Abstract: A method and a modification system for modifying a search query for a user are provided. The method includes receiving at least one search query from a user; determining a present context of the user, based on the at least one search query and on-device data; identifying at least one relevant attribute related to the search query based on the present context of the user and a personalized knowledge graph, wherein the personalized knowledge graph is dynamically generated based on the on-device data; and modifying the search query, based on the at least one relevant attribute and a relation of the at least one relevant attribute with the search query, to obtain at least one modified search query.

Abstract: A method may include obtaining a graph dataset that includes a plurality of nodes. The method may include specifying two or more clusters into which each node of the plurality of nodes is to be sorted. The method may include assigning each respective node of the plurality of nodes of the graph dataset into a respective cluster of the two or more clusters according to respective costs that are each associated with each of the respective clusters such that all of the costs are within a threshold value of each other. The respective cost associated with its respective cluster may be determined based on a number of external edges connecting the respective nodes in the respective cluster to the nodes in each other cluster. The method may include analyzing the plurality of nodes with respect to the respective cluster to which each of the respective nodes is assigned.

Abstract: A method for audience recommendation using node similarity in combined contextual graph embeddings can include receiving a merchant identifier of a merchant and generating one or more merchant tags describing merchant data corresponding to the merchant. A set of audience embeddings can be generated from a set of audience auxiliary data using an audience taxonomy and a set of merchant embeddings can be generated from the merchant data relating to the merchant using the one or more merchant tags. The set of audience embeddings and the set of merchant embeddings are used to produce a heterogenous information network of combined audience data and merchant data, which is then analyzed to identify relationships between each audience and the merchant. A score for one or more audiences can be determined based on the relationships between the one or more audiences and the merchant.

Abstract: Disclosed are various embodiments for monitoring services in a multi-service system and detecting deviations in health metrics and/or business metrics of one or more of the services. In response to detecting a metric deviation for a given service, an enhanced message is generated detailing specific data associated with the detected deviation. The enhanced message is generated and transmitted to a recipient address associated with a services that may be affected by the deviation. An action service monitoring messages being received by a domain associated with the recipient address analyzes the information included in the message content. According to the analysis of the message, an action to be performed is identified according to the detected deviation and one or more action requests are generated and transmitted to one or more components and/or services of the multi-service system.

Abstract: System and methods are provided for detecting, tracking, and managing outages of transaction processors. An indication is received indicating a potential outage associated with a transaction processor computer configured to process transactions of an online retail website. The indication can be received from a threshold monitoring service and/or from a machine-learning detection system. A computing service can be initiated to confirm and track the outage over time. An outage may include a number of situations in which the transaction processor fails to process transactions according to a set of predefined processing parameters. If the outage spans a particular time period, the service can perform a number of remedial actions (e.g., notifying an administrator of the outage, etc.).

Abstract: A method and a modification system for modifying a search query for a user are provided. The method includes receiving at least one search query from a user; determining a present context of the user, based on the at least one search query and on-device data; identifying at least one relevant attribute related to the search query based on the present context of the user and a personalized knowledge graph, wherein the personalized knowledge graph is dynamically generated based on the on-device data; and modifying the search query, based on the at least one relevant attribute and a relation of the at least one relevant attribute with the search query, to obtain at least one modified search query.

Abstract: Embodiments provide methods and systems for predicting overall account-level risks of cardholders. The method performed by server system includes accessing payment transaction data associated with a cardholder from a transaction database. Method includes generating a set of transaction features based on a set of transaction indicators. The method includes determining a plurality of network risk scores associated with the cardholder based on the set of transaction features and a set of trained machine learning models. The plurality of network risk scores includes a payment capacity risk score, a contactless payment risk score, and a set of account-level risk scores. The method includes aggregating the plurality of network risk scores to calculate an overall account risk score associated with the cardholder based on a statistical model. The method also includes transmitting a notification to the issuer server associated with the cardholder based on the overall account risk score.

Abstract: A method for audience recommendation using node similarity in combined contextual graph embeddings can include receiving a merchant identifier of a merchant and generating one or more merchant tags describing merchant data corresponding to the merchant. A set of audience embeddings can be generated from a set of audience auxiliary data using an audience taxonomy and a set of merchant embeddings can be generated from the merchant data relating to the merchant using the one or more merchant tags. The set of audience embeddings and the set of merchant embeddings are used to produce a heterogenous information network of combined audience data and merchant data, which is then analyzed to identify relationships between each audience and the merchant. A score for one or more audiences can be determined based on the relationships between the one or more audiences and the merchant.

