US 6314420

Analysis of U.S. Patent No. 6,314,420

Date of Analysis: April 26, 2026

An analysis of United States Patent 6,314,420, titled "Collaborative/adaptive search engine," has been conducted based on information from the U.S. Patent and Trademark Office (USPTO) and a review of its claims. A search of the 2026 dockets for the Court of Appeals for the Federal Circuit (CAFC) revealed no pending litigation specifically involving this patent.

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Patent Overview

Title	Collaborative/adaptive search engine
Assignee	I/P Engine Inc (Current Assignee); Lycos Inc (Original Assignee)
Inventors	Andrew K. Lang, Donald M. Kosak
Filing Date	December 3, 1998
Issue Date	November 6, 2001
Abstract	A search engine system is provided for a portal site on the internet. The search engine system employs a regular search engine to make one-shot or demand searches for information entities which provide at least threshold matches to user queries. The search engine system also employs a collaborative/content-based filter to make continuing searches for information entities which match existing wire queries and are ranked and stored over time in user-accessible, system wires corresponding to the respective queries. A user feedback system provides collaborative feedback data for integration with content profile data in the operation of the collaborative/content-based filter. A query processor determines whether a demand search or a wire search is made for an input query.

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Plain-Language Summary of Independent Claims

This patent contains two independent claims, which define the core of the invention.

• Claim 1: This claim describes a search engine system that uses two different methods for handling user queries. The first method is a standard "demand" search, which finds immediate results based on the content of a user's query. The second method is a "wire" search. A "wire" is a continuous, long-term search for a specific query. The system decides whether to perform a "demand" or "wire" search. A key feature is that for "wire" searches, the system improves its results over time by incorporating feedback from other users. This "collaborative feedback" is combined with the original content-based filtering to determine the relevance of the search results.

• Claim 9: This claim outlines a method for operating a search engine. It details the process of receiving a query from a user and then deciding to perform either a "demand" search for immediate results or a "wire" search for ongoing, continuously updated results. The method involves filtering information from a network (like the internet) on a continuing basis. For at least the "wire" searches, the system combines feedback data from multiple users with the content of the information to determine what results to provide to the user. This allows the search results for "wire" queries to become more refined and relevant over time based on the collective input of users.

Litigation Involving US Patent 6,314,420

As of April 26, 2026, US Patent 6,314,420, titled "Collaborative/adaptive search engine," has been the subject of significant litigation. The primary case involving this patent is detailed below:

I/P Engine, Inc. v. AOL, Inc., et al.

• Plaintiff: I/P Engine, Inc. (a wholly-owned subsidiary of Vringo, Inc.)
• Defendants: AOL, Inc., Google, Inc., IAC Search & Media, Inc., Gannett Company, Inc., and Target Corporation.
• Jurisdiction: U.S. District Court for the Eastern District of Virginia.
• Case Number: 2:2011cv00512.
• Filing Date: September 15, 2011.

Outcome and Status:

The litigation went through several stages with differing outcomes:

1. District Court Verdict: On November 6, 2012, a jury found that the defendants had infringed upon the asserted claims of U.S. Patent Nos. 6,314,420 and 6,775,664. The jury awarded I/P Engine approximately $30.5 million in damages and set a running royalty rate of 3.5% for future infringement.

2. Post-Trial Motions and Additional Awards: Following the verdict, the District Court entered final judgment on November 20, 2012. In subsequent rulings, the court awarded I/P Engine additional supplemental damages and prejudgment interest, and also determined an ongoing royalty rate for continued infringement.

3. Appeal to the Federal Circuit: The defendants appealed the District Court's decision to the U.S. Court of Appeals for the Federal Circuit. In a split decision on August 15, 2014, the Court of Appeals reversed the lower court's judgment. The majority opinion held that the asserted claims of the '420 patent were invalid for obviousness.

4. Subsequent Actions: As a result of the Federal Circuit's reversal, the previous judgments and orders regarding damages and ongoing royalties were vacated by the District Court in January 2016. I/P Engine's petition for a rehearing en banc at the Federal Circuit was also addressed. The case was also appealed to the U.S. Supreme Court.

This case was highly publicized and is a notable example of the complexities and potential for reversal in patent litigation.

Based on a review of the USPTO's public records and external search, no AIA trial proceedings (IPR, PGR, or CBM) have been filed against US Patent 6,314,420.

Proceedings Overview

There are zero AIA trial proceedings on file for this patent. This gives a defendant a uniquely strong defensive posture, not due to PTAB activity, but because the patent's key claims were previously invalidated in federal court, rendering subsequent PTAB challenges unnecessary.

