Abstract: A method and system of data deduplication for data streams in a multi-tenant system. The method receives, at a data accuracy manager, an event from an activity tracking component, determine whether the event is recorded in a probabilistic model that tracks previously received events from the activity tracking component, where the probabilistic model can accurately identify the event has not been previously received with a possible false positive response where the event has been previously received, determines whether information for the event is stored in a metric storage, where the metric storage is a database of metrics derived from the previously received events, and discards the event in response to determining that the event is recorded in the probabilistic model and in the metric storage.

Abstract: There is provided computer implemented method for detecting and reducing or removing bias for generating a machine learning model, comprising: prior to generating the machine learning model: receiving a training dataset, comprising target inputs, each comprising parameters and labelled with a corresponding target output, wherein at least one of the parameters of at least of the target inputs comprises a sensitive parameter indicative of the corresponding target input assigned to a sensitive group that is potentially biased against other target inputs that are excluded from the sensitive group, analyzing the training dataset to identify target inputs affected by label bias when a statistically significant difference is detected between target inputs assigned to the sensitive group and target inputs excluded from the sensitive group, correcting labels of the target inputs affected by label bias, and generating the machine learning model using the corrected labels.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for appending data to large data volumes in a multi-tenant store. These mechanisms and methods for appending data to large data volumes can enable embodiments to provide more reliable and faster maintenance of changing data. In an embodiment and by way of example, a method for appending data to large data volumes is provided. The method embodiment includes receiving new data for a database. The new data is written to a temporary log. The size of the log is compared to a threshold. Then the log is written to a data store, if the size of the log is greater than the threshold.

Abstract: Described herein are systems, apparatus, methods and computer program products configured for actions to be performed on segments within a pipeline. The disclosed systems and techniques allow a user to select a data segment on a graphical user interface. The user may then utilize the data of the segment to perform one or more actions. Thus the data of the segment may be used to provide communications to parties contained within the data, manipulate the data segment based on the parties contained within the data, and change the data displayed based on attributes selected.

Abstract: Described herein are means for implementing consensus on read via a consensus on write smart contract trigger for a Distributed Ledger Technology (DLT) platform in conjunction with a cloud based computing environment.

Abstract: Provided herein are system, methods and computer program products for using a bot server for initiating and controlling bot instances, specifically conversation bot instances at client devices for interacting with users associated with the client devices. The bot server may communicate with a remote cloud service providing bot services for initiating and operating the bot instances to retrieve logic metadata used to control the bot instances and may use this metadata to initiate and control one or more bot instances at the client devices to interact with the associated users. In particular, the bot server may be deployed at a network edge in close network proximity to the client devices.

Abstract: There are provided mechanisms and methods for maintaining data stored in a data structure. These mechanisms and methods for maintaining data stored in a data structure can provide maintenance operations with improved efficiency, functionality, etc.

Abstract: A request to exchange of a first quantity of a first fungible digital token type stored within a smart contract instance recorded in a public trust ledger and owned by a first party within the public trust ledger may be received via a communication interface at a database system. The request may authenticate a first account in the database system. The first account may be linked with the first party within the public trust ledger. The smart contract instance may be executed to determine whether the requested exchange is permissible based on one or more transaction rules included within the smart contract instance. The database system may be updated to reflect a transaction recorded within the public trust ledger when it is determined that the requested exchange is permissible.

Abstract: A request to perform an action related to a smart contract recorded on a public trust ledger external to the database system may be received via a communication interface at a database system. The request may authenticate a designated database system account. A determination may be made as to whether the designated database system account is authorized to perform the action by accessing definition information for a public trust ledger synthetic party identifying a plurality of database system accounts authorized to perform one or more actions related to the smart contract. The database system may communicate with a token exchange to perform the action by executing the smart contract when it is determined that the designated database system account is authorized to perform the action.

Abstract: Systems and techniques for managing data in a relational database environment and a non-relational database environment. Data in the relational database environment that is static and to be maintained beyond a preselected threshold length of time is identified. The data is copied from the relational database and stored in the data the non-relational database. Access to the data is provided from the non-relational database via a user interface that accesses both the relational database and the non-relational database.

Abstract: System, method, and/or computer program product embodiments for automatic removal of sensitive data items from records are disclosed. In one or more embodiments, a record with a sensitive field (for storing a sensitive data item) is linked to a self-removal data policy that includes a condition set. When the condition set is true, the sensitive data item is automatically removed from the record without deleting the record and without removing other data items stored in other fields of the record. Conditions may be associated with a time period following the upload or storage of the sensitive date item, the occurrence of an event that requires the sensitive date item, a read or approval of the sensitive data item, etc. A user may modify a condition in the condition set to make the condition more stringent or less stringent.

