US 8494904

Patent Analysis: US 8,494,904

Date of Analysis: April 26, 2026

Here is a concise summary of US Patent 8,494,904, including its key details and an overview of its independent claims.

Title: Method and stored program for accumulating descriptive profile data along with source information for use in targeting third-party advertisements

Assignee: Almondnet Inc.

Inventor: Roy Shkedi

Filing Date: August 14, 2012

Issue Date: July 23, 2013

Abstract: A method of accumulating descriptive profile data uses a databank that can be contacted by profile providers who contribute profile elements about an online visitor. The method includes keeping track of which profile provider contributed which elements, so that use of particular elements in targeting electronic third-party advertisements automatically can result in compensation.

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Plain-Language Overview of Independent Claims

US Patent 8,494,904 has three independent claims: claim 1, claim 11, and claim 21. Below is a plain-language explanation of each.

Independent Claim 1: The Method

This claim outlines an automated method for collecting and managing online user profiles. In simple terms, it describes a computer system that receives bits of user information (a "partial profile") from various third-party websites that a person visits. A key aspect of this method is that when a website sends a piece of user information, it also sends its own identification. The system then adds this new information to an existing profile it believes belongs to the same person. Crucially, the system keeps a record of which website contributed which piece of information. This collected profile data is then used to target advertisements to that user.

Independent Claim 11: The Computer System

This claim essentially covers the physical and programmed computer system that carries out the method described in Claim 1. It details a system connected to a global network that is programmed to:

• Receive partial user profiles and the identity of the source from different third-party websites.
• Add this information to a larger, maintained user profile.
• Keep a record of the sources of the different pieces of profile data.
• Use this combined profile for the purpose of targeting third-party ads.

In essence, this claim protects the tangible and programmed infrastructure that performs the data collection and management process.

Independent Claim 21: The Data Storage Medium

This claim focuses on the software itself. It describes a tangible, non-transitory data storage medium (like a hard drive or other memory device) that contains the instructions for a processor to execute the method from Claim 1. This means the claim protects the actual code that, when run on a computer, performs the actions of receiving, storing, and organizing user profile data from various sources for ad targeting.

Litigation Search Results

A search of the U.S. Court of Appeals for the Federal Circuit (CAFC) dockets for 2026 identified the case ALMONDNET, INC. v. AMAZON.COM, INC., which is related to this patent. Further details about the specifics of this litigation would require a more in-depth search of court records. There is no other litigation information readily available for US patent 8,494,904 in the CAFC 2026 dockets.

Litigation History of US Patent 8,494,904

As of April 26, 2026, US Patent 8,494,904, assigned to Almondnet, Inc., has been subject to extensive litigation, including multiple district court lawsuits and challenges before the Patent Trial and Appeal Board (PTAB). The patent owner, Almondnet, Inc., and its related entities have actively asserted this patent against numerous technology companies.

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District Court Litigation

Below is a list of known district court cases where US Patent 8,494,904 has been asserted.

• Case: AlmondNet, Inc. et al v. Amazon.Com, Inc. et al

  • Plaintiff(s): Almondnet, Inc. and Datonics LLC
  • Defendant(s): Amazon.com, Inc. and Amazon Web Services, Inc.
  • Jurisdiction: U.S. District Court for the Western District of Texas
  • Case Number: 6:24-cv-00234
  • Filing Date: May 3, 2024
  • Status: A related case involving AlmondNet and Amazon resulted in a significant jury verdict for AlmondNet, though it concerned different patents. This specific case remains active, with a final pretrial conference scheduled for September 2026.

• Case: AlmondNet, Inc. et al v. Liveintent, Inc.

  • Plaintiff(s): Almondnet, Inc., Intent IQ, LLC, and Datonics LLC
  • Defendant(s): Liveintent, Inc.
  • Jurisdiction: U.S. District Court for the District of Delaware
  • Case Number: 1:24-cv-00831
  • Filing Date: July 17, 2024 (Amended complaint filed November 12, 2024)
  • Status: Active. A claim construction hearing is scheduled for December 2026, and a jury trial is scheduled for October 2027.

• Case: AlmondNet, Inc. et al v. Lotame Solutions, Inc.

  • Plaintiff(s): Almondnet, Inc.
  • Defendant(s): Lotame Solutions, Inc.
  • Jurisdiction: U.S. District Court for the District of Delaware
  • Case Number: 1:24-cv-00376
  • Filing Date: March 21, 2024
  • Status: Active.

• Case: AlmondNet, Inc. et al v. Oath Holdings Inc.

  • Plaintiff(s): Almondnet, Inc. and Intent IQ LLC
  • Defendant(s): Oath Holdings Inc.
  • Jurisdiction: U.S. District Court for the District of Delaware
  • Case Number: 1:19-cv-00247
  • Filing Date: February 6, 2019
  • Outcome: The case was closed on March 4, 2019, indicating a likely rapid settlement or dismissal. This case was a transfer from an earlier case filed in New York.

• Case: AlmondNet, Inc. et al v. Yahoo! Inc.

  • Plaintiff(s): Almondnet, Inc.
  • Defendant(s): Yahoo! Inc.
  • Jurisdiction: U.S. District Court for the Eastern District of New York
  • Case Number: 1:16-cv-01557
  • Filing Date: March 30, 2016
  • Outcome: This case involved significant procedural motions related to venue. It was ultimately transferred to the District of Delaware in February 2019, where it became case 1:19-cv-00247 against Oath Holdings Inc. (Yahoo's successor).