Strategic Summary

The claims of US Patent 6,314,420 are effectively CANCELED and UNENFORCEABLE. This is not the result of a PTAB trial, but rather a final, binding decision from the U.S. Court of Appeals for the Federal Circuit. In the case I/P Engine, Inc. v. AOL, Inc., et al., the Federal Circuit reversed a lower court's infringement verdict and held that the asserted claims were invalid for obviousness. This appellate decision is a more powerful defensive tool than a PTAB Final Written Decision, as it is a binding legal precedent.

Because no PTAB proceedings were ever instituted, there is no petitioner estoppel landscape to analyze under 35 U.S.C. § 315(e)(2). The primary defensive shield against any assertion of this patent is the Federal Circuit's judgment of invalidity. Any attempt to assert this patent today would likely be considered frivolous and potentially subject to sanctions, given the clear appellate ruling.

The absence of PTAB activity is a direct signal of the patent's weakness following the court's decision. Once the Federal Circuit invalidated the claims in 2014, potential infringers had no need to spend resources on filing an IPR, as the patent was already rendered unenforceable.

Recommended Next Steps

If you are a defendant facing an assertion of US Patent 6,314,420, your primary response should be to cite its invalidation by the Federal Circuit.

• The key document is the opinion from the U.S. Court of Appeals for the Federal Circuit in case number 13-1307, decided on August 15, 2014. The court's disposition states:

  "Because we find that the asserted claims of the ’420 patent would have been obvious... we reverse the district court’s denial of JMOL of invalidity."

• This decision effectively neutralizes the patent. An immediate motion to dismiss any new infringement complaint would be the standard defensive action, pointing to the binding precedent that has already invalidated the patent's claims.

Inventors

• Andrew K. Lang: Co-inventor. At the time of filing, Lang was likely an employee of Lycos, Inc., the original assignee.
• Donald M. Kosak: Co-inventor. At the time of filing, Kosak was likely an employee of Lycos, Inc., the original assignee.

There are no unusual patterns noted regarding the inventors' employment status relative to the filing date. The initial assignment from the inventors to the original assignee was recorded on 1999-09-27 (Reel 010363/0748).

Original assignee

• Lycos, Inc.: The original assignee as named on the issued patent. Lycos was a prominent developer of a web search engine and a network of web portals that became one of the most visited online destinations in the 1990s and early 2000s. The company's search engine product directly embodied the claims of the patent. After a series of acquisitions and divestitures, the Lycos brand still operates but at a much smaller scale than during its peak. The transfer of this patent in 2011 occurred long after the company's market prominence had faded.

Assignment timeline

• 1999-08-27 / recorded 1999-09-27 — Reel 010363/0748

  • Conveyance: Assignment
  • Assignor: Andrew K. Lang, Donald M. Kosak
  • Assignee: LYCOS, INC.
  • Correspondent: R. Gibson Danner, Danner & Associates, Hoffman Estates, IL
  • Context: Standard initial assignment of invention from inventors to their employer.

• 2011-06-23 / recorded 2011-07-06 — Reel 026732/0890

  • Conveyance: Assignment
  • Assignor: LYCOS, INC.
  • Assignee: SMART SEARCH LABS, INC.
  • Correspondent: John M. Ang-Nutta, King & Spalding LLP, New York, NY
  • Context: A transfer from the original operating company to a new entity, later revealed to be an assertion vehicle.

• 2011-07-14 / recorded 2011-07-19 — Reel 026859/0815

  • Conveyance: Security Agreement
  • Assignor: SMART SEARCH LABS, INC.
  • Assignee: HUDSON BAY MASTER FUND LTD.
  • Correspondent: John M. Ang-Nutta, King & Spalding LLP, New York, NY. This correspondent handled multiple related transactions.
  • Context: Securitization of the patent asset, likely to finance acquisition and litigation activities.

• n/a / recorded 2011-09-15 — Reel 027375/0236

  • Conveyance: Change of Name
  • Assignor: SMART SEARCH LABS, INC.
  • Assignee: I/P ENGINE, INC.
  • Correspondent: John M. Ang-Nutta, King & Spalding LLP, New York, NY. This correspondent handled multiple related transactions.
  • Context: Formal change of name for the new patent-holding entity just before litigation was initiated.

• 2012-08-01 / recorded 2012-08-06 — Reel 028975/0507

  • Conveyance: Security Agreement
  • Assignor: I/P ENGINE INC. (F/K/A SMART SEARCH LABS, INC.)
  • Assignee: HUDSON BAY MASTER FUND LTD.
  • Correspondent: John M. Ang-Nutta, King & Spalding LLP, New York, NY. This correspondent handled multiple related transactions.
  • Context: A further securitization of the patent asset under the new entity name.

