SYSTEM AND METHOD FOR LEVERAGING PROXIMITY DATA IN A WEB-BASED SOCIALLY-ENABLED KNOWLEDGE NETWORKING ENVIRONMENT
First Claim
1. A method of advertisement optimization via semantic profiles, comprising:
- receiving a model profile from an advertiser, the model profile represents an ideal set of user characteristics of a model user specified by the advertiser;
parsing the model profile to obtain a first set of model user metadata associated with the ideal set of user characteristics;
comparing model user metadata of the first set of model user metadata with user metadata of a set of user metadata of a semantic user profile of a user; and
generating a correlation index to indicate a degree of correlation between the model profile and the semantic user profile.
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Abstract
Systems and methods for leveraging proximity data in a web-based socially-enabled information networking environment are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of semantic advertising via semantic profiles. One embodiment can include, receiving a model profile from an advertiser, enforcing a set of rules that govern accessibility of the web content, parsing the model profile to obtain a first set of model user metadata associated with the ideal set of user characteristics, comparing model user metadata of the first set of model user metadata with user metadata of a set of user metadata of a semantic user profile of a user, and generating a correlation index to indicate a degree of correlation between the model profile and the semantic user profile.
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Citations
49 Claims
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1. A method of advertisement optimization via semantic profiles, comprising:
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receiving a model profile from an advertiser, the model profile represents an ideal set of user characteristics of a model user specified by the advertiser; parsing the model profile to obtain a first set of model user metadata associated with the ideal set of user characteristics; comparing model user metadata of the first set of model user metadata with user metadata of a set of user metadata of a semantic user profile of a user; and generating a correlation index to indicate a degree of correlation between the model profile and the semantic user profile. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A method of generating a semantic user profile, comprising:
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identifying context-independent user metadata for generating a context-independent semantic user profile; identifying context-dependent user metadata for generating a context-dependent semantic user profile; identifying temporal user meta-data for generating a temporal semantic user profile; and generating the semantic user profile from at least one of the context-independent semantic user profile, the context-dependent semantic user profile, and the temporal semantic user profile. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
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29. A method of generating a context-independent semantic user profile in a web-based environment for a user, comprising:
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receiving explicit user input from the user via web-submission; identifying a plurality of relationships the user has with a plurality of entities in the web-based environment;
wherein the plurality of entities comprises one or more of, tangible, intangible and software entities; andtracking user click-stream history to track and collect data related to aggregate user behavior in the web-based environment. - View Dependent Claims (30, 31, 32, 33)
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34. A method of generating a context-dependent semantic user profile, comprising:
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identifying context-related activity in a web-based environment that the user is currently engaged in through a web-browser; identifying a first set of entities of the plurality of entities in the web-based environment associated with the context-related activity; and identifying a set of context-dependent meta-tags from the first set of entities.
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35. A method of generating a temporal semantic user profile, comprising:
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aggregating a set of user activity performed in the web-based environment through the web-browser within a time window; identifying a second set of entities of the plurality of entities in the web-based environment associated with the set of user activity; and identifying a set of temporal meta-tags from the second set of entities. - View Dependent Claims (36)
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37. A method of determining proximity between entities in a web-space, comprising:
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identifying a first set of neighboring entities having one degree of separation from a central entity, each of the first set of entities have a relationship with the central entity;
wherein the relationship is one of a plurality of types;determining a set of relative probabilities corresponding to a likelihood of a user associated with the central entity to browse to each of the first set of entities, the set of relative probabilities to be determined based on a type of relationship between each of the first set of entities and the central entity; computing a set of absolute probabilities by normalizing the set of relative probabilities such that the sum of the absolute probabilities of the user associated with the central entity to browse to each of the first set of entities is substantially one; wherein the proximity between the central entity and each of the first set of entities is proportional to a corresponding absolute probability of the set of absolute probabilities. - View Dependent Claims (38, 39, 40, 41, 42, 43, 44, 45)
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46. A system, comprising:
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a model analyzer module to receive a model profile from an advertiser, the model profile represents a desired set of user characteristics of a model user specified by the advertiser; a parser module communicatively coupled to the model analyzer module, when, in operation, the parser module establishes a communication session with the model analyzer and parses the model profile provided by the model analyzer module to obtain a first set of model user metadata associated with the desired set of user characteristics; a user database to store a set of user metadata of a semantic user profile of a user; a comparison module communicatively coupled to the user database and the parser module, when in operation, the comparison module establishes a communication session with the parser module to retrieve the model user metadata and to compare model user metadata of the set of model user metadata with user metadata of a set of user metadata of a semantic user profile of a user; and a matching module communicatively coupled to the comparison module to generate a correlation index to indicate a degree of correlation between the model profile and the semantic user profile.
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47. A system for generating a semantic user profile, comprising:
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a communications module, when, in operation, establishes a communication session with a user to receive user input; a tracking module for tracking a set of user activity; a metadata generator module communicatively coupled to the tracking module, when, in operation, the metadata generator module identifies a set of context-independent user metadata for generating a context-independent semantic user profile; wherein, when, in operation, the metadata generator module identifies a set of context-dependent user metadata for generating a context-dependent semantic user profile; a timing module communicatively coupled to the user tracking module, when, in operation, the timing module establishes a communication session with the user tracking module to track an amount of time user activity is being recorded; wherein, when, in operation, the metadata generator module identifies a set of temporal user metadata for generating a temporal semantic user profile; and a profile generator engine communicatively coupled to the metadata generator module for generating the semantic user profile from at least one of the context-independent semantic user profile, the context-dependent semantic user profile, and the temporal semantic user profile.
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48. A system for semantic advertising, comprising:
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means for, receiving a model profile from an advertiser, the model profile represents a desired set of user characteristics of a model user specified by the advertiser; means for, parsing the model profile to obtain a first set of model user metadata associated with the ideal set of user characteristics; means for, comparing model user metadata of the first set of model user metadata with user metadata of a set of user metadata of a semantic user profile of a user; and means for, generating a correlation index to indicate a degree of correlation between the model profile and the semantic user profile.
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49. A method of optimized targeted advertising based on semantic user profiles, comprising:
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receiving a model profile from an advertiser, the model profile represents an ideal set of user characteristics of a model user to whom promotional content is to be presented; generating a set of semantic user profiles for each of a set of users; comparing the model profile and the set of semantic user profiles; generating a set of correlation index for indicating the degree of correlation between the model user and the set of users; and identifying a sub-set of the set of users as candidates to whom the promotional content is to be presented.
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Specification