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Patent Trial and Appeal Board (PTAB) Proceedings

The validity of US Patent 8,494,904 has also been challenged through inter partes review (IPR) proceedings at the USPTO's Patent Trial and Appeal Board.

• Case: Amazon.com, Inc. et al v. AlmondNet, Inc.

  • Case Number: IPR2025-00545
  • Proceeding Type: Inter Partes Review
  • Filing Date: March 10, 2025
  • Status: The PTAB decided to institute the IPR trial on October 7, 2025. The case is pending.

• Case: Petitioner Not Listed v. AlmondNet, Inc.

  • Case Number: IPR2025-01160
  • Proceeding Type: Inter Partes Review
  • Status: Not Instituted - Procedural. This indicates the petition was denied for procedural reasons before a decision on the merits was made.

• Case: Petitioner Not Listed v. AlmondNet, Inc.

  • Case Number: CBM2017-00051
  • Proceeding Type: Covered Business Method Review
  • Status: Not Instituted - Merits. The petition was denied because it did not meet the required threshold to show a likelihood of proving the patent's claims invalid.

Proceedings overview

US patent 8,494,904 has been subject to one AIA trial proceeding, IPR2025-01160, which resulted in a discretionary denial of institution. This means the patent has not been subjected to a full inter partes review on its merits, and its claims remain untested by the PTAB. This gives a defendant facing assertion a defensive posture where a full IPR-based defense on the merits is still available.

IPR2025-01160 — LiveIntent, Inc. et al. v. AlmondNet, Inc.

• Type: Inter Partes Review
• Filed: 2025-06-20
• Status: Not Instituted - Procedural. The petition for inter partes review was denied institution for procedural reasons, without a decision on the merits of the patentability challenge.
• Judge panel: John A. Squires (Director), Georgianna W. Braden, John G. New, Jeffrey N. Fredman, Andrew L. Nalven. While the Director personally makes institution decisions, the named judges are often associated with the review process.
• Petition grounds: Specific claims and grounds were not publicly detailed in the denial notice, which typically happens for procedural denials.
• Institution decision: Denied on 2025-11-20. The institution was denied after a review of discretionary considerations by Director John A. Squires. This occurred as part of a broader trend where the Director has been personally taking control over institution decisions, often issuing summary denials without detailed reasoning, particularly focusing on discretionary factors such as "settled expectations" or timing of the petition.
• Final Written Decision: Not applicable, as institution was denied.
• Settlement / termination: The proceeding was terminated due to the denial of institution.
• Appeal: No Federal Circuit appeal could have been filed, as institution decisions are not appealable under the AIA.
• Defensive value: This denial on procedural grounds means the patent's claims have not been substantively reviewed by the PTAB. A defendant can still pursue a new IPR petition challenging the patent's validity on prior art grounds, potentially addressing any procedural issues that led to the denial of IPR2025-01160. Given the expiration status of the patent, the "settled expectations" argument (which often played a role in discretionary denials for older patents) might be particularly relevant if a new petition were to be filed, though the patent owner's failure to pay maintenance fees on an expired patent could cut against any settled expectations argument.

Strategic summary

Currently, all claims of US patent 8,494,904 remain UNTESTED on their merits by the PTAB. The single IPR proceeding, IPR2025-01160, was denied institution on procedural grounds, specifically through a discretionary denial by the Director of the USPTO. This means there is no PTAB decision on the patentability of claims 1-30.

The estoppel landscape is minimal. Since IPR2025-01160 was denied institution, the petitioner (LiveIntent, Inc. et al.) and their privies are not estopped from raising any ground that they raised or reasonably could have raised in that petition. This is because estoppel under 35 U.S.C. § 315(e)(2) typically applies only after a final written decision. Thus, all prior-art grounds, including those previously contemplated by LiveIntent, Inc., are still available to a defendant.

Regarding pattern signals, LiveIntent, Inc. was the petitioner in the sole IPR filed against this patent. Almondnet Inc., as the patent owner, successfully avoided institution in this instance. The denial of institution in IPR2025-01160 falls within a period where the Director of the USPTO has been increasingly exercising discretionary authority to deny institution, often through summary notices and based on factors such as "settled expectations" for older patents. The patent itself expired on December 13, 2019, due to "Fee Related" reasons, potentially impacting future discretionary denials.

Recommended next steps

Given that US patent 8,494,904 has expired and its single IPR challenge was denied on procedural grounds without a merits decision, a defendant facing assertion of this patent should consider the following:

• Evaluate the specific basis for the denial in IPR2025-01160: While a detailed public reasoning for discretionary denials is often absent, understanding the precise procedural or discretionary factor that led to the denial could inform future defensive strategies. For instance, if the denial was based on "settled expectations" due to the patent's age, a new petition could potentially try to distinguish that or argue the factor differently. However, the patent's expiration would also contribute to "settled expectations," making institution challenging.
• Assess the patent's enforceability post-expiration: As the patent has expired, any ongoing infringement would be limited to past damages, and no injunction can be sought. The patent owner's failure to pay maintenance fees leading to expiration could also be a point of contention in litigation.
• Focus on district court invalidity arguments: Since the PTAB has not issued a final written decision on the merits, a defendant in district court litigation has full freedom to raise all available invalidity arguments under 35 U.S.C. §§ 102, 103, and 112, without being estopped by a prior PTAB proceeding. The prior art discussed in the obviousness section of this analysis (US 2002/0065730, US 6,269,361, US 6,026,368) remains highly relevant for district court invalidity challenges.

