Abstract: The subject matter described herein presents various technical solutions for the technical problems facing autonomous vehicles (e.g., fully autonomous and semi-autonomous vehicles). To address technical problems facing wireless communication cost and latency, a heterogeneous roadside infrastructure can be used to improve the ability for a vehicle to communicate with a data source. To address technical problems facing interruption of vehicle services due to an abrupt loss of connection, a quality of service system provides the ability to determine and share quality of service information, such as location-based information, maps, interference data, and other quality of service information. To address technical problems facing high volume data upload and download between autonomous vehicles and cloud-based data services, optical wireless communication (OWC) provides increased data throughput and reduced complexity, and may be beneficial for short-range high-mobility wireless communications.

Abstract: A system and method to generate search results in response to a search query based on comparisons of embedding vectors. The system and method receive, from an end user system, a search query including a set of keywords associated with the entity. Using a neural network, an embedding vector is identified based on the set of keywords of the search query. The system and method compares the embedding vector associated with the search query to a set of embedding vectors associated with a set of structured data elements relating to the entity. Based on the comparison, a set of matching structured data elements is identified. The system and method generate a search result in response to the search query, wherein the search result includes at least a portion of the set of matching structured data elements. The search result is displayed via an interface of the end user system.

Abstract: A multitenant server application dependency mapping system maps data flows through multitenant infrastructure components through the use of a machine learning model framework that continually learns data flow patterns across the enterprise network and predicts the state of any given server. The multitenant server application dependency mapping system treats the network architecture as a whole and collects data accordingly, and uses that data to compute state probabilities conditioned upon both a point in time (and the observed prior states retrieved from the historical telemetry data. This provides a way to predict the likelihood of observing a tenant state being occupied, while also accounting for variations among the activity levels of various application.

Abstract: A computer based system and method for identifying complaint interactions, including: detecting appearances of linguistic structures related to complaints in an interaction; calculating at least one sentiment metric of the interaction; and classifying the interaction as being or not being a complaint interaction based on the detected linguistic structures and the at least one sentiment metric, for example using a trained supervised learning model.

Abstract: A dialogue complexity assessment method, system, and computer program product including calculating a complexity utilizing domain-dependent terms and domain-independent terms of a dialogue, where the dialogue includes dialogue data from contact centers of service providers.

Abstract: The various embodiments described herein include methods, devices, and systems for relaying messages in a communications system. In one aspect, a method is performed at a server having one or more processors and memory storing instructions for execution by the one or more processors. The method includes: (1) obtaining a plurality of incoming messages; (2) identifying one or more messages from among the plurality of incoming messages, the one or more messages obtained from a first user; (3) receiving a feedback message from a second user about at least one of: the first user and a first message of the one or more messages; and (4) sending the feedback message from the second user to a plurality of users, where the plurality of users track at least one of: the first user and the first message.

Abstract: A contact center server receives an utterance from a customer device as part of a conversation. The contact center server identifies utterance parameters of the utterance, generates a first response to the utterance based on the utterance parameters, and outputs the utterance parameters and the first response to an agent device. The contact center server receives agent-identified-information corresponding to the utterance or agent-modified-information corresponding to the utterance parameters from the agent device. Subsequently, the contact center server generates a second response to the utterance based on the agent-identified-information or the agent-modified-information and outputs the second response to the agent device.

Abstract: An embodiment of the present invention is directed to an intelligent customer service and query management and routing system. The innovative system comprises a communications server that receives a query from a client; a predictive analytics engine that applies predictive analytics to the query including parsing keywords and phrases; classifying the keywords and phrases; and applying a tag to the query; a management platform dashboard that provides an interface to a customer service representative to provide feedback to the predictive analytics engine and further applies automatic routing and categorization into a plurality of communication inboxes; and a periodic model build processing component that builds, monitors, optimizes and deploys one or more predictive models executed by the predictive analytics engine.

