Abstract: Computerized systems and methods for identifying a table in a document include: removing from a document content other than text characters and associated size, position and format information; converting each text character into a block covering the corresponding text character; converting each page of the document into a corresponding image file; drawing a set of horizontal lines spanning a width of the document, each block super-scored and under-scored by at least one of the horizontal lines; drawing a set of vertical lines spanning all or a portion of a length of the document; removing a subset of redundant vertical lines; and determining, based on the set of horizontal lines and the subset of vertical lines, (i) a set of table coordinates corresponding to a table in the document, and (ii) one or more sets of cell coordinates corresponding to one or more cells in the table.

Abstract: A computerized method of assessing a chatbot conversation includes: extracting one or more messages from the conversation; determining, based on the one or more messages, an existing business opportunity value score using a business opportunity state detector module; determining, based on the one or more messages, an existing user experience score using a user experience state detector module of the computing device; determining, based on the one or more messages, a future business opportunity value score using a future business opportunity predictor module of the computing device; determining, based on the one or more messages, a future user experience score using the future user experience predictor module of the computing device; calculating a composite score indicating whether human intervention in the chatbot conversation is desirable; and generating a display signal including a status indicator, for review by a human agent, reflecting a desirability of human intervention in the chatbot conversation.

Abstract: A computing device having a software radio (e.g., a mobile device where the software radio is substantially defined in software) transmits first information related to a financial transaction over the first radio network to the financial institution, and transmits second information related to the financial transaction over the second radio network to the financial institution. A server of the financial institution receives the first information and the second information to carry out the financial transaction.

Abstract: The Seed Splitting and Firmware Extension for Secure Cryptocurrency Key Backup, Restore, and Transaction Signing Platform Apparatuses, Methods and Systems (“SFTSP”) transforms transaction signing request, key backup request, key recovery request inputs via SFTSP components into transaction signing response, key backup response, key recovery response outputs. An offline transaction signing request message for a transaction is received by a first cold HSM and includes an encrypted second master key share from a second cold HSM and an encrypted third master key share from a hot HSM. A first master key share is retrieved. The encrypted master key shares are decrypted and, along with the first master key share, used to recover a master private key. A keychain path is determined. A signing private key for the keychain path is generated using the master private key. The transaction is signed using the signing private key, and the generated signature is returned.

Abstract: Methods and apparatuses are described for generating a recommended conversation topic flow. A server executes a topic modelling algorithm on voice call transcripts to determine a distribution of topics present in the transcripts. The server generates a historical topic flow for each transcript by determining topic-related words in text blocks in the transcript and assigning a score to each text block. The server categorizes each topic flow as positive or negative based upon outcomes associated with the transcript. The server trains a classification model using the categorized topic flows as input. The server captures a bitstream corresponding to a current voice call and converts the bitstream into unstructured text. The server executes the classification model on the unstructured text to determine whether a call topic flow is positive or negative. The server generates topic recommendations and transmits the recommendations to a second client device.

Abstract: Methods and apparatuses are described for automatic classification of error conditions in automated user interface testing. A server receives an image file corresponding to a current user interface (UI) view of a software application under test. The server analyzes the image file to identify error conditions that exist in the current UI view. The server assigns a classification to the image file according to one or more error types based upon the error conditions identified in the current UI view. The server transmits a notification message to one or more remote computing devices, the notification message comprising the image file and the classification assigned to the image file.

Abstract: Methods and apparatuses are described for enterprise access control governance in a computerized information technology (IT) architecture. A server generates a first vector space, each node in the first space representing a user of resources in the IT architecture and including attributes of the user. The server generates a second vector space, each node in the second space representing an entitlement to access resources in the IT architecture and including attributes of the entitlement. The server creates an entitlement utility matrix by mapping nodes in the first space to nodes in the second space. The server determines a set of recommended entitlements for a plurality of users based upon the utility matrix. The server determines a discrepancy between the set of recommended entitlements for a first user and a set of existing entitlements for the first user and adjusts the set of existing entitlements based upon the discrepancy.

Abstract: Methods and apparatuses are described for generating and manipulating 3D objects in a 3D environment of an alternative reality software application. A server retrieves a data set comprising data elements, each having one or more attributes. The server generates, for each data element, a virtual object, each virtual object positioned inside a virtual container and located in proximity to a center of the virtual container. The server attaches virtual magnets to an exterior surface of the virtual container, each magnet associated with a data filter value and an attraction value. The server determines, for each virtual object, a movement distance and a movement speed in relation to each virtual magnet based upon the data filter value and the attraction value for the virtual magnet. The server moves at least a portion of the virtual objects to a new location based upon the movement distance and movement speed.

Abstract: Methods and apparatuses are described for generating and displaying custom-selected content for a mobile application. A mobile device captures a request to launch an application and determines content cards eligible to be displayed. A user-specific content classification model is generated for selecting one of the content cards to be displayed, where the mobile device identifies historical usage characteristics and transmits the historical usage characteristics to a server, which generates the user-specific content classification model based upon the historical usage characteristics and transmits the user-specific content classification model to the mobile device. The mobile device executes the user-specific content classification model to select one or more content cards to be displayed and launches the application to display the selected content cards.

Abstract: A computer-implemented method is provided for automatically masking data for display in a mobile computing device. The computer-implemented method includes receiving a request to display data on the mobile computing device and detecting a physical location of the mobile computing device, a time corresponding to the request, and at least one network characteristic of a wireless network on which the mobile computing device is making the request. The method also includes automatically determining whether to mask the data for display in the mobile computing device based on the physical location, the time, and the at least one network characteristic. The method further includes responsive to determining to mask the data, applying one or more masking rules to the data.

