System and methods for constructing personalized context-sensitive portal pages or views by analyzing patterns of users' information access activities

• US 20050278326A1
• Filed: 07/27/2005
• Published: 12/15/2005
• Est. Priority Date: 04/04/2002
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Anderson, Corin Ross, Horvitz, Eric
• Granted Patent: US 7,702,635 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/954 Navigation, e.g. using categorised browsing
• CPC Class Codes: G06Q 30/0256 User search
• CPC Class Codes: Y10S 707/99948 Application of database or data structure, e.g. distributed, multimedia, or image

Abstract

The present invention relates to a system and methodology to assist users with data access activities and that includes such activities as routine web browsing and/or data access applications. A coalesced display or montage of aggregated information is provided that is focused from a plurality of sources to achieve substantially one-button access to user'"'"'s desired web or data source information/destinations in order to mitigate efforts in retrieving and viewing such information. Past web or other type data access patterns can be mined to predict future browsing sites or desired access locations. A system is provided that builds personalized web portals for associated users based on models mined from past data access patterns. The portals can provide links to web resources as well as embed content from distal (remote) pages or sites producing a montage of web or other type data content. Automated topic classification is employed to create multiple topic-centric views that can be invoked by a user.

Claims

1. A method for distinguishing for learning purposes of whether access to a web page is performed by a user or performed via an automated refresh, comprising:

computing a statistical predictive model of a user'"'"'s web page revisit interval;

and using inferred intervals to identify an automated refresh.

2. The method of 1, the method for distinguishing automated refresh and user activity, further comprises:

comparing the interval since the user'"'"'s last visit with a statistical mode of a probability distribution of revisit intervals for a respective URL; and

discarding accesses within a tolerance of the statistical mode.