System and Method for an Electronic Product Advisor

• US 20120035981A1
• Filed: 10/26/2011
• Published: 02/09/2012
• Est. Priority Date: 05/02/2005
• Status: Abandoned Application

• Current Assignee: CBS Interactive Inc. (Paramount Global (f/k/a ViacomCBS Inc.))
• Original Assignee: CBS Interactive Inc. (Paramount Global (f/k/a ViacomCBS Inc.))
• Inventors: Bedard, Scott, Kasavin, Greg, Andrus, Patrick Cashman
• Application Number:
  US13/282,313
• Publication Number:
  US 20120035981A1
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9536 Search customisation based on social or collaborative filtering
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0217 involving input on products or services in exchange for incentives or rewards
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0251 Targeted advertisements
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/0623 Item investigation
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

A system and method operates on a client device and acquires a suspect list of user products based on information derived from the client device. The system normalizes the list, and the user confirms the accuracy of the product list. The user product list is sent to a server where the user product list is compared to other lists using collaborative filtering techniques. The collaborative filtering techniques determine products of interest for the use and the level of interest of the user. The system computes a similarity measure based upon the number of similar products that match the user'"'"'s product list and rankings provided by the user and others. Demographic and behavioral data may also be used in performing the comparison and the similarity measure. The system acquires editorial rankings of products from other users and provides a ranked list of recommended products based upon the editorial rankings.

Claims

1. A computer implemented method for establishing and maintaining an online community of users of products, the method comprising:

via an Internet-compatible communications interface, receiving data regarding a plurality of users, and receiving data regarding at least one user-owned product, the data regarding at least one user-owned product including a price of the product;

associating at least one user-owned product having received price data with at least one product user;

estimating the value of at least one associated product, at least in part as a function of received price data; and

via the Internet-compatible communications interface, providing functionality allowing each profiled user to search and retrieve an estimated used value of a product, including the cumulative used value of a subset of products associated with the user and having estimated prices.