Abstract: Method and apparatus for measuring and influencing article selection in a social network are disclosed. A learning-and-guiding module tracks access to articles by users of the social network and determines patterns of users' attraction to articles based on contents of articles and attributes of users. The module utilizes learned user-articles characteristics to influence article selection through communicating with users through the social network. The module relies on historical usage data characterizing user's affinity to articles. To guard against usage data obsolescence due to shifting interests, usage data are frequently adjusted to place more emphasis on recent usage patterns.

Abstract: A marketing inference engine determines prospective clients, drawn from a population of users, for a commodity. A set of relevant consumer traits is conjectured or determined from data relevant to prior clients of the commodity. Massive data characterizing the population is analysed to determine a superset of user communities of the population of users, each community corresponding to a respective trait of a predefined superset of traits. A set of primary communities, corresponding to the set of relevant consumer traits, is selected from the superset of communities. A set of secondary communities, each determined to have a significant kinship to the set of primary communities, is selected from the superset of communities. A set of primary prospective clients is determined from the primary communities. An expanded set of prospective clients is determined from both the primary communities and the secondary communities.

Abstract: Method and apparatus for measuring and influencing article selection in a social network are disclosed. A learning-and-guiding module tracks access to articles by users of the social network and determines patterns of users' attraction to articles based on contents of articles and attributes of users. The module utilizes learnt user-articles characteristics to influence article selection through communicating with users through the social network. The module relies on historical usage data characterizing user's affinity to articles. To guard against usage data obsolescence due to shifting interests, usage data are frequently adjusted to place more emphasis on recent usage patterns.

Abstract: A method and apparatus for machine-aided marketing are disclosed. A hardware processor executes instructions for tracking a population of social-media users, segmenting the population of users into a set of clusters based on individual user properties, acquiring metrics of user behaviour, and determining saturation of candidate metrics within each cluster based on the individual user metrics. The method identifies a set of distinctive metrics and corresponding distinct clusters according to metric-saturation levels. To promote a specific commodity, the method determines compatible distinctive metrics and at least one distinct cluster. Various means of communicating with users of the at least one distinct cluster may then be employed.

Abstract: Methods and apparatus for guiding article selection from a vast collection of articles are disclosed. Inter-article affinity measures are determined based on individual article characteristics and network-users' successive access to articles. For each detected access to an article, the apparatus determines a complementing article according to the inter-article affinity measures and communicates an identifier of the complementing article to a respective user. The apparatus employs multiple hardware processor and maintains a registry of article-selection data, for active users detected by the apparatus, and a storage medium storing inter-article transition scores and inter-article affinity coefficients which are continually updated.

Abstract: Methods and apparatus for directing access to sources of information through an information dissemination network are disclosed. Upon detecting a user's access to a source, a recommendation to access a complementing source is communicated to the user. The recommendation is based on affinity measures for pairs of sources of information. Upon detecting the user's access transition to a new source of information within a predefined time interval, inter-source transition scores are recorded and new affinity levels of the current source to the new source are determined for each affinity measure. Affinity merits corresponding to affinity levels are determined based on tracking a population of users and determining users' compliance with recommendation. A complementing source is selected according to affinity merits corresponding to specific affinity levels of a current source to a set of sources.

Abstract: Method and apparatus for interacting with an information distribution system to determine a preferred article to access following inspection of any article of a collection of articles are disclosed. A candidate target article is evaluated based on content similarity to a currently inspected article as well as usage data indicating article-transition patterns. Usage data of the population of users is sorted according to predefined users' groups. For a user, of a specific group, currently inspecting a specific article, a recommendation of a candidate successor article is influenced by content similarity, article transition-pattern of the population of users, and respective group-specific article-transition patterns, with the latter preferably given more weight.

Abstract: Method and apparatus for measuring and influencing article selection in a social network are disclosed. A learning-and-guiding module tracks access to articles by users of the social network and determines patterns of users' attraction to articles based on contents of articles and attributes of users. The module utilizes learnt user-articles characteristics to influence article selection through communicating with users through the social network. The module relies on historical usage data characterizing user's affinity to articles. To guard against usage data obsolescence due to shifting interests, usage data are frequently adjusted to place more emphasis on recent usage patterns.