Abstract: In an example, a system and method is disclosed for providing a user matching system. To ease creation of a profile, a node may be enabled to connect to a third-party social media site where the node already has an established profile. The established profile is imported, wherein common fields are directly mapped, inferred fields may be deterministically inferred, and other fields such as “likes” may be assigned relative weights based on recentness, subjective user rankings, or correlation to other “likes.” The node may also be enabled to permanently log in to the matching system via credentials for the third-party social media site.

Abstract: In an example, a system and method is disclosed for providing a user matching system. To ease creation of a profile, a node may be enabled to connect to a third-party social media site where the node already has an established profile. The established profile is imported, wherein common fields are directly mapped, inferred fields may be deterministically inferred, and other fields such as “likes” may be assigned relative weights based on recentness, subjective user rankings, or correlation to other “likes.” The node may also be enabled to permanently log in to the matching system via credentials for the third-party social media site.

Abstract: Finding a match for an end user on an online social platform is not a trivial task. To improve match making, various methods and systems are disclosed which are configured to compute heuristics for various end users, which help to predict the likelihood that two end users would ultimately engage in some form of communication with each other. The heuristics are used in an algorithm (i.e., a statistical/predictive model) for providing a set of matches to an end user. These heuristics may be computed based on varying forms of communication which indicate different levels of engagement between end users, and/or based on some other indication of how an end user may react to another end user.

Abstract: Finding a match for an end user on an online social platform is not a trivial task. To improve match making, various methods and systems are disclosed which are configured to compute heuristics for various end users, which help to predict the likelihood that two end users would ultimately engage in some form of communication with each other. The heuristics are used in an algorithm (i.e., a statistical/predictive model) for providing a set of matches to an end user. These heuristics may be computed based on varying forms of communication which indicate different levels of engagement between end users, and/or based on some other indication of how an end user may react to another end user.

Abstract: Finding a match for an end user on an online social platform is not a trivial task. To improve match making, various methods and systems are disclosed which are configured to compute heuristics for various end users, which help to predict the likelihood that two end users would ultimately engage in some form of communication with each other. The heuristics are used in an algorithm (i.e., a statistical/predictive model) for providing a set of matches to an end user. These heuristics may be computed based on varying forms of communication which indicate different levels of engagement between end users, and/or based on some other indication of how an end user may react to another end user.

Abstract: In an example, a system and method are disclosed for providing functionality for two users of a matching service, such as an online dating service, to identify a midpoint at which they may conveniently meet. User locations may be based on exact coordinates, or may be more generalized, such as by zip code or city. A midpoint is identified, which may be a geographic center, or which may be a relatively-centralized place of interest. In some cases, a plurality of potential meeting locations are displayed and are ranked for the user.

Abstract: A method is provided in one example embodiment and includes identifying a user in a computer-implemented matching system as having paid a fee for additional promotion of the identified user during a promotional period; and, during the promotional period, providing impressions for the identified user in accordance with an impression probability calculated to achieve a promotional target with respect to the user, wherein the impressions comprise presenting the identified user to other users in the computer-implemented matching system. In one embodiment, the promotional target comprises a target number of visits by other users to a profile of the identified user during the promotional period. In another embodiment, the promotional target comprises a target number of impressions for the identified user during the promotional period.

Abstract: A method is provided in one example embodiment and includes identifying a user in a computer-implemented matching system as having paid a fee for additional promotion of the identified user during a promotional period; and, during the promotional period, providing an increased number of impressions for the identified user to achieve a promotional target with respect to the user, in which the impressions comprise presenting the identified user to other users in the computer-implemented matching system. The method further includes providing evidence to the identified user of each of the impressions during the promotional period; and providing at least one premium service to the identified user to enable the identified user to optimize use of the computer-implemented matching system.

Abstract: A method is provided in one example embodiment and includes processing a first text created by a user into a first bag of words, the first bag of words comprising a list of words that appear in the text, each of the words having associated therewith a number representing a number of times the associated word appears in the text; and computing a similarity between the first bag of words and at least one second bag of words. The method further comprises comparing the computed similarity with a threshold; and determining that the user is a spammer if the computed similarity bears a first relationship with the threshold.

