Abstract: In one embodiment, a method includes receiving a user query associated with dialog-intents at a client system, executing tasks corresponding to the dialog-intents, generating a multi-perspective response by a stitching model based on two or more of execution results of the tasks, wherein the multi-perspective response comprises a natural-language response combining the two or more execution results, and presenting the multi-perspective response at the client system.

Abstract: The present application discloses a method and apparatus for acquiring point-of-interest (POI) state information, a device and a computer storage medium, and relates to the field of big data. An implementation includes acquiring a text containing POI information in a preset time period from the Internet; and identifying the text using a pre-trained POI-state identifying model to obtain a binary group in the text, the binary group including a POI name and the POI state information corresponding to the POI name; wherein the POI-state identifying model performs label prediction of the POI name and a POI state on a word sequence corresponding to the text, and label prediction results of the POI name and the POI state are aligned to obtain the binary group. With the present application, a human cost may be saved, and timeliness and accuracy may be improved.

Abstract: Systems, computer program products, and methods are described herein for implementing intelligent data analysis. The present invention is configured to receive, from a computing device of a user, a first data file, wherein the first data file is associated with a base version of a data source; receive, from the computing device of the user, a second data file, wherein the second data file is associated with an updated version of the data source; initiate an intelligent data analysis engine on the first data file and the second data file; analyze the second data file to determine one or more discrepancies in relation to the first data file; determine one or more discrepancy types associated with the one or more discrepancies; retrieve, from an action datastore, one or more offset actions to rectify the one or more discrepancies; and automatically execute the one or more offset actions.

Abstract: A data management system includes a management apparatus including a processor, and plural storage devices. The processor is configured to generate hash values corresponding to data to be managed according to a predetermined calculation rule, the plural storage devices stores first hash values that are hash values generated by the processor at a first point in time, and the processor is configured to perform determination of invariance related to the plural first hash values or the data by comparing sets including the plural of first hash values read out from the plural storage devices and second hash values that are hash values regenerated according to the calculation rule at a second point in time later than the first point in time.

Abstract: In some implementations, a subscriber to an online content management system can share content items that are external to the subscriber's content library. A computing device can include managed content items associated with the subscriber's content library. The computing device can include unmanaged content items that are stored externally to the subscriber's content library. The subscriber can provide input associated with an unmanaged content item to generate a link (e.g., URL, file path, location reference, etc.) for the unmanaged content item. When generating the link, the unmanaged content item can be uploaded to the online content management system and stored separately from the subscriber's content library. The generated link can be shared with recipient user (e.g., subscriber or non-subscriber). The generated link can be used by the recipient to access the unmanaged content item uploaded to and stored by the online content management system.

Abstract: A method for changing an itinerary based on a user change request is disclosed. The method may commence with receiving an itinerary request associated with one or more passengers. The method may continue with receiving a user itinerary change request associated with the itinerary network. The method may continue with generating an itinerary object associated with the user itinerary change request. The method may continue with modifying the itinerary network based on the itinerary object. The method may continue with processing the itinerary network using a topology of the itinerary network to create a plurality of tuples, the plurality of tuples including at least flight tuples and hotel tuples. The method may continue with performing a content search for the plurality of tuples for each of the one or more passengers. The method may continue with generating feasible itinerary solutions based on results of the content searches.

Abstract: A system for and a method of using user-entered information to return more meaningful information in response to Internet search queries are disclosed. A method in accordance with the disclosed subject matter comprises managing a database in response to multiple user inputs and displaying search results from the database in response to a search query. The search results include a results list and supplemental data related to the search query. Managing the database includes, among other things, re-ranking elements in the results list, storing information related to relevancies of elements in the results list, blocking a link in the results list, storing links to documents related to the search query, or any combination of these. The supplemental data include descriptions of or indices to one or more concepts related to the search query.

Abstract: A system includes an interface, a processor, and a memory. The interface is configured to receive a version of a model from a model registry. The processor is configured to store the version of the model, start a process running the version of the model, and update a proxy with version information associated with the version of the model, wherein the updated proxy indicates to redirect an indication to invoke the version of the model to the process. The memory is coupled to the processor and configured to provide the processor with instructions.

Abstract: An overlay network is augmented to provide more efficient data storage by processing a dataset of high dimension into an equivalent dataset of lower dimension, wherein the data reduction reduces the amount of actual physical data but not necessarily its informational value. Data to be processed (dimensionally-reduced) is received by an ingestion layer and supplied to a learning-based storage reduction application that implements the data reduction technique. The application applies a data reduction algorithm and stores the resulting dimensionally-reduced data sets in the native data storage or third party cloud. To recover the original higher-dimensional data, an associated reverse algorithm is implemented. In general, the application coverts an N dimensional data set to a K dimensional data set, where K<<N. The N dimensional dataset has a high dimension, and the K dimensional dataset has a low dimension.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for conversation context profiles for use with queries submitted using social media. An example apparatus includes at least one memory, instructions, and at least one processor to execute the instructions to identify a first cloud computing resource based on an electronic message including a query, generate a conversation context profile based on overlapping attributes from at least one of a user, group, or service profile associated with the query, generate a search scope of the query to constrain first search information associated with a cloud computing system to the overlapping attributes, in response to determining that the user profile does not include the first cloud computing resource, grant access to at least one of the first cloud computing resource or second search information based on the conversation context profile, and provide one or more search results based on the search scope.

