Abstract: Systems and methods for rating associated members in a social network are set forth. According to one embodiment a method comprising outputting a ratings interface for rating at least one member of a social network associated with a user, wherein the rating interface provides the user with the ability to rate the member in one or more categories, receiving ratings for the member from the user, associating the ratings with the member, and connecting the ratings for the member with the user is set forth.

Abstract: Systems and methods for rating associated members in a social network are set forth. According to one embodiment a method comprising outputting a ratings interface for rating at least one member of a social network associated with a user, wherein the rating interface provides the user with the ability to rate the member in one or more categories, receiving ratings for the member from the user, associating the ratings with the member, and connecting the ratings for the member with the user is set forth.

Abstract: Systems and methods for the display and navigation of a social network or set forth. According to one embodiment a method comprising identifying a first profile in a social network, identifying associated profiles associated with the first profile, ranking the associated profiles, wherein ranking is not based exclusively on a degree of separation, and outputting the associated profiles based at least in part on the ranking is set forth. According to another embodiment a method comprising identifying a user profile, identifying a member profile, determining an association path for the user profile and the member profile, and outputting the association path is set forth.

Abstract: Systems and methods for the display and navigation of a social network or set forth. According to one embodiment a method comprising identifying a first profile in a social network, identifying associated profiles associated with the first profile, ranking the associated profiles, wherein ranking is not based exclusively on a degree of separation, and outputting the associated profiles based at least in part on the ranking is set forth. According to another embodiment a method comprising identifying a user profile, identifying a member profile, determining an association path for the user profile and the member profile, and outputting the association path is set forth.

Abstract: Systems and methods for rating associated members in a social network are set forth. According to one embodiment a method comprising outputting a ratings interface for rating at least one member of a social network associated with a user, wherein the rating interface provides the user with the ability to rate the member in one or more categories, receiving ratings for the member from the user, associating the ratings with the member, and connecting the ratings for the member with the user is set forth.

Abstract: Systems and methods for automatic generation and recommendation of communities in a social network or set forth. According to one embodiment a method comprising accessing a group of profiles in a social network, identifying a match between entries in at least two profiles within the group of profiles, and determining a community based at least in part on the match is set forth.

Abstract: Systems and methods for providing a gift registry are described. In one described method, gift interest data is identified. A gift registry comprising a gift indicator associated with the gift interest data is generated. An audience criterion is identified, and an inquiry signal is received. The inquiry signal is evaluated for satisfaction of the audience criterion, and the gift registry is output if the inquiry signal satisfies the audience criterion.

Abstract: A search engine may perform a search for a user search query over a number of possible search categories. For example, the search query may be performed for general web documents, images, and news documents. The search engine ranks categories based on the search query and/or the documents returned for each category and presents the search results to the user by category. Higher ranking categories may be presented more prominently than lower ranking categories.

Abstract: A search engine may perform a search for a user search query over a number of possible search categories. For example, the search query may be performed for general web documents, images, and news documents. The search engine ranks categories based on the search query and/or the documents returned for each category and presents the search results to the user by category. Higher ranking categories may be presented more prominently than lower ranking categories.

Abstract: A method for evaluating an input system interfacing a human user with an electronic device uses empirically determined bi-action times for users to perform a second input action (e.g., pressing a second key) immediately after performing a first input action (e.g., pressing a first key). The bi-action times (or, more generally, n-action times) are used together with a selected interface map which associates input actions (e.g., pressing keys) to corresponding signifiers (e.g., characters) to calculate a peak expert input rate for the input system. One or more optimized interface maps can be found by combining the evaluation method with any of various optimization strategies. For example, one method for optimizing the input system repeatedly changes the interface map and recalculates the peak expert input rate, while another optimization method calculates peak expert input rates for multiple interface maps in parallel.

Abstract: A search engine may perform a search for a user search query over a number of possible search categories. For example, the search query may be performed for general web documents, images, and news documents. The search engine ranks categories based on the search query and/or the documents returned for each category and presents the search results to the user by category. Higher ranking categories may be presented more prominently than lower ranking categories.

Abstract: Systems and methods for rating associated members in a social network are set forth. According to one embodiment a method comprising outputting a ratings interface for rating at least one member of a social network associated with a user, wherein the rating interface provides the user with the ability to rate the member in one or more categories, receiving ratings for the member from the user, associating the ratings with the member, and connecting the ratings for the member with the user is set forth.

Abstract: Systems and methods for the display and navigation of a social network or set forth. According to one embodiment a method comprising identifying a first profile in a social network, identifying associated profiles associated with the first profile, ranking the associated profiles, wherein ranking is not based exclusively on a degree of separation, and outputting the associated profiles based at least in part on the ranking is set forth. According to another embodiment a method comprising identifying a user profile, identifying a member profile, determining an association path for the user profile and the member profile, and outputting the association path is set forth.

Abstract: A method for evaluating an input system interfacing a human user with an electronic device uses empirically determined bi-action times for users to perform a second input action (e.g., pressing a second key) immediately after performing a first input action (e.g., pressing a first key). The bi-action times (or, more generally, n-action times) are used together with a selected interface map which associates input actions (e.g., pressing keys) to corresponding signifiers (e.g., characters) to calculate a peak expert input rate for the input system. One or more optimized interface maps can be found by combining the evaluation method with any of various optimization strategies. For example, one method for optimizing the input system repeatedly changes the interface map and recalculates the peak expert input rate, while another optimization method calculates peak expert input rates for multiple interface maps in parallel.