Techniques for facilitating on-line contextual analysis and advertising

• US 20100138452A1
• Filed: 08/10/2007
• Published: 06/03/2010
• Est. Priority Date: 04/03/2006
• Status: Abandoned Application

• Current Assignee: Amobee, Inc. (Nexxen International Ltd.)
• Original Assignee: Kontera Technologies Incorporated (Nexxen International Ltd.)
• Inventors: Brickner, Itai, Henkin, Assaf, Shaham, Yoav, Klein, Daniel, Grenager, Trond
• Application Number:
  US11/891,435
• Publication Number:
  US 20100138452A1
• Time in Patent Office: Days
• US Class Current: 707/803
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0256 User search

Abstract

Various techniques are disclosed for facilitating on-line contextual analysis and/or advertising operations implemented in a computer network. According to some embodiments, various aspects may be used for enabling advertisers to provide contextual advertising promotions to end-users based upon real-time analysis of web page content which may be served to an end-user'"'"'s computer system. In at least one embodiment, the information obtained from the real-time analysis may be used to select, in real-time, contextually relevant information, advertisements, and/or other content which may then be displayed to the end-user, for example, via real-time insertion of textual markup objects and/or dynamic content. According to specific embodiments, various operations may be performed for adapting or modifying a conventional context-based advertising systems to improve various features such as, for example, ad relevance estimation, click-through rate estimation, advertisement selection and layout, balancing exploration and exploitation, etc.

Claims

1. A system for facilitating on-line contextual advertising operations implemented in a computer network, the system comprising:

an estimation engine adapted to generate EMV information relating to estimates of Expected Monitory Values (EMV) based on specified criteria, said specified criteria including click through rate (CTR) estimation information;

a relevance engine adapted to generate relevance information relating to relevance criteria between a specified page or document and at least one specified ad;

a layout engine adapted to generate ad ranking information for one or more of the at least one specified ads using the relevance information and EMV information;

a data analysis engine adapted to analyze historical information including user behavior information and advertising-related information; and

an exploration engine adapted to explore the use of selected keywords and ads in order for the purpose of improving EMV estimation.

2. A method for facilitating on-line contextual advertising operations implemented in a computer network, the method comprising:

identifying a first page for contextual ad analysis;

generating page classifier data using content associated with the first page;

identifying a first group of keywords on the page as being candidates for ad markup/highlighting;

identifying one or more potential ads for selected keywords of the first group of keywords;

generating ad classifier data for each of the identified ads using at least one criteria selected from a group consisting of;

ad content, meta data, and content of the ad'"'"'s landing URL;

generating a relevance score for each of the selected ads, wherein the relevance score indicates the degree of relevance between a given ad and the content of the identified page;

generating a ranking value for each selected ad based on the ad'"'"'s associated relevance score and associated EVM estimate; and

selecting specific keywords for markup/highlighting using at least the ad ranking values.

3. A system for facilitating on-line contextual advertising operations implemented in a computer network, the system comprising:

means for identifying a first page for contextual ad analysis;

means for generating page classifier data using content associated with the first page;

means for identifying a first group of keywords on the page as being candidates for ad markup/highlighting;

means for identifying one or more potential ads for selected keywords of the first group of keywords;

means for generating ad classifier data for each of the identified ads using at least one criteria selected from a group consisting of;

ad content, meta data, and content of the ad'"'"'s landing URL;

means for generating a relevance score for each of the selected ads, wherein the relevance score indicates the degree of relevance between a given ad and the content of the identified page;

means for generating a ranking value for each selected ad based on the ad'"'"'s associated relevance score and associated EVM estimate; and

means for selecting specific keywords for markup/highlighting using at least the ad ranking values.