• 2012-08-27 / recorded 2012-08-29 — Reel 029124/0001

  • Conveyance: Release
  • Assignor: HUDSON BAY MASTER FUND LTD.
  • Assignee: I/P ENGINE, INC. (F/K/A SMART SEARCH LABS, INC.)
  • Correspondent: John M. Ang-Nutta, King & Spalding LLP, New York, NY. This correspondent handled multiple related transactions.
  • Context: Release of the prior security interest, clearing title for the patent holder.

• 2016-03-31 / recorded 2016-04-07 — Reel 038038/0879

  • Conveyance: Release
  • Assignor: SILICON VALLEY BANK
  • Assignee: VRINGO, INC.
  • Correspondent: Vringo, Inc., New York, NY
  • Context: Release of a security interest held by SVB against Vringo, the parent company of I/P Engine, Inc. This does not represent a change in ownership of the patent itself from I/P Engine.

Timeline diagram

timeline
    title Ownership of US 6314420
    1998 : Filed by inventors
    1999 : Assigned to Lycos Inc
    2001 : Patent issued
    2011 : Assigned to Smart Search Labs
         : Name changed to IP Engine Inc
         : First infringement suit filed
    2012 : District Court finds infringement
    2014 : Federal Circuit reverses invalidates claims

NPE / troll-pattern signals

1. Shell-entity transfer: Present. The patent was transferred from Lycos, Inc., an operating company, to Smart Search Labs, Inc. on 2011-06-23 (Reel 026732/0890). This entity had no apparent products and its name was quickly changed to I/P Engine, Inc. before it commenced litigation.

2. Known asserter in the chain: Present. I/P Engine, Inc. was a subsidiary of Vringo, Inc., a publicly traded company widely recognized and tracked by services like Unified Patents and RPX as a patent assertion entity (NPE). The litigation I/P Engine, Inc. v. AOL, Inc., et al. confirms this.

3. Repeat correspondent across the chain: Present. John M. Ang-Nutta of King & Spalding LLP acted as the correspondent for the critical series of five transactions from July 2011 to August 2012 (Reels 026732/0890, 026859/0815, 027375/0236, 028975/0507, 029124/0001) that moved the patent from its original owner to the assertion entity and managed related security agreements. This recurrence signals a coordinated transfer campaign.

4. Cascading transfers: Present. The transfer from Lycos to Smart Search Labs (June 2011), the immediate name change to I/P Engine (September 2011), and the filing of a major lawsuit (September 2011) all occurred within a three-month period.

5. Pre-litigation transfer: Present. The assignment from Lycos to Smart Search Labs was executed on June 23, 2011. The first infringement suit was filed on September 15, 2011, less than three months later. This timing is a classic indicator of a transfer made specifically to enable an assertion campaign.

6. Bankruptcy fire-sale: Not present. There is no evidence that this transfer resulted from a Lycos bankruptcy proceeding. It appears to be a direct sale of the asset.

7. Privateering: Unclear. While the transfer from an operating company (Lycos) to an NPE (I/P Engine) fits the general pattern, there is no public evidence of a formal agreement for Lycos to share in the assertion revenue.

8. Defensive aggregator (anti-NPE): Not present. The chain of title shows no involvement of any defensive aggregators.

Verdict

• NPE — high confidence

This verdict is based on multiple strong and unambiguous signals. The patent was transferred from its original operating company owner, Lycos, to a newly formed entity (Smart Search Labs / I/P Engine) on 2011-06-23 (Reel 026732/0890). This entity was a subsidiary of Vringo, a known patent assertion entity. The transfer occurred less than three months before I/P Engine initiated a major infringement lawsuit, a classic sign of a pre-litigation transfer for the purpose of assertion. The presence of a repeat correspondent for the series of transfers further solidifies the coordinated nature of this NPE campaign.

Verification Link: USPTO Assignment Search for Pat. 6,314,420

Analysis of Prior Art for U.S. Patent 6,314,420

As a senior patent analyst, I have reviewed the citations for US Patent 6,314,420 ("the '420 patent"). The patent's core invention, as defined by its independent claims 1 and 9, is a search engine system that can perform two types of searches: a standard, immediate "demand" search, and a continuous, long-term "wire" search. For at least the "wire" searches, the system combines content-based filtering with collaborative feedback from other users to improve and rank results over time.

While the claims of the '420 patent were ultimately invalidated for obviousness under 35 U.S.C. § 103 (meaning the invention would have been an obvious combination of existing technologies to a person of ordinary skill), this analysis focuses on potential anticipation under 35 U.S.C. § 102, which requires a single prior art reference to disclose every element of a claim.

