Abstract: A method including transcribing, automatically, an ongoing stream of voice data into text phrases. The method also includes receiving an indication of a selected text phrase in the text phrases. The method also includes converting the selected text phrase to a selected phrase vector. The method also includes generating a subsequent text phrase, after the selected text phrase, from the ongoing stream of voice data, and adding the subsequent text phrase to the text phrases. The method also includes converting the subsequent text phrase to a subsequent phrase vector. The method also includes generating a similarity confidence score from the selected phrase vector and the subsequent phrase vector, using a machine learning model. The method also includes highlighting, responsive to the similarity confidence score exceeding a threshold value, the subsequent text phrase in the text phrases.

Abstract: A federation link is used to facilitate bi-directional identity federation between software applications. The federation link is created to include user and account identity information for software applications having respective authentication providers. The federation link is created by one of the software applications and shared, for example, with the authentication provider of the other software application. The federation link can be utilized by both software applications to facilitate automated user authentication when navigating in either direction between the software applications.

Abstract: Certain embodiments of the present disclosure provide techniques for performing performance tests against services in a computing environment. The method generally includes deploying application code to an application namespace hosted on a first set of resources in the computing environment. Testing code is deployed to an infrastructure namespace hosted on a second set of resources in the computing environment. A request to test the application code is received. The request generally includes information identifying a load to be generated in testing the application code. A plurality of container instances implementing the test code are instantiated based on the identified load to be generated to test the application code. A test is executed against the application code through the instantiated plurality of container instances.

Abstract: A method extracts explainable corpora embeddings. The method includes constructing a graph with nodes representing terms from a text sequence and edges that include pointwise values generated between pairs of terms. The method further includes generating a rank vector from the graph. Elements of the rank vector correspond to the edges of the graph. A rank value, of the rank values, corresponds to a term from the text sequence. The method further includes selecting the term by comparing the rank vector to a previous rank vector generated for a previous text sequence.

Abstract: A method and system assist users of an electronic bookkeeping system to sort financial transactions into accounts representing bookkeeping categories. The method and system generate vectors representing the accounts and the merchants known to the bookkeeping system. The method and system generate compressed versions of the vectors by compressing the vectors. The method and system assist users to sort the financial transactions by analyzing the compressed vectors.

Abstract: Aspects of the present disclosure provide techniques for detecting sensitive information. Embodiments include determining a first likelihood that a record contains at least a given type of sensitive information using a first detection technique that involves providing one or more inputs to a machine learning model based on the record and receiving the first likelihood as an output from the machine learning model based on the one or more inputs. Embodiments include determining a second likelihood that the record contains at least the given type of sensitive information using a second detection technique comprising a search of the record. Embodiments include applying a policy to determine whether the record contains sensitive information based on the first likelihood and the second likelihood. Embodiments include performing one or more actions based on whether the record contains sensitive information.

Abstract: A plurality of graph snapshots for a plurality of consecutive periodic time samples maps between connected components in consecutive graph snapshots and describes at least one feature of each connected component. A recursively-built tree tracks an evolution of one of the connected components through the plurality of graph snapshots, the tree including a root node representing the connected component at a final one of the consecutive periodic time samples and a plurality of leaf nodes branching from the root node. A plurality of paths is extracted from the tree by traversing the tree from the root node to respective ones of the plurality of leaf nodes. Each path contains data describing an evolution of a respective one of the connected components through time as indicated by evolution of the at least one feature of the respective one of the connected components.

Abstract: A method including receiving a first command including both a data extraction expression and a first report configuration expression. The data extraction expression includes program code for extracting fields of a dataset of a data source. The first report configuration expression includes program code configured to populate cells of first dimensions of a first report and to generate a first tree including subset nodes including records of the dataset. The first command is executed by executing the data extraction expression on the dataset to generate the records. Executing the first command also includes executing the first report configuration expression on the records to generate the first tree. Executing the first command also includes populating, using the first report configuration expression and the first tree, the cells. Executing the first command also includes generating, in response to receiving the first command and by traversing the first tree, the first report.

Abstract: A method converts from compressed language to natural language. The method includes receiving an element string. The element string is in a compressed language format and is extracted from a document in a structured document language. The method includes tokenizing the element string to form multiple element tokens, generating a token set from the element tokens, and generating a name string from multiple token sets. The name string is in a natural language format.

Abstract: A computer-implemented method includes receiving data comprising a plurality of application programming interface (API) requests from a plurality of client devices. The method includes generating a plurality of API sessions based on the data, wherein each of the API sessions is associated with a corresponding client device of the plurality of client devices and includes a sequence of API requests originating from the corresponding client device. The method includes comparing each of the plurality of API sessions to one or more of a plurality of different patterns indicative of permissible API sessions determined based on training data. The method includes determining one or more API sessions of the plurality of API sessions generated based on the data are abnormal based, at least in part, on the comparing. Finally, the method includes performing one or more actions based on determining the one or more API sessions are abnormal.

