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Method for Automatically Detecting Important locations in a User’s Life for Transmitting Personalized Content

IP.com Disclosure Number: IPCOM000239721D
Publication Date: 2014-Nov-27
Document File: 2 page(s) / 32K

Publishing Venue

The IP.com Prior Art Database

Related People

Frank Bentley: INVENTOR [+5]

Abstract

A method is disclosed for automatically detecting important locations in a user’s life for transmitting personalized content. The method automatically identifies the most important locations in a user’s life based on analysis of one or more of, but not limited to, phonebook data of the user and / or contacts of the user, social network data of the user and / or contacts of the user, geographical IP history and location data extracted from search history / application interaction.

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Method for Automatically Detecting Important locations in a User’s Life for Transmitting Personalized Content

Abstract

A method is disclosed for automatically detecting important locations in a user’s life for transmitting personalized content.  The method automatically identifies the most important locations in a user’s life based on analysis of one or more of, but not limited to, phonebook data of the user and / or contacts of the user, social network data of the user and / or contacts of the user, geographical IP history and location data extracted from search history / application interaction.

Description

Disclosed is a method for automatically detecting important locations in a user’s life for transmitting personalized content.  The personalized content may include, but is not limited to, news, sports, weather, events in respective locations and the like.  The important locations for the user can be place of birth, place of schooling, present location and the like. 

Different ways can be used or combined to automatically detect the most important locations of the user and transmit the content related to that location personally to the user.

In an implementation, the method detects important locations in a user’s life by observing area codes of contacts in the user’s phonebook.  Then, the method sums up the similar area codes based on cities / Designed Market Area (DMA) / regions.  The method uses the top regions to be the regions in which the user has the most number of phone contacts.

In another implementation, the method detects important locations in a user’s life by aggregating geographical information stored in address fields of contacts in the user’s phonebook.  Thereafter, the method finds the cities / regions that are higher in number, thereby indicating that they may be of interest to the user.

In yet another implementation, the method detects important locations in a user’s life by using geographical IP history of the user to find the places travelled by the user.  This can include tracking the number of location specific pages visited by the user, checking the places from where the user accessed different applications/websites.  The information can be analyzed to determine often visited cities or to determine a large amount of time spent by the u...