Abstract: A message batching configuration may be determined for transmitting a message to recipients. The message batching configuration may include two or more message batches, a respective recipient count for each message batch, a respective time delay between each message batch, and a performance metric for evaluating the message. The message is transmitted in accordance with the message batching configuration. The transmission of subsequent message batches is halted when it is determined that the designated performance metric fails to meet a designated performance metric threshold.

Abstract: A first message indicating that a first digital token created within an on-demand database system and recorded in a public trust ledger external to the on-demand database system has been transferred from a first party within the public trust ledger to a second party within the public trust ledger may be received. The on-demand database system may communicate with the public trust ledger to add a wallet account as a secondary owner to a smart contract that includes a second digital token. The smart contract may identify one or more conditions for transferring the second digital token to the second party. A second message identifying the second digital token may be transmitted to the second party within the public trust ledger.

Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for dynamically configuring a hardware device. A hardware configuration descriptor can be customized, where the hardware configuration descriptor includes a set of hardware interface attributes for use in configuring hardware interfaces of a hardware device and indicates one or more web addresses corresponding to computer-readable instructions configurable to control operation of the hardware device during runtime. The hardware configuration descriptor can be transmitted to the hardware device responsive to a request from the hardware device. The hardware device automatically applies the hardware configuration descriptor to configure its interfaces and subsequently accesses the web addresses during operation of the hardware device.

Abstract: A computer-implemented database system as described herein includes a memory device and one or more processors coupled with the memory device. The one or more processors are configurable to create and maintain a folder structure for a user interface (UI) environment, wherein the folder structure includes: a feature folder that defines an application feature supported by the UI environment, the application feature having a UI component associated therewith, and the UI component having a UI text string associated therewith; a component folder located in the feature folder, the component folder having computer readable files that define the UI component; and a text string file located in the component folder, wherein the text string file defines content of the UI text string.

Abstract: Embodiments described herein provide an attentive network framework that models dynamic attributes with item and feature interactions. Specifically, the attentive network framework first encodes basket item sequences and dynamic attribute sequences with time-aware padding and time/month encoding to capture the seasonal patterns (e.g. in app recommendation, outdoor activities apps are more suitable for summer time while indoor activity apps are better for winter). Then the attentive network framework applies time-level attention modules on basket items' sequences and dynamic user attributes' sequences to capture basket items to basket items and attributes to attributes temporal sequential patterns. After that, an intra-basket attentive module is used on items in each basket to capture the correlation information among items.

Abstract: Techniques are disclosed relating to user authentication using multi-party computation and public key cryptography. In some embodiments, a server may receive, from a client, a request to authenticate a user to a service. The server may access key-pair information that includes, for a server key-pair, a first component of a server private key and, for a client key-pair, a client public key and a first component of a client private key. The server may generate a partial signature value that is based on the first component, but not the entirety, of the server private key. The server may send, to the client, an authentication challenge that includes challenge information and the partial signature value. The server may then determine whether to authenticate the user based on an authentication response from the client.

Abstract: A method for sequence-to-sequence prediction using a neural network model includes A method for sequence-to-sequence prediction using a neural network model, generating an encoded representation based on an input sequence using an encoder of the neural network model, predicting a fertility sequence based on the input sequence, generating an output template based on the input sequence and the fertility sequence, and predicting an output sequence based on the encoded representation and the output template using a decoder of the neural network model. The neural network model includes a plurality of model parameters learned according to a machine learning process. Each item of the fertility sequence includes a fertility count associated with a corresponding item of the input sequence.

Abstract: A method for training parameters of a student model includes receiving one or more teacher models trained using sensitive data. Each teacher model includes one or more intermediate layers and a prediction layer coupled to the one or more intermediate layers. The method includes receiving, from the one or more teacher models, one or more intermediate layer outputs and one or more prediction layer outputs respectively based on public data. Student model training is performed to train parameters of the student model based on the intermediate layer outputs and prediction layer outputs of the one or more teacher models.

Abstract: Techniques are disclosed relating to authentication token refresh. In various embodiments, a first of a plurality of instances of an application executing on the server system receives a request to provide content to a browser of a client device. The first application instance determines that an authentication token useable to provide the content has expired. The authentication token is maintained in a storage accessible to the plurality of application instances. The first application instance sends a refresh request for the authentication token to an authentication service. In response to the authentication service denying the refresh request, the first application instance waits for a particular period of time before checking the storage to determine whether another instance of the plurality of instances of the application has refreshed the authentication token.