Abstract: Personalized sensory services are provided to mobile devices. As a sensor monitors an area of surveillance, the sensor may detect a passing mobile device. The sensor may thus ally itself to the passing mobile device and provide personalized sensory operations.

Abstract: Techniques are disclosed for data management techniques using artificial intelligence-based cache distribution within a distributed information processing system. For example, a cohesive and distributed machine learning approach between the same or similar customer data centers and products predict optimal data needed at each customer data center, and intelligently synchronize or federate the data between customer data centers and a core data center using a combination of customized caching and push techniques according to one or more customer behavior patterns.

Abstract: A computer-implemented method, a computer system, and a computer program product for automatically generated conversation output is provided. The present invention may include training an answer-intent classifier to associate an intent expressed in an example question with an example answer that is responsive to the example question. The present invention may further include classifying, using the trained answer-intent classifier, a content transmitted to the trained answer-intent classifier with the intent expressed in the example question in response to determining, using the trained answer-intent classifier, that the content includes relevant information for generating the example answer that is responsive to the example question.

Abstract: Techniques for generating human-readable explanations (also referred to herein as “reasons”) for navigational recommendations are disclosed. Composing a human-readable explanation includes individually selecting words or phrases that are then analyzed, combined, rearranged, modified, or removed to generate the human-readable explanation for a navigational recommendation. A decoder trains a machine learning model to generate the human-readable reasons for the navigational recommendations based on (1) historical recommendation vectors, and (2) historical human-readable reasons associated with the recommendation vectors. The system generates a dictionary of human-readable reasons for recommendations, with each entry of the dictionary including: (1) a recommendation identifier (ID) associated with a recommended navigational target, (2) a reason identifier (ID) associated with a particular reason for the recommendation, and (3) a human-readable reason associated with the reason ID.

Abstract: Systems and methods are provided for data migration. The system may comprise one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to migrate at least one first table of a first database schema to at least one second table of a second database schema, determine a query for modifying the first table during the migration, modify the second table based at least in part on the query, and update a mutation table to describe the modification, wherein the mutation table at least describes the modification.

Abstract: A computer-implemented system and method for predicting and flagging an anomaly entered in a digital form. A server computing device classifies a plurality of data fields of the digital form to identify a set of non-zero value data fields; and obtains an anomaly detection model comprising a statistical tree structure associated with the data field of the digital form. The server computing device receives datasets including a target value of a data field and values of a set of cohorting data features; traverses a statistical tree structure of the anomaly detection model with the target dataset to form a set of target cohorts to determine a target statistic value for the data field; flags the data field value of the target dataset as an anomaly item; and generates one or more confidence scores for a runtime prediction based on one or more variance changes for the data field.

Abstract: Systems and methods are described for processing ingested data using an online machine learning algorithm as the data is being ingested. For example, the online machine learning algorithm can be an adaptive thresholding algorithm used to identify outliers in a moving window of data. As another example, the online machine learning algorithm can be a sequential outlier detector that detects anomalous sequences of logs or events. As another example, the online machine learning algorithm can be a sentiment analyzer that determines whether text has a positive, negative, or neutral sentiment. As another example, the online machine learning algorithm can be a drift detector that detects whether ingested data marks the start of a change in the distribution of a time-series.

Abstract: The disclosure includes a method for retrieving information stored in a cloud capable database. —A user has an OPC UA client, which is connected for communication with an OPC UA server, wherein the OPC UA server is used for the creating, aggregating and conforming of information models, wherein the OPC UA server interacts with an API for accessing the database, including: creating and loading a user-specific information model into the OPC UA server by using the configuration module, wherein the user-specific information model defines one or more pieces of information to be queried from the database; querying information defined in the user-specific information model from the database using the API and transferring the information from the API to the OPC UA server; converting the queried information into OPC UA-conforming structure data; and sending the structure data from the OPC UA server to the OPC UA client.

Abstract: Various methods, apparatuses/systems, and media for implementing a data quality check module for determining whether data is acceptable or not are disclosed. A processor collects all facts data corresponding to an agreement based on corresponding received distribution event data in accordance with margin requirements associated with the agreement and calculates statistical analysis data based on historical data points of the facts data for the agreement. The processor also creates and configures dynamic rules that are required to be applied for determining whether the agreement is in good order; verifies the statistical analysis data against the rules to determine anomaly data; marks the agreement as a good order agreement flag when it is determined that the anomaly data is within a predetermined threshold value; and automatically executes, in response to marking the agreement as a good order agreement flag, a straight through processing of the agreement.

Abstract: Computer-implemented systems and methods are disclosed for indexing and aggregating proxy server data. In accordance with some embodiments, the systems comprise a memory device configured to store a set of instructions, and one or more processors configured to execute the set of instructions to receive a plurality of log lines of proxy server data comprising a plurality of data components and index one or more of the plurality of data components for the plurality of log lines. The processors also generate a plurality of log data records, each including the one or more indexed data components, and generate a summarized data record by aggregating one or more log data records having at least one matching indexed data component.