Abstract: Data is received that characterizes artefacts associated with each of a plurality of layers of a first machine learning model. Fingerprints are generated corresponding to each of the artefacts in each layer. The generated fingerprints can collectively form a model indicator for the first machine learning model. A second machine learning model then determines, based on the generated fingerprints, whether the first machine learning model is derived from another machine learning model. Data provided this characterization can be provided to a consuming application or process. This second machine learning model can be trained model with historical fingerprints having a known provenance classification. Related apparatus, systems, techniques and articles are also described.

Abstract: A service provider computing system includes memory having stored thereon instructions that, when executed by one or more processors, cause the one or more processors to obtain a first set of complaint logs corresponding to one or more user complaints, each complaint log including a resolution comments field providing a textual representation of a resolution for a corresponding complaint log, parse the resolution comments field of each complaint log of the first set of complaint logs to identify one or more key terms, and execute a machine-learning predictive model using the one or more key terms to generate, for each complaint log, a prediction indicating whether a corresponding complaint should have compensation, the machine-learning predictive model being a supervised machine learning model configured to accept the parsed resolution comments field for the first set of complaint logs as inputs and to output the prediction for each complaint log.

Abstract: A print head assembled to a liquid ejecting apparatus ejecting a liquid with respect to a medium includes an ejecting portion ejecting the liquid in response to a drive signal and an electrically erasable non-volatile memory, and the non-volatile memory stores history information changing in accordance with an operation state of the print head.

Abstract: A method, apparatus, and system of managing digital queues for multiple store locations are disclosed. A method includes receiving, by an enterprise computing system associated with the branch location, a request from a mobile device based on the mobile device navigating to a uniform resource locator (URL) from scanning a code associated with the branch location, in response to the request, causing a graphical user interface (GUI) to display on the mobile device that prompts a user for additional information regarding the request, receiving, from the mobile device via the GUI, the additional information including identity information regarding the user and a reason for the request, identifying a queue specific to the branch location based on the request and additional information, adding the user to the queue, and providing, by the enterprise computing system, a confirmation notification to the user indicating that the user has been added to the queue.

Abstract: A system and method of use to train customer service agents. The training system employs intelligent systems to facilitate or enable the training of customer service agents. The training system provides training to customer service agents and tracks the progress of the customer service trainees. In one aspect, the training system emulates a customer engaging with the customer service trainee, by emulating one or both of the persona of the customer and the scenario of the customer/trainee interaction.

Abstract: A method for encouraging dialogue between, and promoting transparency of said dialogue, a plurality of telecommunicators is provided. The plurality of telecommunicators may include an end user and an agent. The method includes receiving a request for a dialogue from the end user. The request includes a set of end user log-in credentials associated with the end user. The method further includes identifying the agent associated with a set of agent log-in credentials. The agent may respond to the request. The method also distinguishes the end user from the agent based on the set of end user log-in credentials and the set of agent log-in credentials and then instantiates an instance of telecommunications between the end user and the agent based, at least in part, on the distinguishing. Finally, the method includes monitoring the instantiation and displaying to the agent a live customer sentiment score based on a sentiment model.

Abstract: Disclosed are examples relating to managing remote support sessions using devices in communication through a network. In some examples, a request is obtained that includes a selection of an endpoint device for remote support. A sample associated with a remoting capability is obtained from the endpoint device. A remote support server can be selected from among multiple remote support servers based on the sample. Examples of causing the endpoint device to communicate with the remote support server are also disclosed.

Abstract: A system performs operations that include identifying a first subset of accounts from a set of accounts, each account in the first subset of accounts satisfying a first abuse score threshold for a first time period, the first abuse score threshold corresponding to a first buyer abuse component. The operations further include determining a first restriction rate for the first subset of accounts based on a number of accounts in the first subset of accounts that have been restricted for potential abuse. The operations also include comparing the first restriction rate with respective restriction rates of one or more other subsets of the set of accounts that correspond to one or more other abuse components, and based on the comparing, determining whether to adjust the first abuse score threshold.