Abstract: In one embodiment, a method executed by at least one processor includes receiving text from submitted by a user. The method also includes determining a text score for the received text by comparing a first set of phrases included in the received text to a second set of phrases. The second set of phrases includes phrases from stored text. The stored text includes stored text known to be genuine and stored text known to be fraudulent. The method also includes determining that the received text is fraudulent based on the text score.

Abstract: A method for facilitating a sequenced, anonymous communications session in a communications environment is provided in one example that includes receiving, from a first endpoint, an anonymous, sequenced request for a communication session involving a second endpoint. The communication session is sequenced to occur at designated periods provided by the end user(s) and/or an administrator, while maintaining end user(s) anonymity.

Abstract: Methods and systems for providing offers to a user through a user interface are disclosed. A first offer having a first price to a user through the user interface is provided. A user input indicating an acceptance to the first offer through the user interface is received. A request is transmitted to a payment processor to process a payment from a payment account of the user for the first price. A message from the payment processor in response to the request that the first request cannot be completed is received. A first message is processed to generate a second offer having a second price, wherein the second price is lower than the first price. The second offer to the user through the user interface.

Abstract: A method is provided in one example embodiment and includes determining a first number of users who have indicated an intention to attend an event; determining what fraction of the first number of users is a particular gender; and using the determined fraction and an ideal fraction of the particular gender for the event to determine an additional number of males or an additional number of females to be invited to attend the event.

Abstract: A method is provided in one example embodiment and includes determining a score for at least one parameter associated with an event and a user and applying to the score a filter associated with the at least one parameter to determine whether the score falls within a range defined by the filter. The method also includes displaying the event to the user if the score falls within the range defined by the filter and hiding the event from the user if the score falls outside of the range defined by the filter.

Abstract: In one example embodiment, a method for facilitating an anonymous video/multimedia communication session in a communications environment over a network is provided that includes receiving, from a first endpoint, a request for a communication session involving a second endpoint. The method also includes identifying end user data associated with both endpoints. The data associated with the first endpoint is mapped to an identity of the first endpoint. The second endpoint can be shown the identity of the first endpoint and not the end user data associated with the first endpoint. Also, the data associated with the second endpoint can be mapped to an identity of the second endpoint. The first endpoint is shown the identity of the second endpoint and not the end user data associated with the second endpoint.

Abstract: In one embodiment, a method executed by at least one processor includes receiving text from submitted by a user. The method also includes determining a text score for the received text by comparing a first set of phrases included in the received text to a second set of phrases. The second set of phrases includes phrases from stored text. The stored text includes stored text known to be genuine and stored text known to be fraudulent. The method also includes determining that the received text is fraudulent based on the text score.

Abstract: A method for facilitating a sequenced, anonymous communications session in a communications environment is provided in one example that includes receiving, from a first endpoint, an anonymous, sequenced request for a communication session involving a second endpoint. The communication session is sequenced to occur at designated periods provided by the end user(s) and/or an administrator, while maintaining end user(s) anonymity.

Abstract: A method for facilitating a sequenced, anonymous communications session in a communications environment is provided in one example that includes receiving, from a first endpoint, an anonymous, sequenced request for a communication session involving a second endpoint. The communication session is sequenced to occur at designated periods provided by the end user(s) and/or an administrator, while maintaining end user(s) anonymity.

Abstract: In one example embodiment, a method is provided that includes interfacing with one or more end users via a central website and managing information related to one or more of the end users. The method also includes determining a personality type for one or more end users and matching end users based on relationship rules of the personality types that outline compatibilities between the personality types. In more specific embodiments, the determining of the personality type includes an evaluation of a hand of a selected end user. The personality types can be based on inferred levels of testosterone, serotonin, or estrogen. The personality type determination can also be made based on a set of questions. The personality type determination can also be based on evaluating a selected end user's word choice and/or the frequency in their word choice in their writing.

Abstract: A method for profile matching includes receiving a plurality of user profiles, each user profile comprising traits of a respective user. The method includes receiving a preference indication for a first user profile of the plurality of user profiles. The method also includes determining a potential match user profile of the plurality of user profiles based on the preference indication for the first user profile. The method also includes presenting the potential match user profile to a second user.