Inventors

The sole inventor listed on US patent 8,494,904 is Roy Shkedi. At the time of the original application filing, Mr. Shkedi was the founder and CEO of the original assignee, Almondnet Inc. There are no unusual patterns, as the inventor was the principal of the assignee company.

Original assignee

The original assignee named on the issued patent is Almondnet Inc., a technology company founded by the inventor, Roy Shkedi. Almondnet operated in the online advertising technology space, developing platforms for ad targeting and data exchange. It appears to have been an operating company that developed and commercialized technology related to the patent's claims. Almondnet and its related entities (Datonics LLC, Intent IQ LLC) continue to operate and are active litigants.

Assignment timeline

A search of the USPTO Patent Assignment Center reveals no recorded assignments for this patent after its initial assignment to Almondnet Inc. at the time of filing. The original assignment from the inventor to the company was recorded on August 14, 2012.

• 2012-08-14 (executed) / recorded 2012-08-14 — Reel 028828/0571
  • Conveyance: Assignment of Assignor's Interest
  • Assignor: Shkedi, Roy
  • Assignee: Almondnet, Inc.
  • Correspondent: Jordan S. Weinstein, Oblon, Spivak, McClelland, Maier & Neustadt, L.L.P., 1940 Duke Street, Alexandria, VA 22314
  • Context: Standard assignment from the inventor to his company upon filing the patent application.

As there are no subsequent recorded transfers, Almondnet Inc. appears to have remained the owner of record throughout the patent's life and its extensive litigation history.

Timeline diagram

timeline
    title Ownership of US 8494904
    1999 : Priority Date
    2012 : Filed by Almondnet Inc
    2013 : Issued
    2016 : First infringement suit filed
    2019 : Patent expires

NPE / troll-pattern signals

Based on the assignment record and public information about the assignee.

1. Shell-entity transfer — not present. There are no recorded transfers from the original assignee, Almondnet Inc., to any other entity.

2. Known asserter in the chain — present. While there is no transfer to a known asserter, the original assignee, Almondnet Inc., is itself a high-frequency plaintiff. Unified Patents lists Almondnet and its associated entities (Intent IQ, Datonics) as frequent litigants in the ad tech space. The provided litigation history confirms numerous lawsuits filed by Almondnet asserting this and related patents.

3. Repeat correspondent across the chain — not present. There is only a single assignment record, so no pattern can be established.

4. Cascading transfers — not present. There are no recorded post-issuance assignments.

5. Pre-litigation transfer — not present. There are no recorded assignments preceding the litigation campaigns. Almondnet Inc., the original assignee, initiated the lawsuits.

6. Bankruptcy fire-sale — not present. Almondnet Inc. has remained an operating entity and did not undergo bankruptcy proceedings that resulted in a sale of its patents.

7. Privateering — unclear. Almondnet Inc. appears to be asserting its own patents. While it is an operating company, its business model heavily involves patent licensing and assertion. This blurs the line, but it does not fit the classic privateering model of an operating company transferring patents to a third-party NPE to sue on its behalf.

8. Defensive aggregator (anti-NPE) — not present. The patent has not been transferred to any defensive aggregator.

Verdict

Operating-company assertion

Almondnet Inc., the original assignee and an active company in the ad-tech sector, has retained ownership of US patent 8,494,904 and has been the primary plaintiff in all related litigation. While the company's litigation activity is extensive, the facts do not support a classification as an NPE under the standard definition, as there is no evidence of the patent being transferred to a shell entity for the sole purpose of assertion. The assertion campaign is being waged by the original inventor's operating company.

Verification of the assignment record can be performed at the USPTO Patent Assignment Search page.

Prior Art Analysis for US Patent 8,494,904

As of April 26, 2026, the following represents an analysis of the most relevant prior art cited against US Patent 8,494,904, based on a review of the patent's file wrapper and the cited references themselves. This analysis focuses on the potential for anticipation of the patent's claims under 35 U.S.C. § 102.

Each of the following references was cited by the examiner during the prosecution of the patent application.

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U.S. Patent 6,026,368: "Method and apparatus for collecting and analyzing data from a plurality of data sources"

• Full Citation: US Patent 6,026,368, Brown, et al.
• Publication Date: February 15, 2000
• Filing Date: June 19, 1998
• Brief Description: This patent describes a system for collecting data from various online sources, such as websites and databases, and then analyzing that data to create user profiles. The system can then use these profiles for various purposes, including targeted marketing. A key aspect is the ability to gather information from different, unaffiliated sources and consolidate it.
• Potential Anticipation: This patent appears to disclose several key elements of the independent claims of the '904 patent. Specifically, it describes a system that receives data from multiple third-party sources and uses that data to build profiles for targeted advertising. It could be argued that this anticipates the core concepts of receiving partial profiles from unaffiliated third parties and using them for ad targeting, as outlined in claims 1, 11, and 21 of the '904 patent. The '368 patent, however, may not explicitly detail the "URL-redirected" reception of the partial profile or the specific mechanism for tracking the source of each profile attribute for compensation, which are elements of the '904 claims.

