Abstract: The early adopters and potential influencers (EAPI) system, method and computer-readable medium provide a way to identify early adopters and potential influencers. The EAPI system obtains a list of purchases for customers of merchants and/or subscriptions from a transaction tracking system. The EAPI system creates a time-based transaction network, and using a scoring function, the EAPI system determines an early adopter and/or potential influencer ranking among customers in the network. The EAPI system may use one or more customer attributes to determine a customer's influence with respect to different dimensions.

Abstract: The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

Abstract: Various methods are provided for determining transactional networks using transactional data. One example method may comprise receiving a set of transactional data associated each of a plurality of customers, the set of the transactional data comprising a plurality of ordered lists of elements, each ordered list of elements defining a transaction of a plurality of transactions, the ordered list of elements comprising information identifying a particular customer from the plurality of customers, a merchant, and a timestamp, for each particular customer from the plurality of customers, generating a network, each generated network comprising one or more merchant nodes, a plurality of customer nodes, one or more merchant-customer edges between at least one of the one or more merchant nodes and at least one of the plurality of customer nodes, and one or more customer-customer edges between two or more customer nodes.

Abstract: The present invention is associated with a method that takes a subsequence of a credit card number, in particular the suffix (or last n digits), and transaction data associated with the cardholder. For each subsequence of the credit card number, a set of data may be used in order to uniquely identify the cardholder. The identification of the cardholder may be performed in a particular search space that is composed of all possible credit card numbers and includes the transaction data associated with the cardholder.

Abstract: The present invention is associated with a computerized system that takes a subsequence of a credit card number, in particular the suffix (or last n digits), and transaction data associated with the cardholder. For each subsequence of the credit card number, a set of data may be used in order to uniquely identify the cardholder. The identification of the cardholder may be performed in a particular search space that is composed of all possible credit card numbers and includes the transaction data associated with the cardholder. In an exemplary embodiment, the computerized system is used to promote engagements between individual cardholders and merchants by effectuating marketing actions in combination with commercial transactions when products or subscriptions are purchased.

Abstract: A method whereby an audio content is analyzed for speech semantic content and speech vocal content to determine audio content metrics. Additionally, the method may also incorporate the similarity of the audio content to other audio contents and weight the analyses to determine audio content metrics.

Abstract: The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

Abstract: A method of operating a speech synthesizing conversation agent involves operating an audio interface to receive caller audio signal during a call session. The method generates an audio transcript from the caller audio signal through operation of a sentiment analysis engine configured by a sentiment model. The method communicates the audio transcript to a user interface switch. The method operates the speech synthesizer engine. The speech synthesizer engine generates a response signal for the caller audio signal and the audio transcript through operation of response logic engine configured by the historical conversation data. The speech synthesizer engine generates a synthesized audio response with ambient signal and a synthesized user model response from the response signal through operation of a speech synthesis model configured by the historical conversation data. The method communicates the synthesized audio response to the caller audio signal through the audio interface during the call session.

Abstract: The early adopters and potential influencers (EAPI) system, method and computer-readable medium provide a way to identify early adopters and potential influencers. The EAPI system obtains a list of purchases for customers of merchants and/or subscriptions from a transaction tracking system. The EAPI system creates a time-based transaction network, and using a scoring function, the EAPI system determines an early adopter and/or potential influencer ranking among customers in the network. The EAPI system may use one or more customer attributes to determine a customer's influence with respect to different dimensions.

Abstract: A method of operating a speech synthesizing conversation agent involves operating an audio interface to receive caller audio signal during a call session. The method generates an audio transcript from the caller audio signal through operation of a sentiment analysis engine configured by a sentiment model. The method communicates the audio transcript to a user interface switch. The method operates the speech synthesizer engine. The speech synthesizer engine generates a response signal for the caller audio signal and the audio transcript through operation of response logic engine configured by the historical conversation data. The speech synthesizer engine generates a synthesized audio response with ambient signal and a synthesized user model response from the response signal through operation of a speech synthesis model configured by the historical conversation data. The method communicates the synthesized audio response to the caller audio signal through the audio interface during the call session.

Abstract: The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

Abstract: The early adopters and potential influencers (EAPI) system, method and computer-readable medium provide a way to identify early adopters and potential influencers. The EAPI system obtains a list of purchases for customers of merchants and/or subscriptions from a transaction tracking system. The EAPI system creates a time-based transaction network, and using a scoring function, the EAPI system determines an early adopter and/or potential influencer ranking among customers in the network. The EAPI system may use one or more customer attributes to determine a customer's influence with respect to different dimensions.

Abstract: A distributed multisensory system to record spatially diverse events configures a group of sensors searching sensed events utilizing random access search. The system utilizes presence and co-location detection to identify objects or people in an area. The system then processes audio signals utilizing a multimodal network and machine learning tiered with obfuscated text indexing to provide high-speed, high accuracy searching of stored data. In addition, the obfuscated text allows the system to not have to store an audio transcript, increasing the security of the system. The system utilizes beamforming to merge resultant audio streams for the recorded event.

Abstract: The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

Abstract: The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

Abstract: The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

Abstract: The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

Abstract: The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

Abstract: The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.

Abstract: The present invention is associated with a method that takes a subsequence of a credit card number, in particular the suffix (or last n digits), and transaction data associated with the cardholder. For each subsequence of the credit card number, a set of data may be used in order to uniquely identify the cardholder. The identification of the cardholder may be performed in a particular search space that is composed of all possible credit card numbers and includes the transaction data associated with the cardholder.