performance of the system. The described techniques also allow the architecture, and indeed the entire system, to be simulated.

Abstract: A data creation device that is a training data creation device for creating training data which is used for deep learning of an object detection program for detecting whether or not an object is included in an image, includes: an acquisition unit that acquires an anchor that is information on a frame specifying an area for each cell for detecting presence or absence of the object from the image; and a creation unit that associates area information of the object with image data to create the training data that includes a plurality of image data in which the area information is included. The creation unit determines a frame of the area information, based on a position of the anchor.