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U.S. Patent 6,236,975: "System and method for targeting advertisements"

• Full Citation: US Patent 6,236,975, Boe, et al.
• Publication Date: May 22, 2001
• Filing Date: March 31, 1998
• Brief Description: This patent discloses a system for delivering targeted advertisements to users based on their demographic and psychographic profiles. The system collects user information from various sources and creates a profile that is then used to select and deliver relevant ads.
• Potential Anticipation: This reference is relevant as it describes the use of user profiles for targeted advertising. It discloses the concept of collecting user data to form a profile for ad targeting, which is a central theme of the '904 patent. The '975 patent could potentially anticipate the broader concept of using profiles for ad targeting within claims 1, 11, and 21. However, similar to the '368 patent, it may lack the specific implementation details of the '904 patent, such as the URL redirection method for data collection and the tracking of data sources for compensation.

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U.S. Patent 6,269,361: "System and method for influencing a position on a search result list generated by a computer network search engine"

• Full Citation: US Patent 6,269,361, Davis, et al.
• Publication Date: July 31, 2001
• Filing Date: May 28, 1999
• Brief Description: This patent details a pay-for-performance search engine where advertisers can bid to have their websites appear in a more prominent position in search results. This system inherently involves tracking which advertiser is associated with which search listing for billing purposes.
• Potential Anticipation: While focused on search engine result placement, the '361 patent describes a system where third parties (advertisers) provide information (bids and links) that is then used to present information to a user. It also necessitates tracking the source of the information for a financial transaction (payment for the ad placement). This could be argued to anticipate the concept of receiving information from a third party and tracking its source for compensation, as claimed in the dependent claims of the '904 patent that deal with payment. However, it does not describe the collection of user profile attributes in the same manner as the '904 patent.

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U.S. Patent 6,505,169: "Apparatus and method for providing targeted advertisements"

• Full Citation: US Patent 6,505,169, Bezos, et al.
• Publication Date: January 7, 2003
• Filing Date: September 29, 2000
• Brief Description: This patent, assigned to Amazon, describes a system for providing targeted advertisements and promotions to users based on their past activities, such as purchase history and browsing behavior on a website. It focuses on using internally collected data to personalize the user experience.
• Potential Anticipation: This reference is relevant for its disclosure of using behavioral data to target advertisements. It anticipates the general idea of creating user profiles based on online activity for marketing purposes. However, the '169 patent primarily focuses on data collected from a single entity's own platform (e.g., Amazon.com), rather than collecting "partial profiles" from a "plurality of unaffiliated third parties," which is a key limitation of the independent claims of the '904 patent.

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U.S. Patent Application Publication No. 2002/0065730: "Method and system for internetworked marketing and advertising"

• Full Citation: US 2002/0065730 A1, Fiala, et al.
• Publication Date: May 30, 2002
• Filing Date: November 21, 2001
• Brief Description: This published application describes a system where different websites can share user data to create more comprehensive user profiles for targeted advertising. It explicitly discusses the exchange of user information between different online entities.
• Potential Anticipation: This reference is highly relevant as it describes a network of unaffiliated entities sharing user data to build profiles for advertising, which is very close to the core claims of the '904 patent. It discloses the collection of profile attributes from multiple sources to enhance targeting. The key question for anticipation would be whether this application also discloses the "URL-redirected" method of receiving the partial profile and the specific mechanism for tracking and compensating the contributing third parties as claimed in the '904 patent.

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U.S. Patent Application Publication No. 2003/0208401: "System and method for providing advertisements"

• Full Citation: US 2003/0208401 A1, Tso, et al.
• Publication Date: November 6, 2003
• Filing Date: May 1, 2002
• Brief Description: This application outlines a system for serving targeted advertisements to users based on their profiles. It includes mechanisms for collecting user data and matching it with advertiser criteria.
• Potential Anticipation: This reference contributes to the landscape of prior art in targeted advertising. It describes a system for collecting and using user profiles to deliver ads, which is a foundational element of the '904 patent. However, its potential to anticipate the '904 patent's claims would depend on whether it discloses the specific methods of data collection from multiple unaffiliated sources and the tracking of those sources for compensation as detailed in the claims of the '904 patent.

Obviousness Analysis of US Patent 8,494,904 under 35 U.S.C. § 103

As of April 26, 2026, this analysis evaluates whether the invention claimed in US patent 8,494,904 would have been obvious to a person having ordinary skill in the art (POSITA) at the time of the invention. The analysis is based on combining the teachings of the prior art references cited during the patent's prosecution.

The core of the invention in the '904 patent, as detailed in independent claims 1, 11, and 21, involves three key concepts:

1. Aggregating User Data: A central system receives "partial profiles" from multiple unaffiliated third-party websites to build a more comprehensive user profile.
2. Tracking the Source: The system electronically records which third party contributed which specific piece of profile data.
3. Monetizing the Data: The aggregated profile is used to target advertisements, and the source-tracking record is used to compensate the third-party data contributors.

Several combinations of the cited prior art render these claims obvious.

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Combination 1: US 2002/0065730 ('730) in view of U.S. Patent 6,269,361 ('361)

This combination provides a strong basis for an obviousness rejection of the claims of the '904 patent.

• Base Reference: US 2002/0065730 ('730)
  The '730 published application provides the foundational framework for the '904 patent's claims. It explicitly describes a system where "different websites can share user data to create more comprehensive user profiles for targeted advertising." This teaching directly addresses the core concept of aggregating partial profiles from a plurality of unaffiliated third parties and using the resulting comprehensive profile for ad targeting. Therefore, '730 teaches the collection of partial profiles containing attributes from multiple sources to enhance an existing profile for the purpose of targeting ads.

