Abstract: The disclosed embodiments relate to a computer implemented recommender system/method which enables the computer to provide more “emotionally” relevant/connected, and therefore more likely to be successful, recommendations while minimizing dependency on historical data as well susceptibility to bias, e.g., monetary and/or sponsor based. The disclosed embodiments segment a target set of known users into groups based on similar characteristics and then associate each group with one or more unique sets of affinities derived from the social media interactions of a general population having similar affinities. Similarly, a unique set of affinity characteristics is derived, and stored in a data structure, for each of a set of recommendations. The unique sets of affinities associated with the groups are compared with the set of affinity characteristics associated with each recommendations to derive a subset thereof relevant to the users of the particular group.

Abstract: The disclosed embodiments relate to a computer implemented recommender system/method which enables the computer to provide more “emotionally” relevant/connected, and therefore more likely to be successful, recommendations while minimizing dependency on historical data as well susceptibility to bias, e.g. monetary and/or sponsor based. The disclosed embodiments segment a target set of known users into groups based on similar characteristics and then associate each group with one or more unique sets of affinities derived from the social media interactions of a general population having similar affinities. Similarly, a unique set of affinity characteristics is derived, and stored in a data structure, for each of a set of recommendations. The unique sets of affinities associated with the groups are compared with the set of affinity characteristics associated with each recommendations to derive a subset thereof relevant to the users of the particular group.

Abstract: The disclosed embodiments relate to a computer implemented recommender system/method which enables the computer to provide more “emotionally” relevant/connected, and therefore more likely to be successful, recommendations while minimizing dependency on historical data as well susceptibility to bias, e.g. monetary and/or sponsor based. The disclosed embodiments segment a target set of known users into groups based on similar characteristics and then associate each group with one or more unique sets of affinities derived from the social media interactions of a general population having similar affinities. Similarly, a unique set of affinity characteristics is derived, and stored in a data structure, for each of a set of recommendations. The unique sets of affinities associated with the groups are compared with the set of affinity characteristics associated with each recommendations to derive a subset thereof relevant to the users of the particular group.

Abstract: The disclosed embodiments relate to a computer implemented recommender system/method which enables the computer to provide more “emotionally” relevant/connected, and therefore more likely to be successful, recommendations while minimizing dependency on historical data as well susceptibility to bias, e.g. monetary and/or sponsor based. The disclosed embodiments segment a target set of known users into groups based on similar characteristics and then associate each group with one or more unique sets of affinities derived from the social media interactions of a general population having similar affinities. Similarly, a unique set of affinity characteristics is derived, and stored in a data structure, for each of a set of recommendations. The unique sets of affinities associated with the groups are compared with the set of affinity characteristics associated with each recommendations to derive a subset thereof relevant to the users of the particular group.

Abstract: The disclosed embodiments relate to a computer implemented recommender system/method which enables the computer to provide more “emotionally” relevant/connected, and therefore more likely to be successful, recommendations while minimizing dependency on historical data as well susceptibility to bias, e.g. monetary and/or sponsor based. The disclosed embodiments segment a target set of known users into groups based on similar characteristics and then associate each group with one or more unique sets of affinities derived from the social media interactions of a general population having similar affinities. Similarly, a unique set of affinity characteristics is derived, and stored in a data structure, for each of a set of recommendations. The unique sets of affinities associated with the groups are compared with the set of affinity characteristics associated with each recommendations to derive a subset thereof relevant to the users of the particular group.

Abstract: A system includes a memory and processor. The memory stores a user account identifier associated with a user account. The processor receives at least one user credential and authenticates the user account based at least in part on the at least one user credential. The processor further receives a first request, from a device associated with the user account, to generate a one-time password and generates the one-time password in response to receiving the first request. The processor associates the one-time password to the user account and communicates the one-time password to the device associated with the user account. The processor further receives a second request, from a transaction device, the second request comprising an attempted one-time password, determines whether the attempted one-time password is valid, and communicates, to the transaction device, an indication that the attempted one-time password is valid in response to determining that the attempted one-time password is valid.

Abstract: A system may include a memory and processor. The memory may store a user account identifier associated with a user account. The processor may be able to receive at least one user credential and authenticate the user account based at least in part on the at least one user credential. The processor may also receive a first request, from a device associated with the user account, to generate a one-time password and generate the one-time password in response to receiving the first request. The processor may associate the one-time password to the user account and communicate the one-time password to the device associated with the user account.

Abstract: A system may include a memory and processor. The memory may store a user account identifier associated with a user account. The processor may be able to receive at least one user credential and authenticate the user account based at least in part on the at least one user credential. The processor may also receive a first request, from a device associated with the user account, to generate a one-time password and generate the one-time password in response to receiving the first request. The processor may associate the one-time password to the user account and communicate the one-time password to the device associated with the user account.