Abstract: Aspects of the subject disclosure may include, for example, automatically detecting a service issue of a telecommunication system that may impact a customer of a telecommunication service provider of the telecommunication system, predicting, by the processing system, a future customer care interaction by the customer as a result of the service issue, initiating a resolution action of the telecommunication system for the service issue before the customer contacts a customer care agent of the telecommunication service provider, wherein the initiating is responsive to the predicting the future customer care interaction and modifying a component of the telecommunication system to improve efficiency of operation of the telecommunication system by reducing a number of customer care contacts by customers of the telecommunication service provider. Other embodiments are disclosed.

Abstract: Systems and methods are described implementing streaming analytics on a serverless compute system. A user can specify a data stream against which analytics should be conducted, serverless functions to be used to conduct the analysis, and criteria for the analytics, such as windowing criteria and aggregation criteria. The windowing criteria can specify windows of items within the stream that should be collectively analyzed. The aggregation criteria can specify how to group items within each window during analysis. A poller device can read data items from the stream, window and group the items according to the windowing and aggregation criteria, and invoke serverless functions to conduct streaming analytics on the data items. The poller device can further maintain state between invocations.

Abstract: A method for personalizing a delivery of services to a first customer including: providing a customer profile; updating the customer profile via performing a first process to collect interaction data, the first process including the steps of: monitoring activity on the communication device and, therefrom, detecting the first interaction with the first contact center; identifying data relating to the first interaction for collecting as the interaction data; and updating the customer profile to include the interaction data identified from the first interaction; generating an interaction predictor, the interaction predictor comprising knowledge about the first customer derived, at least in part, from the data stored within the customer profile, the knowledge comprising a behavioral factor attributable to the first customer given a first type of interaction; and augmenting the customer profile by storing therein the interaction predictor.

Abstract: A method for encouraging dialogue between, and promoting transparency of said dialogue, a plurality of telecommunicators is provided. The plurality of telecommunicators may include an end user and an agent. The method includes receiving a request for a dialogue from the end user. The request includes a set of end user log-in credentials associated with the end user. The method further includes identifying the agent associated with a set of agent log-in credentials. The agent may respond to the request. The method also distinguishes the end user from the agent based on the set of end user log-in credentials and the set of agent log-in credentials and then instantiates an instance of telecommunications between the end user and the agent based, at least in part, on the distinguishing. Finally, the method includes monitoring the instantiation.

Abstract: A noise reduction and smart ticketing application for social media-based communication systems may identify social media-based communications from users who are attempting to engage with a brand or entity on a social media platform as actionable, and distinguish other communications as noise. The noise reduction and smart ticketing system may use machine learning to determine which social media communications are actionable for a given company or other organization, and generates tickets for actionable communications. Actionable communications may include, but are not limited to, technical support issues, inquiries about a product release date, grievances, incidents, suggestions to improve service, critiques of company policies, etc. Non-actionable communications (i.e., “noise”) may include, but are not limited to, suggestions to other users, promotions, coupons, offers, marketing campaigns, affiliate marketing, statements that a user is attending an event, etc.

Abstract: An example printing device may comprise an indicator to convey information to a user, a print substance reservoir to house a print substance, where the print substance reservoir is communicatively coupled to a fill port, a sensor to determine when a refill container is connected to the fill port, a processing resource, and a non-transitory machine-readable medium storing instructions executable by the processing resource to transmit signals to the indicator responsive to an indication that the sensor has detected the refill container connected to the fill port, where the signals correspond to the information to be conveyed by the indicator, and authenticate the refill container.

Abstract: A system and method for detecting duplicate tickets submitted to a ticket tracking or issue tracking system. A trained machine learning model can be leveraged to compare tokens representing ticket pairs and/or to determine whether two or more tickets are duplicate tickets, despite that content of those tickets may not be identical.

