Abstract: Methods and apparatuses are described for automated execution of computer software based upon determined empathy of a communication participant. A server captures a digitized voice segment from a remote computing device. The server analyzes vocal cues of the digitized voice segment to generate a voice empathy score. The server converts speech in the digitized voice segment into text and determines empathy keywords in the text to generate a keyword empathy score. The server captures digitized images of the participant's face and analyzes physical expressions of the face to identify emotions and generate a facial empathy score. The server generates an overall empathy confidence score for the communication participant based upon the voice empathy score, the keyword empathy score, and the facial empathy score. The server generates recommended changes for the user based upon the overall empathy confidence score and executes a software application that displays the recommended changes.

Abstract: A computerized method of testing a mobile application stored on a mobile test device includes executing, by a computing device, a test script stored in memory of the computing device; running, by the computing device, according to the test script, a human behavior simulation module; retrieving, by the computing device, an event list stored in a server, the event list including one or more electronic human behavior simulations; receiving, by the computing device an electronic human behavior simulation from the event list; providing, by the computing device, selected data of the electronic human behavior simulation to memory of the server for recordation; executing, by the computing device, the electronic human behavior simulation on a mobile test device in electronic communication with the computing device; and executing, by the computing device, according to the test script, a test case stored in memory of the computing device on the mobile test device.

Abstract: Methods and apparatuses are described for automated secure software development management, risk assessment and risk remediation. A server generates security requirements for a software application under development based upon a plurality of technical attributes and a threat model. The server creates a first set of development tasks based upon the generated security requirements. The server scans source code to identify one or more security vulnerabilities and creates a second set of development tasks based upon the identified vulnerabilities. The server generates a security risk score based upon the generated security requirements and the identified vulnerabilities. The server deploys the software application under development to a production computing system upon determining that the security risk score satisfies a criterion.

Abstract: Methods and apparatuses are described for time-series database user authentication and access control. A server computing device receives a request from a remote computing device to access a time-series database coupled to the server computing device, wherein the request includes one or more authentication credentials associated with the remote computing device. The server computing device validates the one or more authentication credentials associated with the remote computing device. The server computing device connects to an access control layer associated with the time-series database. The access control layer authorizes the remote computing device to access data in the time-series database based upon an access profile associated with the validated authentication credentials. The server computing device retrieves data from the time-series database in response to the request.

Abstract: Methods and apparatuses are described for automated analysis, categorization, and behavior prediction of computer scripts using rules-based pattern matching. A server receives from a client device, a request for analysis of a process flow decision. The server identifies computer scripts that execute to generate the process flow decision. For each identified computer script: the server identifies text patterns in the computer script and categorizes the computer script based upon the identified patterns; the server converts the computer script into an expression tree data structure; the server traverses the expression tree to determine logical expressions that return a true result; the server parses each logical expression that returns a true result to identify parameters that contribute to the true result; the server generates a response to the request for analysis of the process flow decision and transmits the response to the request to the client computing device.

Abstract: Methods and apparatuses are described for automatic authentication switching in online chat sessions. A server receives a request to establish an online chat session from a first client device, including authentication credentials associated with the first client device. The server establishes an online chat session between the first client device and a second client device via a first authenticated communications channel. The server transmits one or more chat messages between the first client device and the second client device using the first authenticated communications channel. The first client device determines that the online chat session has lost authentication. The first client device automatically switches the online chat session to a second unauthenticated communications channel. The server maintains the established online chat session between the first client device and the second client device via the second unauthenticated communications channel.

Abstract: Methods and apparatuses are described for detecting vulnerabilities associated with a software application build. A server generates a software application build based upon a source code repository, including determining application dependencies of the software application build. The server identifies vulnerabilities associated with the application dependencies. For each identified vulnerability, the server creates an aspect class based upon a package file associated with the vulnerability, the aspect class comprising vulnerability logging code. The server integrates the created aspect classes into libraries of the application dependencies, generates a new package file based upon the application dependencies, and integrates the new package file into the software application build. The server executes the software application build, including generating log statements by calling the aspect classes in the new package file.

Abstract: Methods and apparatuses are described for analyzing unstructured computer text for identification and classification of complaint-specific interactions. A computer data stores unstructured text. A server computing device splits the unstructured text into phrases of words. The server generates a set of tokens from each phrase and removes tokens that are stopwords. The server generates a normalized sentiment score for each set of tokens. The server uses a rules-based classification engine to generate a rules-based complaint score for each set of tokens. The server uses an artificial intelligence machine learning model to generate a model-based complaint score for each set of tokens. The server determines determine whether each set of tokens corresponds to a complaint-specific interaction based upon the rules-based complaint score and the model-based complaint score.

Abstract: Methods and apparatuses are described for automated computer text classification and routing using artificial intelligence transfer learning. A server trains a word embedding model using one-hot vectors of word pairs from a filtered first corpus of unstructured computer text and a filtered second corpus of unstructured computer text, using an artificial intelligence neural network. The server trains a long short-term memory model using vector matrices that correspond to sentences in the filtered second corpus of unstructured computer text, and labels. The server receives a message, generates a matrix for each sentence in the message by applying the trained word embedding model, generates one or more labels, and a probability for each label, for each sentence in the message by applying the trained long short-term memory model, and routes the message to a second client computing device based upon an assigned label.

Abstract: A computer-implemented method of training, using a computer log file, an application error prediction engine to identify one or more application errors includes parsing the computer log file into a plurality of data sets. Each data set is associated with a unique computing session having a session identifier and ending in an application or. The method also includes extracting, from each data set, values for a specified set of parameters in each data set. The method also includes encoding the extracted values for each data set into a corresponding data structure. The method also includes generating, for each data structure, a corresponding vector, the corresponding vectors collectively forming a matrix. The method also includes calculating, based on the matrix, a set of clusters, each cluster corresponding to a known error type, the set of clusters used to create a model used to identify new error types.