Abstract: Systems and methods for controlling traffic flow for software experimentation are disclosed. An example method includes receiving a first traffic from a first plurality of users to receive an existing feature or a new feature, determining, from the first traffic, a first portion of the first plurality of users to receive the existing feature (with the first portion bounded by a first lower threshold and/or a first upper threshold) and a second portion of the first plurality of users to receive a new feature (with the second portion bounded by a second lower threshold and/or a second upper threshold). The method also includes providing the existing feature to the first portion, providing the new feature to the second portion, receiving feedback from the first plurality of users, and adjusting the first portion and/or the second portion based on the feedback and based on the bounds.

Abstract: This disclosure relates to restricting access in a social network. The social network stores profile information for each of a plurality of users of the social network in a database. The social network receives, from a first user of the social network, a request to invite a second user to establish a connection with the first user. The social network transmits, to the first user, one or more questions pertaining to the profile information of the second user. The social network receives, from the first user, one or more answers responsive to the one or more questions. The social network determines whether each of the answers is correct based on the stored profile information of the second user. The social network transmits, to the second user, an invitation to establish the connection with the first user when at least a number of the answers are correct.

Abstract: A method implements brand engine for extracting and presenting brand data with user interfaces. The method includes receiving a blueprint with a set of structure blocks extracted from a selected content. A structure block of the set of structure blocks includes a set of style parameter requests for a section of the selected content. The method further includes processing the set of structure blocks with a first set of smart blocks to generate a set of scores. A smart block of the first set of smart blocks includes brand data with style parameter selections. The method further includes selecting a second set of smart blocks, for the set of structure blocks, from the first set of smart blocks, using the set of scores. The method further includes presenting the second set of smart blocks with the brand data.

Abstract: Certain aspects of the present disclosure provide techniques for executing a function in a software application through a conversational user interface based on a knowledge graph associated with the function. An example method generally includes receiving a request to execute a function in a software application through a conversational user interface. A graph definition of the function is retrieved from a knowledge engine. Input is iteratively requested through the conversational user interface for each parameter of the parameters identified in the graph definition of the function based on a traversal of the graph definition of the function. Based on a completeness graph associated with the function, it is determined that the requested inputs corresponding to the parameters identified in the graph definition of the function have been provided through the conversational user interface. The function is executed using the requested inputs as parameters for executing the function.

Abstract: A method scalably authorizes requests. A request to authorize access to a resource is received. A plurality of policies controlling the request is identified. The plurality of policies are concurrently processed. A decision for a policy is received. The decision is of a plurality of decisions corresponding to the plurality of policies. The policy is of the plurality of policies. The decision is determined using a machine learning model and the request. An aggregate decision is generated from the plurality of decisions. A token to access the resource is transmitted in response to the aggregate decision.

Abstract: Aspects of the present disclosure provide techniques for improved text classification. Embodiments include providing, based on a text string, one or more first inputs to a summary model. Embodiments include determining, based on one or more first outputs from the summary model in response to the one or more first inputs, a summarized version of the text string. In some embodiments the summarized version of the text string comprises a number of tokens that is less than or equal to a maximum number of input tokens for a machine learning model. Embodiments include providing, based on the summarized version of the text string, one or more second inputs to the machine learning model. Embodiments include determining one or more attributes of the text string based on one or more second outputs received from the machine learning model in response to the one or more second inputs.

Abstract: Certain aspects of the disclosure provide a method for transferring an achievement token, comprising: receiving a request to transfer an achievement token to a user; querying a smart contract to obtain a requirement associated with the achievement token; verifying, via a blockchain, the user completed the requirement, including retrieving user evidence associated with the requirement from the blockchain; and storing user evidence with a transaction history associated with the transfer of the achievement token to the user; and transferring, via the blockchain, the achievement token to the user.

Abstract: A method optimizes questions to retain engagement. The method includes generating, using a machine learning model, a churn risk from user interaction data. The method includes selecting, when the churn risk satisfies a threshold, a field, from multiple fields, using multiple prediction confidences corresponding to multiple prediction values generated for the multiple fields. The method includes obtaining a prediction value for the field and obtaining a question, corresponding to the field, using the prediction value. The method includes presenting the question and receiving a user input in response to the question.

Abstract: Certain aspects of the present disclosure provide techniques for determining similarities between businesses. One example method generally includes receiving a similarity query and receiving transaction data associated with a plurality of businesses for comparing the plurality of businesses. The method further includes generating a set of vectors representing the plurality of businesses based on the transaction data and generating a set of compact vectors based on the vectors by applying a dimensionality reduction technique. The method further includes generating based on the set of compact vectors, a similarity index and determining a response to the similarity query using the similarity index.