Abstract: A method and system for identifying and labeling fraudulent store return activities includes receiving, by a server, retailer events from an online transaction system of a retailer, the retailer events comprising records of transactions between customers and the retailer, including sale, exchange and return activities across multiple stores. The retailer events are processed to build a network that associates stores, transactions, payment instruments, and customer identification over related activity sequences of transactions.

Abstract: A management system operates in conjunction with an automotive dealership to improve customer engagement with the automotive dealership. The management system creates customer profiles of the automotive dealership systems' customers using features of the customers obtained via various sources. The management system assigns a customer category to a customer based on the features included in the customer profile and may generate a customized recommendation of a product and/or service for the customer to purchase at the dealership based at least in part on the customer category.

Abstract: One example method of operation may include identifying a call scheduled for a scheduled time having a calling party profile and a called party profile, identifying one or more calling party flags associated with the calling party profile and one or more called party flags associated with the called party profile, establishing a call connection between a calling party device and a called party device at the scheduled time to conduct the call, recording call content identified during the call, processing the call content of the recorded call to identify call content compliance based on the calling party flags and the called party flags, scoring the call based on the identified call content compliance, and updating one or more of the called party profile and the calling party profile to identify the scored call.

Abstract: Devices and methods for client application user experience tracking may include generating a user experience score based on tracked operation and user inputs to the client application. The user experience score is transmitted to an experience tracking service (e.g., remote computer server, locally executed application).

Abstract: The embodiments of the present disclosure provide systems and methods for call deflection, comprising receiving, via a telephone communication from a mobile device of a user, a request for return or exchange, accessing a purchase history of the user to identify at least one order satisfying a predetermined return criteria, generating a unique hyperlink for the user, sending the unique hyperlink to the mobile device of the user, receiving, from the mobile device of the user, a selection of at least one product in the at least one order for return or exchange, and modifying a database to register the at least one product for return or exchange. The unique hyperlink may be assigned to the at least one order that satisfies the predetermined return criteria such that, when activated by the user, the mobile device is configured to display the at least one order.

Abstract: A method, system and computer-usable medium are disclosed for machine learning to identify service request records associated with an account that is likely to escalate. Certain aspects of the disclosure include generating a random forest model using a training set of service request records to determine a probability of escalation for service requests of the training set; applying the random forest model to a current set of service request records to determine an escalation probability for service requests in the current set; and assigning service request records in the current set to a plurality of escalation probability bins, wherein the service request records of the current set are generally equally divided between the plurality of escalation probability bins, and wherein the service request records of the current set are assigned to a probability bin based on the escalation probability of the service request record.

Abstract: A platform can receive information regarding a user interaction, wherein the user interaction is associated with one or more channels that correspond to respective interfaces or media for the user interaction; retrieve supplemental information associated with the user interaction, wherein the supplemental information relates to at least one of: a state of a managed device associated with the user interaction, or a previous user interaction; identify, based on the information regarding the user interaction or the one or more channels, one or more models to process the information regarding the user interaction and the supplemental information, wherein the one or more models are identified from a plurality of models; determine, using the one or more models, an action to be performed with regard to the user interaction; and provide information identifying the action.

Abstract: Systems and methods for using a mathematical model based on historical information to automatically schedule and monitor work flows are disclosed. Prediction methods that use some variables to predict unknown or future values of other variables may assist in reducing manual intervention when addressing incident reports or other task-based work items. For example, work items that are expected to conform to a supervised model built from historical customer information. Given a collection of records in a training set, each record contains a set of attributes with one of the attributes being the class. If a model can be found for the class attribute as a function of the values of the other attributes, then previously unseen records may be assigned a class as accurately as possible based on the model. A test data set is used to determine model accuracy prior to allowing general use of the model.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for an automated chat bot conversation session and an agent transfer system for the conversation session. The computer receives a user input from a user in an automated chat bot conversation session. The computer analyzes the user input for at least one sentiment, wherein an at least one analysis result is a value assigned to the at least one sentiment contained within the user input. The computer compares the at least one analysis result to a threshold value to determine if the user should be transferred from the automated chat bot conversation session to a conversation session with a suitable agent. The computer then transfers the user to the conversation session with the suitable agent.