Abstract: A computerized method of authenticating a user includes receiving, by a computing device, first biometric data from the user via a first biometric input device; extracting one or more first features from the first biometric data; generating a first vector based on the first features; computing a first similarity score reflecting a geometric distance between the first vector and a first reference vector stored in memory; receiving second biometric data from the user via a second biometric input device; extracting one or more second features from the second biometric data; generating a second vector based on the second features; computing a second similarity score reflecting a geometric distance between the second vector and a second reference vector stored in memory; computing a confidence score based on the first and second similarity scores; and determining a right of the user to access restricted information based on the confidence score.

Abstract: The 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. A key backup request that includes an encrypted master key associated with a hosting HSM is received by a backup HSM from a backup utility. A private key decryption key corresponding to a public key encryption key previously provided by the backup HSM to the backup utility for the hosting HSM is retrieved from the backup HSM's tamper-proof storage and used to decrypt the encrypted master key. A specified number of master key shares to generate for the decrypted master key is determined and generated using a secret sharing method. The generated master key shares are provided to the backup utility.

Abstract: Described herein are methods and systems for secure communication of private audio data in a zero user interface computing environment. A server receives text generated from a first digital audio bitstream, the digital audio bitstream corresponding to speech captured by a zero user interface computing device from a user. The server analyzes the text to extract a set of keywords from the text. The server determines whether information responsive to the keywords comprises private data related to the user. If the information responsive to the set of keywords comprises private data: the server generates a text response to the set of keywords that includes the private data relating to the user, determines a personal audio playback device associated with the user, and transmits the generated text response to the personal audio playback device for playback as a second digital audio bitstream.

Abstract: Methods and apparatuses are described for analyzing unstructured computer text for domain-specific stopword identification and removal. A computer data store stores unstructured text. A server computing device splits the unstructured text into phrases and generates tokens from the phrases. The server computing device generates a set of bootstrap keywords using the tokens. An artificial intelligence neural network executing on the server computing device generates a stopword training model. The server computing device generates a first set of candidate stopwords using the bootstrap keywords and the stopword training model. The server computing device generates regular expressions using the bootstrap keywords, and generates a second set of candidate stopwords using the regular expressions. The server computing device stores the candidate stopwords in the data store, and removes stopwords from the unstructured text using the data store.

Abstract: A method of processing data by one or more data processing systems for classification of the processed data into one or more predefined classifications, the method comprising: receiving by one or more data processing systems social profile data; binding by the one or more data processing systems based on the input social profile data, values of one or more attributes included in the social profile data to one or more parameters of a classifier executing on the one or more data processing systems; classifying data representing the user into one or more predefined classifications; for one of the predefined classifications into which the data representing the user is classified, identifying by the one or more data processing systems a candidate action included in the predefined classification and unassociated with the user; and transmitting an alert to notify the user of the candidate action.

Abstract: Methods and apparatuses are described for generating and deploying customized application software containers. Software containers on a first server comprise an application software module and an end-user-specific data set. A second server receives input data from remote computing devices and stores the input data in a master data set. The second server determines end-user-specific data sets from the master data set. The second server encrypts each of the end-user-specific data sets with an encryption key. The second server generates the software containers by executing the application software module in separate processes and storing each of the encrypted data sets in a separate container. Client computing devices authenticate to the second server to access a software container. The client devices decrypt the end-user-specific data set stored in the software container using the encryption key, and use the application software module to interact with the end-user-specific data set.

Abstract: A computerized method of comparing documents includes a computing device: receiving a source document via a first automated document feed channel; receiving a target document via a second automated document feed channel; pre-processing the source document using a first comparison data structure operating on the computing device, thereby producing a pre-processed source document having a text array including text from the source document; pre-processing the target document using a second comparison data structure, thereby producing a pre-processed target document having a text array including text from the target document; determining, using a document comparison engine operating on the computing device, a set of differences between the pre-processed source document and the pre-processed target document with respect to a set of pre-specified criteria; and generating, a summary of the set of differences between the pre-processed source document and the pre-processed target document.

Abstract: A computer-implemented method is provided for authenticating an identity of a user requesting access to a computerized resource via a client computing device. The method includes receiving, by the client computing device, a request to authenticate the identity of the user, determining, by the client computing device, a time period of the request, determining, by the client computing device, an approximate geolocation of the user, and determining, by the client computing device, one or more network characteristics associated with a current network of the client computing device. The method further includes transmitting, by the client computing device to an authentication device, authentication data including the request, the time period of the request, the approximate geolocation of the user and the one or network characteristics.

Abstract: The SECTOR-BASED PORTFOLIO CONSTRUCTION PLATFORM APPARATUSES, METHODS AND SYSTEMS (“SPC”) transform user data request via SPC components into sector-based portfolio investment transaction records. In one implementation, the SPC may provide an electronic user interface (UI) (e.g., web-based, mobile, etc.) for a user to construct a sector-based investment portfolio, to obtain performance prediction for the portfolio's allocation strategies by performance back-testing of selected sector funds and indices.

Abstract: Methods and apparatuses are described for dynamic generation of custom web analytics data. A computing device renders a webpage comprising a plurality of page elements, where the webpage is assigned one or more attributes and each page element is assigned one or more attributes. The computing device detects one or more interactions occurring with one or more of the plurality of page elements on the webpage. For each detected interaction, the computing device identify the page element with which the detected interaction occurred, captures at least one of the one or more attributes of the webpage, captures at least one of the one or more attributes of the identified page element, aggregates the captured attributes of the webpage and the captured attributes of the identified page element into a custom variable, and stores the custom variable in a local memory module of the computing device.