Abstract: A new approach is proposed that contemplates systems and methods to determine temporality of a query in order to generate a search result including a list of objects that are not only based on matching of the objects to the query but also based on temporality analysis of the query. Here, the temporality of the query can be defined as the distribution over time of the objects matching the query, i.e., the chronology histogram of the query. Such distribution can be analyzed to provide a classification of the intent of the query. Classification of the intent of the query can result either in discrete classification of the query into categories, or in continuous classification of the query which may be a scalar or vector value resulting from transformations of the chronology histogram.

Abstract: Advertising based on influence is provided. In some embodiments, advertising based on influence includes determining an influence score (e.g., based on a given dimension) for a subject (e.g., a user), in which the subject is a potential target for an advertisement; and determining targeting of the advertisement based on criteria including the influence score of potential recipients of the advertisement. In some embodiments, the influence score is a directly estimated objective measure of influence (e.g., estimated using a social graph). In some embodiments, advertising based on influence also includes determining pricing of advertisements based on criteria including the influence score of potential recipients of one or more advertisements. In some embodiments, advertising based on influence further includes sharing advertising revenue with the subject based on criteria including the influence score of the first subject (e.g., as an incentive for the subject to view the advertisement).

Abstract: Advertising based on influence is provided. In some embodiments, advertising based on influence includes determining an influence score (e.g., based on a given dimension) for a subject (e.g., a user), in which the subject is a potential target for an advertisement; and determining targeting of the advertisement based on criteria including the influence score of potential recipients of the advertisement. In some embodiments, the influence score is a directly estimated objective measure of influence (e.g., estimated using a social graph). In some embodiments, advertising based on influence also includes determining pricing of advertisements based on criteria including the influence score of potential recipients of one or more advertisements. In some embodiments, advertising based on influence further includes sharing advertising revenue with the subject based on criteria including the influence score of the first subject (e.g., as an incentive for the subject to view the advertisement).

Abstract: Ranking and selecting entities based on calculated reputation or influence scores is provided. In some embodiments, a method includes determining whether a first entity is a subject or an object; determining whether a second entity is a subject or an object; and generating a graph, in which a subset of the graph is a subject graph of subject nodes that includes at least one or more subjects (e.g., subject entities) linked to one or more other subjects, and in which the graph includes one or more objects (e.g., object entities) each linked to one or more subjects in the subject graph. In some embodiments, the graph includes directed and undirected links. In some embodiments, the graph includes one or more objects linked to one or more objects.

Abstract: A new approach is proposed that contemplates systems and methods to support efficient crawling of a social media network based on predicted future activities of each user on the social network. First, data related to a user's past activities on a social network are collected and a pattern of the user's past activities over time on the social network is established. Based on the established pattern on the user's past activities, predictions about the user's future activities on the social network can be established. Such predictions can then be used to determine the collection schedule—timing and frequency—to collect data on the user's activities for future crawling of the social network.

Abstract: Estimating influence includes receiving a subject graph, in which the subject graph includes two or more subject nodes, in which each subject node corresponds to a subject; and determining an objective influence measure for each first subject node of the subject graph, in which the determination is based at least on part on a function of inward scores and outward scores, in which inward scores are computed from one or more paths leading to the first subject of a length of at least one, and outward scores are computed from one or more paths leading from the first subject of a length of at least one.

Abstract: Systems and methods allowing for the attribution of reputation to data sources (e.g., for the creation of referrals) are provided. In an illustrative implementation scores (e.g., reputation scores) are determined for a target entity connected a source entity on a network on a given dimension. In the illustrative implementation, an entity may be directly linked to any number of other entities on any number of dimensions, with each link having an associated score. Illustratively, each dimension has an associated transitive dimension. A directed path on a given dimension between two entities, a source and a target, consists of a directed link from the source entity to an intermediate entity, prefixed to a directed path from the intermediate entity to the target entity. In the illustrative implementation, links on the path can travel on the transitive dimension associated with the given dimension.

Abstract: Systems and methods allowing for the attribution of reputation to data sources (e.g., for the creation of referrals) are provided. In an illustrative implementation scores (e.g., reputation scores) are determined for a target entity connected a source entity on a network on a given dimension. In the illustrative implementation, an entity may be directly linked to any number of other entities on any number of dimensions, with each link having an associated score. Illustratively, each dimension has an associated transitive dimension. A directed path on a given dimension between two entities, a source and a target, consists of a directed link from the source entity to an intermediate entity, prefixed to a directed path from the intermediate entity to the target entity. In the illustrative implementation, links on the path can travel on the transitive dimension associated with the given dimension.

Abstract: Mediating and pricing transactions based on calculated reputation and influence is provided. In some embodiments, mediating and pricing transactions based on calculated reputation and influence includes determining an influence score (e.g., based on a given dimension) for a subject (e.g., a user), in which the subject is requesting a transaction; and determining approval of the transaction based on criteria including the influence score of the subject. In some embodiments, the influence score is a directly estimated objective measure of influence (e.g., estimated using a social graph). In some embodiments, mediating and pricing transactions based on calculated reputation and influence further includes determining pricing of the transaction based on criteria including the influence score of the subject.

Abstract: Estimating influence is provided. For example, estimating influence includes determining an objective influence measure, which can be applied to various applications (e.g., search using objective influence).

Abstract: Advertising based on influence is provided. In some embodiments, advertising based on influence includes determining an influence score (e.g., based on a given dimension) for a subject (e.g., a user), in which the subject is a potential target for an advertisement; and determining targeting of the advertisement based on criteria including the influence score of potential recipients of the advertisement. In some embodiments, the influence score is a directly estimated objective measure of influence (e.g., estimated using a social graph). In some embodiments, advertising based on influence also includes determining pricing of advertisements based on criteria including the influence score of potential recipients of one or more advertisements. In some embodiments, advertising based on influence further includes sharing advertising revenue with the subject based on criteria including the influence score of the first subject (e.g., as an incentive for the subject to view the advertisement).