Abstract: Systems and methods for returning an item. The methods comprise: performing item return operations by a computing device using at least one of machine learned information about a person who purchased the item, machine learned information about a person returning the item, and machined learned information about a condition of the item at the time of sale and at the time of return; and automatively sorting the item using a conveyer system to move the item from a counter to a respective storage area of a plurality of storage areas assigned to different product types.

Abstract: Embodiments recognize and solve problems as a function of biometric and social network data, wherein processors are configured to determine that an e-commerce site user is currently experiencing a problem in association with a purchase of an item on the e-commerce site as a function of analyzing biometric data acquired from the user in association with the item purchase. The processors are further configured to correlate the first problem associated with the item purchase to an alternative problem that is associated with the item purchase as a function of social network data of the user; and to suggest the alternative problem to the user as another problem experienced by the user in association with the item purchase.

Abstract: To provide context-specific interpretation of a user interaction with a user interface of a computer application, a processor may detect a user interaction with a user interface (UI). The processor may analyze the user interaction to determine a plurality of action details. The processor may generate a user context based on the plurality of action details and additional context information. The processor may select at least one operation relevant to the user interaction and context. The processor may cause the computer application to perform the operation.

Abstract: A method and associated system for generating a service specification of a solution. Each process of at least one process is decomposed into at least one atomic service process. The service specification of the solution to be compatible with both a process model framework that includes the at least one process and a data model framework that includes at least one data element that is indirectly matched to the at least one process. The service specification represents a respective process interface of each atomic service process that performs a respective atomic service in the solution. The customized service specification is stored in a database.

Abstract: Techniques for managing service requests in cloud computing systems are disclosed herein. In one embodiment, a method can include in response to determining that a profile of detected service requests substantially deviates from the predetermined profile, identifying a component failure of a service component in the cloud computing system by searching a database containing operational event logs of the cloud computing system based on the detected service requests. The method can then include posting, on a user portal of the cloud computing system, a notification to additional users regarding the identified component failure of the service component and performing various remedial actions to correct the identified component failure.

Abstract: Systems, methods, and non-transitory computer readable media configured to acquire data associated with a content item, the data associated with the content item including contextual information. The data associated with the content item can be provided to a model trained by machine learning. A set of hashtags associated with the content item can be determined based on the model.

Abstract: Computer program products, methods, systems, apparatus, and computing entities are provided for customer controlled management of shipments. For example, customers can define handling identifiers to determine how items should be handled based on the handling identifier. Further, customers can define refund classifications to determine when refunds should be initiated.

Abstract: Recommending actions to an Information Technology (IT) case can include searching an index for an IT case that matches a received IT case, identifying a plurality of actions for the received IT case based on the search, and recommending a subset of actions from the plurality of actions for the received IT case to an IT agent.

Abstract: A vehicle service facility may include an RFID transmitter-receiver. The RFID transmitter-receiver may include at least one RFID antenna. The RFID transmitter-receiver may further include an RFID reader. The vehicle service facility may also include a computer system, the computer system having a programmable processor such as a microprocessor or a microcontroller and processor-readable or computer-readable programming code embodying logic embedded on tangible, non-transitory computer readable media. The computer system is in data communication with the RFID reader.

Abstract: A design support system includes a storage unit, an accepting unit, a selecting unit, and an associating unit. The storage unit stores information regarding design element classifications into which design elements constituting a product are classified and design requirement classifications into which design requirements required for the product are classified. The accepting unit accepts technical information regarding a trouble due to design. The selecting unit refers to the technical information regarding the trouble, selects a classification item to which the trouble belongs from among the design requirement classifications, and selects a classification item to which a design element that has caused the trouble belongs from among the design element classifications.