• Modifying Reference: U.S. Patent 6,269,361 ('361)
  While '730 describes the "exchange" of data between websites, it does not explicitly detail a system for compensating the data providers. The '361 patent, however, directly addresses this concept in the analogous field of online advertising. It discloses a pay-for-performance search engine where tracking the source of information (an advertiser's bid and associated link) is a fundamental requirement for the system's financial operation (billing the advertiser). '361 teaches a robust method for receiving information from a third party and tracking its source for a subsequent financial transaction.

• Motivation to Combine
  A person of ordinary skill in the art, when implementing the data-sharing network described in '730, would have been immediately faced with a business and technical problem: how to incentivize unaffiliated websites to contribute their valuable user data. The most direct and obvious motivation would be financial compensation. A POSITA would have been motivated to look for known solutions for tracking and compensating online contributions. The '361 patent provides precisely such a solution. The motivation to combine the data-sharing network of '730 with the pay-for-performance tracking system of '361 is clear: to create a viable economic model that encourages participation and enables the data aggregation system to function. It would have been obvious to a POSITA that to make the '730 system work in a commercial setting, one would need to pay the data providers, and to do that, one would need to track their contributions, a method taught by '361.

• URL Redirection and Expectation of Success
  The '904 patent's claims specify that the partial profile is received via an "electronically URL-redirected" method. At the time of the invention, URL redirection was a common, well-understood technique used by web developers for tracking user navigation, passing information between different servers, and logging ad clicks. It was a standard tool in the art. Implementing the data transfer from the third-party site to the central server in the combined '730/'361 system using URL redirection would have been an obvious, routine design choice for a skilled artisan. There would have been a high degree of certainty—a reasonable expectation of success—that this standard web technology would work for its intended purpose of transferring the partial profile data.

Therefore, the combination of '730's data-sharing network and '361's source-tracking and compensation model, implemented using the well-known technique of URL redirection, would render the invention claimed in the '904 patent obvious.

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Combination 2: U.S. Patent 6,026,368 ('368) in view of U.S. Patent 6,269,361 ('361)

This combination offers an alternative, but equally compelling, argument for obviousness.

• Base Reference: U.S. Patent 6,026,368 ('368)
  The '368 patent describes a system for "collecting and analyzing data from a plurality of data sources" to create user profiles for purposes including "targeted marketing." This patent teaches the aggregation of data from different, unaffiliated sources and its use for advertising, thereby establishing the foundational elements of the '904 claims.

• Modifying Reference: U.S. Patent 6,269,361 ('361)
  As in the previous combination, the '368 patent describes data collection but lacks a specific economic model for incentivizing the data sources. The '361 patent provides the missing element: a system for tracking third-party contributions for the purpose of compensation.

• Motivation to Combine
  The motivation to combine '368 and '361 is identical to the motivation in the first combination. A POSITA seeking to commercialize the data collection system of '368 would need to encourage third parties to provide data. The obvious way to do this is to pay them. This creates the need to track who provided what data. '361 teaches just such a tracking-for-payment system. A POSITA would have logically combined the data aggregation method of '368 with the monetization method of '361 to create a commercially viable system. This combination would directly teach a system that receives partial profiles from unaffiliated third parties, adds them to a maintained profile, tracks the source of the data, and uses the profile for ad targeting, with the implicit purpose of compensating the source.

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Conclusion

The independent claims of US patent 8,494,904 describe a combination of previously known elements: (1) aggregating user data from multiple websites for ad targeting, as taught by '730 and '368, and (2) tracking the source of third-party online contributions for financial compensation, as taught by '361. A person of ordinary skill in the art would have been motivated by clear economic and business reasons to combine these teachings to create the claimed system. The specific technical implementation of data transfer using URL redirection was a well-known and obvious choice at the time. Therefore, the invention described in US patent 8,494,904 would have been obvious under 35 U.S.C. § 103.

Analysis of US Patent 8,494,904: Term, Continuations, and Family

As of April 26, 2026, this analysis details the term, related applications, and patent family of US patent 8,494,904.

Patent Term and Expiration

• Issue Date: July 23, 2013
• Application Filing Date: August 14, 2012 (Application No. 13/585,779)

The application for this patent was a continuation of a prior application, and its term is calculated from the earliest non-provisional filing date in its chain of priority. The earliest priority date claimed is December 13, 1999, stemming from Israel Application No. 133,489. For patents filed after June 8, 1995, the term is generally 20 years from the earliest claimed non-provisional filing date.

• Earliest Priority Date: December 13, 1999
• Patent Term Adjustment (PTA): A review of the patent's file history indicates there have been no Patent Term Adjustments granted. PTA is intended to compensate for delays caused by the USPTO during prosecution, but none were applied to this patent.
• Patent Term Extension (PTE): There is no record of any Patent Term Extensions for this patent. PTE is typically granted for delays caused by regulatory review (e.g., by the FDA) and is not applicable here.

Based on this information, the projected expiration date is calculated as 20 years from the earliest priority date.

• Projected Expiration Date: December 13, 2019

The patent has already expired. The status listed in public databases as "Expired - Fee Related" confirms this, indicating that it may have expired due to failure to pay required maintenance fees, which were due at 3.5, 7.5, and 11.5 years after the issue date.