Abstract: Methods and apparatuses are described for automated predictive product recommendations using reinforcement learning. A server captures historical activity data associated with a plurality of users. The server generates a context vector for each user, the context vector comprising a multidimensional array corresponding to historical activity data. The server transforms each context vector into a context embedding. The server assigns each context embedding to an embedding cluster. The server determines, for each context embedding, (i) an overall likelihood of successful attempt and (ii) an incremental likelihood of success associated products available for recommendation. The server calculates, for each context embedding, an incremental income value associated with each of the likelihoods of success. The server aggregates (i) the overall likelihood of successful attempt, (ii) the likelihoods of success, and (iii) the incremental income values into a recommendation matrix.

Abstract: Methods and apparatuses are described for identification and traceability of application programming interface (API) functionality in a distributed computing environment. A server retrieves source code comprising API calls from source code repositories, and parses the source code to identify a first set of APIs, each having one or more attributes. The server retrieves API definitions and parses the API definitions to identify a second set of APIs, each having one or more attributes. The server compares the first set of APIs and the second set of APIs to determine matching APIs. Using the matching APIs, the server detects backend systems associated with each API and generates a call graph for each API by traversing abstract syntax trees (ASTs) associated with the source code. The server builds an API model object for each API, comprising the attributes of the API, the detected backend systems, and the call graph.

Abstract: A computerized method is provided for automatically identifying a set of historical issues derived from historical customer interactions with an enterprise. The method includes collecting text-based data corresponding to the historical customer interactions, extracting customer queries from the text-based data, and normalizing and filtering the customer queries to generate the set of historical issues of the customer queries. The method also includes assigning the historical issues to one or more clusters that capture variances among the historical issues. The method further includes generating a legitimacy score for each historical issue and ranking the set of historical issues in accordance with their corresponding legitimacy scores. The method can further include identifying one or more issues in a transcript of unstructured text using the set of historical issues.

Abstract: The Application Source Code Reuse Apparatuses, Methods and Systems (“ACR”) transforms compilation request inputs via ACR components into compilation response outputs. A compilation request datastructure that specifies an application identifier is obtained. A first source code branch associated with the application identifier is pulled from a source code repository. A second source code branch associated with the application identifier is rebased using the first source code branch. A first transformation file in the second source code branch is selected. The first transformation file is written in a first programming language and includes a first set of annotations that specify how to modify the first transformation file into a compilable file in the first programming language. The first transformation file is transformed, in accordance with the first set of annotations, into a compilable file in the first programming language. A content package is generated using the transformed first transformation file.

Abstract: A computer-implemented method is described for authenticating the identity of a caller. A mobile computing device receives, via a wireless communications network, an incoming call setup request initiated by a phone system of a caller, and executes an identity service application upon receipt of the incoming call setup request. The call includes a plurality of data packets. The mobile computing device extracts a caller identifier from the plurality of data packets. The caller identifier includes one or more bits at a first predetermined position within the plurality of data packets. The mobile computing device forwards the caller identifier to an identity service computing device. The identity service computing device determines an identity status of the caller. The mobile computing device receives, from the identity service computing device, an authentication token and the identity status of the caller. The mobile computing device displays the identity status of the caller.

Abstract: Methods and apparatuses are described for enforcing referential integrity of database columns across a plurality of tables in a database. A server periodically captures a database schema comprising relationships between a primary key column in a first table and a foreign key column in a second table. The server executes a first procedure call to determine a discrepancy between the primary key column and the foreign key column with respect to a data length value or a data type value. The server executes database queries against data in the first table or second table to confirm the discrepancy. The server executes a second procedure call to change the data length value or the data type value. After the second procedure call finishes, the data length value and the data type value of the primary key column and the foreign key column match.

Abstract: Methods and systems are described for generating integrated intelligent content overlays for media content streams. A server computing device receives a video content stream from a video data source. The server extracts a corpus of machine-recognizable text from the video content stream, the corpus of machine-recognizable text corresponding to at least one of audio or closed captioning text associated with the video content stream. The server identifies one or more entity names contained in the corpus of machine-recognizable text. The server determines a set of content keywords associated with each of the identified entity names. The server generates a content overlay for the video content stream comprising one or more layers that include graphical content relating to at least one of the sets of content keywords. The server integrates the content overlay into the video content stream to generate a customized video content stream.

Abstract: Systems and methods for predicting computing system issues include: receiving a set of incident management tickets for a set of computing system issues and a set of computer log files for multiple modules of the computing system; arranging the set of tickets into chronologically ordered groups associated with particular computing system issues; pre-processing the set of computer log files to remove specified information, append to each log entry an indicator of the module of the log file, and merge the log entries; determining for each group a set of patterns for the group's associated computing system issue before the group's associated computing system issue arises; calculating for each pattern in each group a similarity score; selecting a subset of patterns whose similarity scores exceed a specified threshold; and generating a computing model associating the subset of patterns in each group with the group's associated computing system issue.

Abstract: A computerized method of populating one or more structured databases includes performing, by a computing device, the steps of: receiving customer message data from one or more data sources; extracting, from the customer message data, data sets representative of a set of customer questions; pre-processing, the data sets representative of the set of customer questions using one or more filters, thereby producing pre-processed data sets representative of customer questions; extracting, from the pre-processed data sets representative of customer questions, a set of customer expression data sets; grouping, the customer expression data sets into a set of clusters, each cluster representing one customer intent data set, each customer intent data set corresponding to one or more customer expression data sets; and storing, the customer intent data sets and the customer expression data sets in the structured database(s), the structured database(s) in electronic communication with the computing device.