Adobe, Inc.

Geoff Baum

Walter Chang

Thomas J Malloy

Minhoe Hur

Systems and methods are discussed to automatically create a domain ontology that is a combination of ontologies. Some embodiments include systems and methods for developing a combined ontology for a website that includes extracting collocations for each webpage within the website, creating first and second ontologies from the collocations, and then aggregating the ontologies into a combined ontology. Some embodiments of the invention include unique ways to calculate collocations, to develop a smaller yet meaningful document sample from a large sample, to determine webpages of interest to users interacting with a website, and to determine topics of interest of users interacting with a website. Various other embodiments of the invention are disclosed.

Hybrid method of building topic ontologies for publisher and marketer content and ad recommendations

A group offer is provided to a first-level recipient that meets a set of criteria. Further, the group offer is activated upon a consumer participant threshold being met, the consumer participant threshold equaling a number of consumers. In addition, a social incentive structure is established that provides a reward to the first-level recipient if the first-level recipient shares the group offer with a second-level recipient that (i) is in a social circle associated with the first-level recipient and (ii) meets a set of qualifications.

Distribution of offer to a social group by sharing based on qualifications

User data and a plurality of micro-segment definitions are received. Each micro-segment definition in the plurality of micro-segment definitions corresponds to one or more offers in an offer provider campaign. Further, a micro-segment parser parses each micro-segment definition from the plurality of micro-segment definitions into a plurality of parsed expression segments that indicate a plurality of micro-segment condition rules. In addition, a compiler compiles the plurality of parsed expression segments into an executable object that indicates a plurality of instructions to determine if the user data matches the plurality of micro-segment definitions. Each micro-segment definition is also serially processed, with a sequential evaluation engine, to apply the plurality of micro-segment condition rules to the user data to determine a match of a user belonging to a micro-segment. Further, the sequential evaluation engine assigns a score to indicate the strength of each match. In addition, the process ranks, with the sequential evaluation engine, each match according to the score for each match.

Sequential engine that computes user and offer matching into micro-segments

A selection of one or more segment attributes from an offer provider campaign is received at a graphical user interface. The one or more segment attributes define one or more segments that correspond to one or more offers in the offer provider campaign. Further, an expression graph based on the one or more segment attributes is generated. In addition, a portable micro-segment object is generated based on the expression tree such that the portable micro-segment object lacks dependence on the offer provider campaign.

Micro-segment definition system

An extensible offer inventory database of offers in a domain is established. Further, an offer ontology is generated based on the extensible offer inventory database. The offer ontology provides an extensible vocabulary that correlates to categories in the offer inventory database. In addition, offers are automatically located. The offers are also semantically analyzed to generate semantic analysis data. Further, user data is obtained. In addition, an optimal offer match is automatically determined based upon the semantic analysis data and the user data.

Automatic expansion of an advertisement offer inventory

User data and a plurality of micro-segment definitions such that each micro-segment definition in the plurality of micro-segment definitions corresponds to one or more offers in an offer provider campaign are received. Further, a dispatcher dispatches a first subset of the user data and a first subset of the plurality of the micro-segment definitions to a first node in a network. In addition, the dispatcher dispatches a second subset of the user data and a second subset of the plurality of the micro-segment definitions to a second node in the network. Parsing and compiling are performed at each node. Further, parallel processing is performed at a scalable evaluation engine at each node to apply micro-segment condition rules to user data to determine matches to micro-segments. Computation of micro-segments occurs in parallel and resulting micro-segment assignments are collected, filtered to remove duplicates, then ranked to produce a final set of micro-segments that can be used to find offers.

Computing user micro-segments for offer matching

A campaign is received, at a micro-segmentation system, from an offer provider. The micro-segmentation system is a third-party system. The campaign indicates a set of target attributes and one or more offers corresponding to the set of target attributes. A set of user attributes pertaining to each of the plurality of users is received at the micro-segmentation system. The set of attributes is defined by an attribute knowledge structure. Permission is received at the micro-segmentation system from each of the plurality of users to receive an offer from the micro-segmentation system. Data associated with the micro-segment classification is provided from the micro-segmentation system without user information to the offer provider.

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Palo Alto, CA, United States of America

Geoff Baum