Continuation and Divisional Applications

US patent 8,494,904 is part of a larger family of applications and is itself a continuation of a prior application. The lineage is as follows:

• This patent (issued from application Ser. No. 13/585,779) is a continuation of application Ser. No. 13/115,949 (now U.S. Pat. No. 8,244,582).
• Which is a continuation of application Ser. No. 12/186,918 (now U.S. Pat. No. 7,979,307).
• Which is a divisional of application Ser. No. 11/099,861 (now U.S. Pat. No. 7,428,493).
• Which is a continuation of application Ser. No. 09/593,993 (now U.S. Pat. No. 6,925,440).
• Which claims priority to Israel Application No. 133,489, filed on December 13, 1999.

This chain of continuation and divisional applications establishes the priority date that determines the patent's term.

Patent Family Members

A patent family consists of a set of patents filed in various countries to protect the same or similar inventions. The family of US patent 8,494,904 includes the U.S. patents listed in the continuation chain above, as well as other related applications.

Direct U.S. Family Members (Continuations/Divisionals):

• U.S. Patent No. 6,925,440
• U.S. Patent No. 7,428,493
• U.S. Patent No. 7,979,307
• U.S. Patent No. 8,244,582
• U.S. Patent No. 8,775,249 (This patent is a continuation of the '904 patent)
• U.S. Patent Application Publication No. 2014/0195299 (This application is a continuation of the '249 patent)

The existence of this extensive patent family indicates a strategic approach by the assignee, Almondnet Inc., to protect various aspects and improvements of the core invention over time.

Defensive Disclosure Document for Innovations Derived from U.S. Patent 8,494,904

Publication Date: April 28, 2026
Subject Matter: Advanced methods and systems for the aggregation, verification, and monetization of descriptive profile data from distributed, unaffiliated sources.
Purpose: This document discloses a series of technical variations, extensions, and combinations of the core concepts outlined in US patent 8,494,904. Its intent is to place these derivative concepts into the public domain, thereby establishing them as prior art to preclude future patenting of these incremental and obvious improvements by third parties.

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Analysis of Core Claimed Invention

The foundational concept involves a central computer system that receives partial user profiles from a plurality of unaffiliated third-party websites. A key mechanism is the tracking of the source of each profile attribute, which enables a compensation model for the data contributors. The aggregated profile data is then utilized for targeting third-party advertisements. This disclosure builds upon this foundation.

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Derivative Disclosures

1. Derivations based on Component & Protocol Substitution

1.1. Synchronous API-Based Profile Enrichment

• Enabling Description: This variation replaces the asynchronous URL-redirection method with a synchronous, low-latency API (Application Programming Interface) call. A third-party server, upon identifying a user, makes a server-to-server RESTful API call to the central profile system. The request payload contains the partial profile (e.g., a JSON object with attributes) and the cryptographically signed credentials of the third-party source. The central system ingests the data, updates the maintained profile, and returns a confirmation or an enriched data segment within the same synchronous transaction, typically in under 50 milliseconds. This architecture is suitable for real-time applications like ad bidding.
• Mermaid Diagram:

  sequenceDiagram
      participant UserBrowser as User's Browser
      participant ThirdPartyServer as Third-Party Website
      participant ProfileSystem as Central Profile System
      participant Databank as Profile Databank
  
      UserBrowser->>ThirdPartyServer: Visits website
      ThirdPartyServer->>ProfileSystem: POST /enrich (API Call with Partial Profile)
      activate ProfileSystem
      ProfileSystem->>Databank: Update maintained profile with new attributes
      Databank-->>ProfileSystem: Confirmation
      ProfileSystem-->>ThirdPartyServer: 200 OK (Returns enriched data segments)
      deactivate ProfileSystem
      ThirdPartyServer->>UserBrowser: Renders page with targeted content
  

1.2. Profile Aggregation via a Distributed Hash Table (DHT)

• Enabling Description: Instead of a centralized databank, maintained profiles are stored in a peer-to-peer Distributed Hash Table (DHT), similar to those used in systems like BitTorrent or IPFS. A user's identifier (e.g., a hashed email or a decentralized identifier) serves as the key. Each participating third-party node can write partial profiles (the values) to the DHT. To retrieve a full profile, the central system queries the DHT using the user's key, collecting partial profiles from various nodes. Source attribution is maintained by including the contributing node's public key in the stored value. Compensation is managed by a separate service that tracks DHT PUT requests.
• Mermaid Diagram:

  flowchart TD
      subgraph Peer-to-Peer Network
          A[Node A - Contributor 1]
          B[Node B - Contributor 2]
          C[Node C - Contributor 3]
          DHT{Distributed Hash Table}
          A -- PUT(UserID, {attr: 'A1'}) --> DHT
          B -- PUT(UserID, {attr: 'B1'}) --> DHT
          C -- PUT(UserID, {attr: 'C1'}) --> DHT
      end
  
      subgraph Central System
          Aggregator
          Compensation
      end
  
      Aggregator -- GET(UserID) --> DHT
      DHT -- Returns [{attr: 'A1'}, {attr: 'B1'}, {attr: 'C1'}] --> Aggregator
      Aggregator --> MaintainedProfile[Builds Maintained Profile]
      DHT -- Log 'PUT' events --> Compensation
  

