Content navigation service

• US 7,689,556 B2
• Filed: 01/31/2005
• Issued: 03/30/2010
• Est. Priority Date: 01/31/2005
• Status: Active Grant

• Current Assignee: Orange S.A.
• Original Assignee: Orange S.A.
• Inventors: Garg, Shishir, Goswami, Amit
• Primary Examiner(s): Rones; Charles
• Assistant Examiner(s): Hotelling; Harold A
• Application Number:
  US11/045,115
• Publication Number:
  US 20060173838A1
• Time in Patent Office: 1,884 Days
• Field of Search: None
• US Class Current: 707/765
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A system, method, and computer program product for presenting items within a list of items based on an individual user profile, a social network of friends of the user or a mood of the user. The system generates the individual profile of the user, determines passive friends of the user from the social network of the user and also determines the mood of the user. The user has a choice to receive an ordered list of items based on the individual user profile, the social network or the mood of the user.

Claims

1. A computer program product storing instructions for execution on a computer system, which when executed by the computer system, causes the computer system to perform a method, comprising:

calculating an intimacy score for each passive friend of a user, the intimacy score being determined based upon a determined correspondence in interests;

generating a social network of passive friends of the user based on the intimacy score of each passive friend;

calculating a weighted score for each item from a list of items based on the social network of the user, and based on a generated ontology of the user, the ontology being established based on relationships between the list of items and each passive friend of the user; and

presenting the items of the list based on the calculated scores of the items, wherein the calculating the intimacy score further comprises,

identifying active friends of the user based upon an interaction history, to determine the passive friends of the user and creating item databases for the user and the passive friends, each data base including a same plurality of categories of characteristics for each item from the list of items,

incrementally increasing a value associated with each characteristic of an item (i) in the database for the user when the user selects the characteristic and (ii) in the database for the passive friend when the passive friend selects the characteristic,

assigning a weight to each characteristic of an item that is proportional to the value of the characteristic,

calculating an index for each characteristic of the item such that the index is a difference between the value of the characteristic for the user and the value of the characteristic for the passive friend,

calculating a ratio between the weight for each characteristic of the item and the corresponding index, and

summing the calculated ratios for all the characteristics of an item and for all the items from the list of items to determine the intimacy score between the user and each of the passive friends.

2. The computer program product according to claim 1, wherein the calculating a score further comprises:

rating items from the list of items by the passive friends from the social network;

assigning an item index for each item from the list of items based on ontologies of the passive friends from the social network;

calculating a ratio, for each passive friend from the social network of the user, between the rating and the item index corresponding to each item; and

summing the calculated ratios for all the passive friends from the social network of the user to determine the score of the item.

3. A computer-implemented method of determining a list of items on a computer, comprising:

calculating an intimacy score for each passive friend of a user, the intimacy score being determined based upon a determined correspondence in interests;

generating a social network of passive friends of the user based on the intimacy score of each passive friend;

calculating a weighted score for each item from a list of items based on the social network of the user, and based on a generated ontology of the user, the ontology being established based on relationships between the list of items and each passive friend of the user; and

presenting the items of the list based on the calculated scores of the items, wherein the calculating the intimacy score further comprises,

identifying active friends of the user based upon an interaction history, to determine the passive friends of the user and creating item databases for the user and the passive friends, each data base including a same plurality of categories of characteristics for each item from the list of items,

incrementally increasing a value associated with each characteristic of an item (i) in the database for the user when the user selects the characteristic and (ii) in the database for the passive friend when the passive friend selects the characteristic,

assigning a weight to each characteristic of an item that is proportional to the value of the characteristic,

calculating an index for each characteristic of the item such that the index is a difference between the value of the characteristic for the user and the value of the characteristic for the passive friend,

calculating a ratio between the weight for each characteristic of the item and the corresponding index, and

summing the calculated ratios for all the characteristics of an item and for all the items from the list of items to determine the intimacy score between the user and each of the passive friends.

4. The computer-implemented method according to claim 3, further comprising:

rating items from the list of items by the passive friends from the social network;

assigning an item index for each item from the list of items based on ontologies of the passive friends from the social network;

calculating a ratio, for each passive friend from the social network of the user, between the rating and the item index corresponding to each item; and

summing the calculated ratios for all the passive friends from the social network of the user to determine the score of the item.