Abstract: A method for facilitating entity resolution is provided. A server generates a graph based on a first dataset comprising a first entity and a second dataset comprising a plurality of entities. Each node in the generated graph corresponds to the first entity or one of the plurality of entities. The server generates a plurality of embeddings for the plurality of nodes in the generated graph. Each of the plurality of embeddings represents an entity as a point in a d-dimensional embedding space. The server identifies a set of nearest neighbors for the first entity based on the plurality of embeddings. The server determines a similarity metric for each of the identified nearest neighbor with respect to the first entity. The server associates the first entity with a second entity of the second dataset that corresponds to a nearest neighbor in the set of nearest neighbors.

Abstract: An electronic device for providing contextual recommendations and a method therefor are provided. The electronic device includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain text including characters, identify, based on a language model, a domain corresponding to the text, identify a reference of the characters based on the domain, and perform, based on the reference, an action related to the domain.

Abstract: Embodiments provide methods and systems for reducing bias in an artificial intelligence model. A method includes computing, by a processor, a reward value based at least in part on a similarity between model predictions from a pre-trained model and agent predictions from a Reinforcement Learning (RL) agent. The method includes performing each step of one or more steps of a rule of a plurality of rules. The rule is assigned a weight and the rule includes a protected attribute, a cumulative statistic value type, and a comparison threshold. The method includes sending a cumulative reward value generated using the reward value and each weighted punishment value computed based at least in part on applying each rule of the plurality of rules to the RL agent. The RL agent learns to biases from the agent predictions while maintaining similarity with model predictions by maximizing the cumulative reward value.

Abstract: An approach is provided in which an information handling system captures a set of performance metrics corresponding to a traffic flow through a set of microservices included in the service mesh. Next, the information handling system identifies one or more modifications to the traffic flow based on analyzing the set of performance metrics against a set of application requirements corresponding to the set of microservices. In turn, the information handling system adjusts a traffic routing policy of the service mesh based on the identified one or more modifications.

Abstract: An approach is provided in which an information handling system captures a set of performance metrics corresponding to a traffic flow through a set of microservices included in the service mesh. Next, the information handling system identifies one or more modifications to the traffic flow based on analyzing the set of performance metrics against a set of application requirements corresponding to the set of microservices. In turn, the information handling system adjusts a traffic routing policy of the service mesh based on the identified one or more modifications.

Abstract: An electronic device for providing contextual recommendations and a method therefor are provided. The electronic device includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain text including characters, identify, based on a language model, a domain corresponding to the text, identify a reference of the characters based on the domain, and perform, based on the reference, an action related to the domain.

Abstract: An absorbent article includes an absorbent assembly including longitudinally opposite ends, transversely opposite sides, a front waist region, a back waist region. The absorbent article also includes a pair of ears extending transversely outward from the opposite sides of the absorbent assembly in the back waist region, each of the ears comprising a loop fastening component. The absorbent article also includes a nonwoven shield coupled to the garment-facing surface of the outer cover and a hook material patch, wherein the hook material patch is disposed between the outer cover and the shield such that at least a portion of the plurality of hooks is accessible through an aperture, and such that at least a portion of the base layer edges is covered by the shield.

Abstract: An absorbent article includes an absorbent assembly including longitudinally opposite ends, transversely opposite sides, a front waist region, a back waist region. The absorbent article also includes a pair of ears extending transversely outward from the opposite sides of the absorbent assembly in the back waist region, each of the ears comprising a loop fastening component. The absorbent article also includes a nonwoven shield coupled to the garment-facing surface of the outer cover and a hook material patch, wherein the hook material patch is disposed between the outer cover and the shield such that at least a portion of the plurality of hooks is accessible through an aperture, and such that at least a portion of the base layer edges is covered by the shield.

Abstract: A system and method for displaying complex scripts with a cloud computing architecture may include a client device and a cloud computing server. The client device accesses a web application via the internet and transmits a request containing complex scripts to the cloud computing server. The cloud computing server parses the text and breaks the text down to a sequence of characters of a particular script, and maps the Unicode of each character to a particular glyph to obtain a glyph ID for each character making a one to one relationship. The cloud computing server analyzes each character, assigns, and applies specific font related operations to each glyph. The cloud computing server optimizes and compresses the glyph ID and positioning data, and transmit the compressed data back to the client device to be rendered on the display of the client device.

Abstract: A system and method for displaying complex scripts with a cloud computing architecture may include a client device and a cloud computing server. The client device accesses a web application via the internet and transmits a request containing complex scripts to the cloud computing server. The cloud computing server parses the text and breaks the text down to a sequence of characters of a particular script, and maps the Unicode of each character to a particular glyph to obtain a glyph ID for each character making a one to one relationship. The cloud computing server analyzes each character, assigns, and applies specific font related operations to each glyph. The cloud computing server optimizes and compresses the glyph ID and positioning data, and transmit the compressed data back to the client device to be rendered on the display of the client device.