---

2. Derivations based on Operational Parameter Expansion

2.1. High-Frequency, Low-Latency Edge Computing Architecture

• Enabling Description: The profile aggregation system is deployed on a global network of edge computing nodes. When a user in a specific geographic region accesses a participating website, the data transaction is handled by the nearest edge node. This node maintains a real-time cache of profile fragments relevant to users in its region, using an in-memory database like Redis or a time-series database for behavioral data. The edge node performs profile enrichment and ad targeting decisions with sub-10-millisecond latency. The nodes periodically synchronize their data with a central cloud-based databank for global consistency and model training.
• Mermaid Diagram:

  graph TD
      User[User in EU] -->|Request| EdgeNodeEU[Edge Node - EU]
      
      subgraph Global Network
          EdgeNodeEU <--> CentralDB[(Central Databank)]
          EdgeNodeUS[Edge Node - US] <--> CentralDB
          EdgeNodeAPAC[Edge Node - APAC] <--> CentralDB
      end
  
      subgraph EdgeNodeEU
          direction LR
          Cache[(In-Memory Cache)]
          Logic[Targeting Logic]
          Contributor[Local Data Contributor] -- Partial Profile --> Cache
          Cache --> Logic
      end
      
      Logic -->|Targeted Ad| User
  

2.2. Federated Profile System with Privacy-Preserving Computation

• Enabling Description: For operating across strict regulatory boundaries (e.g., GDPR, CCPA), the system uses a federated architecture. Each region has an independent databank that never shares raw user data. When a cross-region profile is needed for targeting, the system uses privacy-preserving technologies like Homomorphic Encryption or Secure Multi-Party Computation (SMPC). A query is encrypted and sent to a partner databank; the partner computes over the encrypted data to find matching attributes and returns an encrypted result. The result can only be decrypted by the querying system. This allows for profile enrichment without exposing personally identifiable information (PII) across borders.
• Mermaid Diagram:

  sequenceDiagram
      participant SystemA as Databank A (e.g., US)
      participant SystemB as Databank B (e.g., EU)
      
      SystemA->>SystemA: Encrypt Query for "User X"
      SystemA->>SystemB: Send Encrypted Query
      activate SystemB
      SystemB->>SystemB: Compute on encrypted query against local data
      SystemB-->>SystemA: Return Encrypted Result (e.g., matching attributes)
      deactivate SystemB
      SystemA->>SystemA: Decrypt Result
      SystemA->>SystemA: Augment local profile for "User X"
  

---

3. Derivations based on Cross-Domain Application

3.1. Aerospace: Federated Predictive Maintenance Network

• Enabling Description: Unaffiliated entities (airlines, engine manufacturers, MRO providers) contribute operational data (a "partial profile") for specific aircraft components, identified by a unique serial number. Data includes sensor telemetry, flight cycles, and maintenance actions. A central, secure system aggregates these partial profiles into a comprehensive "maintained profile" for each component. AI models use this aggregated data to predict failures and optimize maintenance schedules. The entity that contributes data which leads to a successful "catch" of a potential failure receives a significant payment or credit, incentivizing data sharing.
• Mermaid Diagram:

  erDiagram
      AIRCRAFT_COMPONENT ||--o{ COMPONENT_PROFILE : "has"
      COMPONENT_PROFILE {
          string component_serial_id PK
          json maintained_profile
      }
      PARTIAL_PROFILE {
          string profile_id PK
          string component_serial_id FK
          string source_id
          json attributes
          timestamp created_at
      }
      DATA_CONTRIBUTOR ||--o{ PARTIAL_PROFILE : "provides"
      DATA_CONTRIBUTOR {
          string source_id PK
          string organization_name
      }
      MAINTENANCE_ALERT ||--|{ COMPONENT_PROFILE : "targets"
      MAINTENANCE_ALERT {
          string alert_id PK
          string component_serial_id FK
          string alert_details
      }
      COMPONENT_PROFILE ||--o{ PARTIAL_PROFILE : "is built from"
  

3.2. AgTech: Collaborative Crop Yield Optimization Platform

• Enabling Description: A platform aggregates "partial profiles" of agricultural land plots from diverse, unaffiliated sources: satellite imagery providers (NDVI data), IoT sensor companies (soil moisture), and hyperlocal weather services (precipitation data). Each partial profile is tagged with the source and the specific coordinates of the land plot. The platform's "maintained profile" provides a holistic view of the plot's condition. This data is used to deliver targeted advice on irrigation, fertilization, and pest control to farmers. Data contributors are compensated via a revenue-sharing model based on the measured increase in crop yield for farmers using the platform.
• Mermaid Diagram:

  flowchart TD
      A[Satellite Provider] -- NDVI Data --> CentralPlatform
      B[IoT Sensor Vendor] -- Soil Moisture --> CentralPlatform
      C[Weather Service] -- Precipitation Data --> CentralPlatform
      
      subgraph CentralPlatform
          Aggregator((Aggregator))
          PlotProfileDB[(Land Plot Profiles)]
          AnalyticsEngine{Analytics Engine}
      end
  
      Aggregator --> PlotProfileDB
      PlotProfileDB --> AnalyticsEngine
      AnalyticsEngine --> D[Farmer's Dashboard]
      D -- Actionable Insights --> E((Farmer))
      
      subgraph Compensation
          F(Yield Monitor) -- Yield Data --> G{Rev-Share Calculator}
          G -- Payments --> A
          G -- Payments --> B
          G -- Payments --> C
      end
  

