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

• US 20050267869A1
• Filed: 07/27/2005
• Published: 12/01/2005
• 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 8,020,111 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 data access model, comprising:

a log that collects past web data access patterns;

a context component to record at least one context relating to the past web data access patterns; and

a predictive component to determine web future data access patterns based at least in part on the past web data access patterns and the recorded context.

2. The model of claim 1, the predictive component determines a probability of information value to a user given evidence of the user'"'"'s interest in at least one of a potential site and topic.

3. The model of claim 2, the probability formulated as:

Pr(Information Value|E₁,E₂, . . . E_J);

wherein Pr is the probability, Information Value relates to an importance of the site and topic to the user given evidence E relating to attributes of information importance, and J being an integer.

4. The model of claim 3, the evidence including at least one of web pages visited, how much time users spend observing the web pages, how many links the user followed from the web pages, higher-level topic of the web pages viewed, interactivity with the web pages and a consideration of navigation efforts of a user.

5. The model of claim 1, further comprising a classifier to perform automatic topic classification, the classifier employing at least one of a Support Vector Machine (SVM), a Naive Bayes, a Bayes Net, a decision tree, a similarity-based, and a vector-based learning algorithm.

6. A computer-readable medium having computer-executable instructions stored thereon to execute the model of claim 1.

7. A system for building a montage, comprising:

means for logging past data access;

means for logging context information in accordance with the data access;

means for building a model to predict future data access;

means for mining at least one of the past data access and the context information; and

means for selecting data based on the context information.