Prior art

Prior Art Analysis for U.S. Patent 8,249,912

As of May 12, 2026, the following analysis details the most relevant prior art cited on the face of U.S. Patent 8,249,912 ("the '912 patent"). The analysis focuses on the potential for these references to anticipate the independent claims of the '912 patent under 35 U.S.C. § 102. Anticipation requires that a single prior art reference discloses each and every element of a claimed invention.

Key Prior Art References and Potential Anticipation

The following references appear most relevant to the subject matter of the '912 patent's claims.

1. U.S. Patent 6,134,531 A ("the '531 patent")

• Full Citation: US Patent 6,134,531 A, "Method and apparatus for correlating real-time audience feedback with segments of broadcast programs."
• Dates: Filed September 24, 1997; Issued October 17, 2000.
• Description: The '531 patent discloses a system for obtaining and processing real-time feedback from a broadcast audience. Viewers can provide feedback (e.g., positive or negative) via a remote device at any point during a program. The system correlates this feedback with the specific program "segment" being viewed at that moment. The aggregated data is used to generate reports showing audience reaction to different parts of the broadcast, which can be used to evaluate and modify program content.
• Potential Anticipation Analysis (§ 102):
  • Claim 1: The '531 patent appears to disclose several elements of Claim 1. It describes a computer system for detecting consumer actions ("real-time feedback") in connection with program content ("segments") and correlating them. It also teaches storing this information. However, it may not anticipate Claim 1 because it does not explicitly teach:
    1. Identifying elements within a "first episode of a serialized media program." The '531 patent speaks of generic "broadcast programs" and "segments" without the specific context of a serialized show.
    2. Using the correlation to generate "responsiveness probability values" that are then utilized to create "graphically represented" probabilities of future responsiveness. The '531 patent focuses on generating reports of past feedback rather than predictive probabilities for future use.
  • Claims 8 & 12: These claims are not anticipated by the '531 patent. The reference does not teach applying any calculated values to a second episode of a serialized program, nor does it disclose the crucial step of placing an advertisement within that second episode based on the analysis. Its focus is on evaluating existing program content, not on optimizing future ad placement.

2. U.S. Patent Application Publication 2005/0203803 A1 ("the '803 application")

• Full Citation: US 2005/0203803 A1, "Systems and methods for optimizing product placement in media."
• Dates: Filed March 12, 2004; Published September 15, 2005.
• Description: The '803 application describes a system for optimizing product placement by creating a "Product Placement A Priori Index" (PAPI). This index is calculated based on numerous variables, including the media type, genre, specific scene characteristics, and product characteristics. The system aims to predict the effectiveness of a potential product placement before it occurs by matching product attributes to media content attributes.
• Potential Anticipation Analysis (§ 102):
  • Claim 1: The '803 application discloses identifying program elements and product placement elements. However, it fails to anticipate Claim 1 because it does not teach key steps of the claimed method. The '803 application's PAPI is a predictive index based on pre-defined attributes, not on a correlation with actual, detected consumer actions ("consumer media reviewing actions"). Therefore, it does not disclose the steps of detecting and storing viewer actions and then correlating them with program elements to derive probability values.
  • Claims 8 & 12: For the same reasons, the '803 application does not anticipate these claims. It lacks the feedback loop of detecting real viewer responses to a first episode and using that specific data to predict responses and place ads in a second episode.

3. U.S. Patent 6,286,005 B1 ("the '005 patent")

• Full Citation: US Patent 6,286,005 B1, "Method and apparatus for analyzing data and advertising optimization."
• Dates: Filed March 11, 1998; Issued September 4, 2001.
• Description: The '005 patent describes a data mining system for optimizing advertising campaigns. It collects consumer data from various sources (e.g., transaction records, demographics) and media exposure data to build consumer profiles. It then uses these profiles to model consumer behavior and predict the likely response to different advertising strategies, allowing an advertiser to select an optimal media plan.
• Potential Anticipation Analysis (§ 102):
  • Claim 1: The '005 patent teaches a computer-based system for correlating consumer data with media exposure to optimize advertising. However, it does not appear to anticipate the specific method of Claim 1. The '005 patent's analysis is not tied to discrete "program elements" and "product placement elements" occurring at "specified time intervals" within a media program. Instead, it correlates broader media exposure (e.g., which ad was seen) with consumer profiles. It does not teach the granular, second-by-second content analysis and correlation at the core of the '912 patent's claims.
  • Claims 8 & 12: The '005 patent does not anticipate these claims as it does not disclose the specific context of analyzing a first episode of a serialized program to inform the placement of an advertisement in a second episode of that same program.

Summary of Findings

While the cited prior art references disclose general concepts of correlating media with consumer data for advertising purposes, none appear to fully anticipate the independent claims of the '912 patent. The key distinguishing features of the '912 patent claims, particularly in Claims 8 and 12, are the specific, iterative process applied to serialized media. This process involves:

1. Analyzing viewer responses to granular content elements in a first episode.
2. Calculating predictive "responsiveness probability values" from this analysis.
3. Applying these specific values to the content of a second episode of the same series to predict viewer behavior.
4. Actively placing an advertisement in that second episode at a precise time and within specific content determined by the prediction.

This complete, cyclical, and episode-specific method of ad placement for serialized content is not explicitly disclosed in any of the reviewed high-relevance prior art references.