Abstract: A system receives data relating to a ticket from a customer of a business organization. The system processes the data using an ensemble machine learning artificial intelligence processor. The ensemble machine learning artificial intelligence processor includes a natural text language processor for analyzing text exchanged between the customer and an agent of the business organization. The ensemble machine artificial intelligence processor also includes a plurality of multivariate machine learning processors for analyzing a handling of the ticket by the business organization. The system generates results from the analysis of the natural language text processor and the analyses of the plurality of multivariate machine learning processors, and provides the results to a meta-learner processor.

Abstract: A universal data gate converts between interface format types of interconnected systems. The data gate learns new interface types and greatly simplifies the requirement for a human user to reprogram the new interface types. A library of known interface types is built up over time and allows re-use of known interface types as required. Voice based room control is enabled by automatically activating the voice control on a guest device when the guest is checked in to a hotel room. Text corresponding to voice commands captured from the user's voice is passed to a hotel app. The system automatically pairs the guest device with the user's assigned room and determines which in-room controllable devices are to be operated by the user's voice commands. When the user switches to a new guest room during travel, the system automatically updates the room pairing and new voice commands operate the new in-room devices.

Abstract: A content replacement system identifies regular content replacement parts and alternative content replacement parts, each alternative content replacement part being a content item with a duration within one of a plurality of ranges. The system detects a start of a content replacement break in a listener content stream, the listener content stream shifted by a listener delay value from a live content stream. The system inserts the regular content replacement parts into the stream. The system detects an end of the content replacement break for the listener content stream, and selects one of the alternative content replacement parts to insert into the listener content stream, the selected alternative content replacement part having a duration that when inserted into the listener content stream minimizes a difference between the listener delay value and a target delay value.

Abstract: In a computer server, a ticket element generated by an issue tracking system responsive to a client request is received, where the ticket element includes a data field including data indicative of an attribute. A database including state data stored therein is accessed responsive to receipt of the ticket element. The state data relates a plurality of states that are specific to the attribute. One of the plurality of states related by the state data is identified as corresponding to a future state of the attribute based on a current state of the attribute, and a future probability of escalation of the ticket element is computed based on the future state of the attribute responsive to identification of the one of the plurality of states as corresponding thereto. An action indicator is provided in response to the client request.

Abstract: A journal manager of a multi-data-store storage appends a committed transaction entry to a journal, indicating a state change which has been approved for commit using an optimistic concurrency control algorithm. A first representation of the state change is generated and stored at one materialization node. A different representation of the same state change, comprising at least one attribute for which a value is not included in the first representation, is generated and stored at a different materialization node.

Abstract: Systems and methods for customer relationship management are disclosed. In one example, a customer relationship management system can receive, from a customer device, a customer location and a request for a sales representative. In response, the customer relationship management system can send, for display to a sales representative device, the customer location and then receive, from the sales representative device, a request for customer profile information. In response to this request, the customer relationship management system can send, for display to the sales representative device, at least some of the customer profile information.

Abstract: Managing confidence data in a question-answering environment is disclosed. Managing confidence data can include sorting, based on a set of answer categories for a subject matter, a first set of a plurality of answers into a first answer category. The first set can correspond to at least one of a third set of a plurality of confidence scores and the second set can correspond to at least one of a fourth set of the plurality of confidence scores. Managing confidence data can include classifying confidence scores of the third set into one of a plurality of confidence buckets using a first threshold and determining a fifth set of a plurality of thresholds using the plurality of confidence scores. Managing confidence data can include classifying unclassified confidence scores of the third set into one of the plurality of confidence buckets using the fifth set of the plurality of thresholds.

Abstract: A system and method for providing delegated metric tools within a partially closed communication platform that includes receiving a tag identifier linked to at least a first identified platform interaction in the communication platform; associating the tag identifier with at least one logged event of an account associated with the first identified platform interaction; defining a tracking resource with at least one tag identifier; measuring platform interactions tracked by a tracking resource; and providing access to measured platform interactions through an application.