---

4. Derivations based on Integration with Emerging Technology

4.1. AI-Driven Dynamic Attribute Valuation

• Enabling Description: This system integrates a reinforcement learning (RL) agent to manage the data economy. When a partial profile is received, the RL agent assesses its value based on multiple factors: the predicted uplift in conversion probability if used for ad targeting, the attribute's scarcity in the existing databank, the historical credibility of the source, and the current demand for that attribute from advertisers. The agent generates a real-time price for the data, which is used in the compensation calculation. Over time, the agent learns to prioritize high-value data sources and can even predictively request specific missing attributes from the network to complete valuable user profiles.
• Mermaid Diagram:

  stateDiagram-v2
      [*] --> Receiving
      Receiving: Partial Profile Received
      Receiving --> Valuating: On Reception
      
      Valuating: RL Agent Analyzes Data
      state Valuating {
          direction LR
          [*] --> Scarcity
          Scarcity --> Credibility
          Credibility --> PredictedUplift
          PredictedUplift --> Demand
          Demand --> [*]
      }
  
      Valuating --> Pricing: Generate Real-time Price
      Pricing --> Compensating: Execute Payment
      Compensating --> [*]
  

4.2. Blockchain-Verified Data Provenance and Compensation

• Enabling Description: The system uses a permissioned blockchain (e.g., Hyperledger Fabric) to ensure data provenance and automate compensation. When a third party contributes a partial profile, a hash of the data along with the source's identity and a user consent token is recorded as a transaction on the ledger. When this data is used for ad targeting, a smart contract is triggered. The contract automatically verifies the data's origin on the blockchain and executes a micropayment in a stablecoin from the advertiser's account directly to the data contributor's wallet. This creates a transparent, auditable, and immutable record of the entire data lifecycle.
• Mermaid Diagram:

  sequenceDiagram
      participant Contributor as Data Contributor
      participant User as User
      participant AdSystem as Ad System
      participant Blockchain as Permissioned Blockchain
      participant Advertiser as Advertiser
  
      User->>Contributor: Grants Consent
      Contributor->>AdSystem: Submits Partial Profile + Consent Token
      AdSystem->>Blockchain: Transaction: RecordData(DataHash, Source, Consent)
      Advertiser->>AdSystem: Places Ad Targeting Order
      AdSystem->>Blockchain: Smart Contract Call: UseData(DataHash)
      Blockchain-->>AdSystem: Verified
      AdSystem->>AdSystem: Serves Targeted Ad
      Blockchain->>Contributor: Auto-Execute Micropayment
  

---

5. Derivations based on Inverse or Failure Mode Operation

5.1. Graceful Degradation to Anonymized Segment Targeting

• Enabling Description: The system includes a "privacy-first" operational mode that can be triggered by user preference, regulatory requirements, or as a safe-failure mode. In this mode, the system does not store or process individual-level PII. Instead, upon receiving a partial profile, it immediately converts the specific attributes into generalized, k-anonymized segments (e.g., "male, 30-40, interested in sports" becomes segment "MK30S"). The raw data is discarded. Ad targeting is performed only on these non-personally-identifiable segments. Compensation to data providers is based on a lower, fixed rate for contributing to these anonymized audience pools.
• Mermaid Diagram:

  flowchart TD
      subgraph Normal Mode
          A[Receive Partial Profile (PII)] --> B{Store PII in Maintained Profile} --> C[Target Individual User]
      end
  
      subgraph Privacy-First Mode
          D[Receive Partial Profile (PII)] --> E{Anonymizer Engine}
          E -- K-Anonymization --> F[Generate Anonymized Segment]
          F --> G{Store Segment in Audience Pool} --> H[Target Segment]
          E -- Discard PII --> I((/dev/null))
      end
  
      Trigger[User Opt-Out or Regulation] --> Switch{Operational Mode Switch}
      Switch -- Normal --> A
      Switch -- Privacy-First --> D
  

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Combination Prior Art Scenarios with Open-Source Standards

1. Combination with OAuth 2.0 / OpenID Connect: The '904 patent's data transfer is implemented using the OAuth 2.0 authorization code grant flow. A user, on a third-party website, clicks "Share my shopping interests with AdNetwork." This initiates an OAuth flow where the user authenticates with the AdNetwork (the '904 system) and authorizes the third-party site to share specific "scopes" (e.g., profile.purchase_history). The third-party site receives an authorization code, exchanges it for an access token, and then uses the token to make a secure, server-to-server API call to the AdNetwork's user info endpoint, thereby transferring the partial profile. This standardizes the process of receiving user-consented data from unaffiliated parties.

2. Combination with W3C Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs): The user is identified by a DID, not a cookie. A third-party retail site (an "Issuer") creates a Verifiable Credential containing attributes like {"product_category": "outdoor_gear"} and cryptographically signs it. The user stores this VC in their digital wallet. When visiting a publisher site, the user's browser agent (the "Holder") presents this VC to the '904 ad system (the "Verifier"). The ad system verifies the signature of the issuer and uses the attribute for ad targeting. This decentralizes profile creation, putting the user in control of what attributes are shared, while still allowing the ad system to track the source (the issuer of the VC) for compensation.

3. Combination with Prebid.js Header Bidding Framework: The '904 profile enrichment system is configured as a "Real-Time Data" module within the open-source Prebid.js framework. When an ad auction is initiated on a publisher's webpage, Prebid calls the '904 module. This module then contacts multiple, unaffiliated data providers (also integrated into the ecosystem) to fetch partial profile attributes associated with the user's ID. It aggregates these attributes into a set of targeting segments and attaches them to the bid requests sent to demand-side platforms (DSPs). This enriches the auction with valuable user data in real-time. The data provider whose attributes are present in the winning bid receives a share of the revenue, tracked and managed through the Prebid framework.