METHODS OF INFERRING USER PREFERENCES USING ONTOLOGIES
First Claim
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1. A method for recommending an object to a user comprising:
- defining an ontology as nodes in a directed acyclic graph each node representing a concept wherein general concepts are parent nodes and specific concepts are child nodes of the parent nodes;
using a propagating function to infer missing scores in the ontology;
calculating personalized scores of the concepts at the nodes of the ontology relative to a known user preference by propagating a score for the known user preference based on concepts of the known user preference, the propagating function, and the directed acyclic graph;
selecting a product because it is instance of a concept that has a high personalized score in the directed acyclic graph; and
recommending the product to the user.
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Abstract
Methods of inferring user preferences using ontologies use ontology structure based similarity and an inference mechanism in defining ontology filtering (OF). Items are recommended to users by identifying items that the users may prefer, but may not have been aware of. This is performed by computing personalized scores for concepts and selecting an instance having a highest score.
34 Citations
33 Claims
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1. A method for recommending an object to a user comprising:
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defining an ontology as nodes in a directed acyclic graph each node representing a concept wherein general concepts are parent nodes and specific concepts are child nodes of the parent nodes;
using a propagating function to infer missing scores in the ontology;
calculating personalized scores of the concepts at the nodes of the ontology relative to a known user preference by propagating a score for the known user preference based on concepts of the known user preference, the propagating function, and the directed acyclic graph;
selecting a product because it is instance of a concept that has a high personalized score in the directed acyclic graph; and
recommending the product to the user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method for recommending an object to a user comprising:
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defining an ontology as nodes in a directed acyclic graph each node representing a concept wherein general concepts are parent nodes and specific concepts are child nodes of the parent nodes;
wherein a propagating function can be computed from a ratio, or combination of a-priori scores at each node of the directed acyclic graph;
wherein an a-priori (APS) score can be calculated from the topology of concepts in the ontology;
calculating personalized scores of the concept at the nodes of the ontology relative to a known user preference by propagating a score for the known user preference based on concepts of the known user preference, the APSs, and the directed acyclic graph;
the propagating function; and
selecting a product because it contains a feature which is an instance of a concept that has a high personalized score at a node in the ontology. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23)
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24. A method of deriving a personal score of a concept by propagating a known personal score through an ontology comprising:
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defining an a-priori score for a first node of an ontology;
defining an a-priori score for a second node of the ontology;
determining a lowest common ancestor node in the ontology connecting the first node and the second node;
defining an a-priori score for the lowest common ancestor node;
calculating an inference from the first node to the second node using the a-priori score for the first node, the a-priori score for the second node, and the a-priori score for the lowest common ancestor node; and
calculating a personalized score for the second node by using the inference and the known personal score for the first node. - View Dependent Claims (25, 26, 27, 29, 30, 31, 32, 33)
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28. A program embodied in a computer readable medium that when executed causes a computing device to:
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define an a-priori score for a first node of an ontology;
define an a-priori score for a second node of the ontology;
determine a lowest common ancestor node in the ontology connecting the first node and the second node;
defining an a-priori score for the lowest common ancestor node;
calculate an inference from the first node to the second node using the a-priori score for the first node, the a-priori score for the second node, and the a-priori score for the lowest common ancestor node; and
calculate a personalized score for the second node by using the inference and the known personal score for the first node.
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Specification