The most relevant prior art references cited in the '420 patent are detailed below.

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Key Prior Art References

1. U.S. Patent 5,867,799 A (The Parent Patent)

• Full Citation: US Patent 5,867,799 A, "Distributed, collaborative/content-based information filtering system". Filed by the same inventors, Andrew K. Lang and Donald M. Kosak, and assigned to Lycos, Inc.
• Dates: Filing Date: April 4, 1996; Publication Date: February 2, 1999.
• Brief Description: This patent, which is the parent application to the '420 patent and is incorporated by reference, discloses the foundational technology for the "wire" search. It describes in detail an information filtering system that continuously processes a data stream to find "informons" (information entities) relevant to a user. The system uses a combination of adaptive content-based filtering (analyzing the text of the informon) and collaborative filtering (using feedback from communities of users with similar interests) to identify and rank relevant information.
• Potential Anticipation of Claims: This reference discloses the majority of the elements of claims 1 and 9, including the system for continuous searching ("on a continuing basis"), the use of collaborative feedback from other users, and the combination of that feedback with content-profile data to determine relevancy. This system is functionally identical to the "wire" system described in the '420 patent. However, the '799 patent focuses exclusively on this long-term filtering model. It does not appear to explicitly disclose the dual-mode search engine that also performs an immediate "demand response" or a "query processor" that decides between the two modes.
  • Conclusion: This patent does not anticipate claims 1 or 9 under § 102 because it lacks the "demand search" element and the controlling system that selects between a "wire" and "demand" response. It is, however, the most critical reference for an obviousness argument.

2. U.S. Patent 6,014,665 A

• Full Citation: US Patent 6,014,665 A, "Personalized search and retrieval system and method". Inventor: Brad Culliss.
• Dates: Filing Date: May 2, 1997; Publication Date: January 11, 2000.
• Brief Description: This patent describes a system that personalizes search results for a specific user. It creates a user interest profile by monitoring the user's queries and the search results they select. This profile is then used to filter and re-rank future search results to better match the user's interests. The system also discloses a "proactive mode" where it can continuously search for new information related to the user's profile, similar to the "wire" concept.
• Potential Anticipation of Claims: This reference teaches a personalized, content-based search system with both an immediate search-and-rerank function (analogous to a "demand search") and a proactive, continuous search function (analogous to a "wire search"). It uses feedback, albeit from the individual user rather than a collaboration of multiple users.
  • Conclusion: This patent does not anticipate claims 1 or 9 under § 102 because it fails to disclose the element of using collaborative feedback from other users to determine the relevancy of informons. Its feedback mechanism is based on a single user's profile.

3. U.S. Patent 5,740,425 A

• Full Citation: US Patent 5,740,425 A, "Collaborative information filtering system". Inventors: Jerome R. Bellegarda, et al. Assignee: Apple Computer, Inc.
• Dates: Filing Date: September 3, 1996; Publication Date: April 14, 1998.
• Brief Description: This patent details a system that uses collaborative filtering to predict a user's interest in various information items. The system generates a user profile based on that user's ratings and compares it to the profiles of other users to find a "neighborhood" of users with similar tastes. It then recommends items that were highly rated by the users in that neighborhood. The core technology is based on Latent Semantic Indexing to manage the user profile data.
• Potential Anticipation of Claims: This reference provides a strong teaching of a "feedback system" that provides "feedback data from other users," a key element of claims 1 and 9. It explicitly describes using the preferences of a community of users to filter information for an individual.
  • Conclusion: This patent does not anticipate claims 1 or 9 under § 102. While it discloses the collaborative filtering element in detail, it does not describe combining it with a content-based filtering system in a search engine, nor does it teach a dual-mode system for handling both "demand" and "wire" (continuous) queries.

As of today's date, 2026-05-11, the asserted claims of US Patent 6,314,420 are considered invalid due to obviousness under 35 U.S.C. § 103. This conclusion is not speculative; it is based on the binding legal precedent set by the U.S. Court of Appeals for the Federal Circuit in the case I/P Engine, Inc. v. AOL, Inc., et al. (Appeal No. 2013-1307), which reversed a district court judgment and found the patent's claims invalid.

This analysis reconstructs the reasoning for that invalidity by examining key prior art references and the motivation to combine them that would have been apparent to a person of ordinary skill in the art (PHOSITA) at the time of the invention (priority date: April 4, 1996).

Person Having Ordinary Skill in the Art (PHOSITA)

A PHOSITA in early 1996 would have possessed a bachelor's degree in computer science or a related field, along with practical experience in information retrieval, database systems, and early Internet technologies. This individual would have been familiar with the limitations of first-generation, purely keyword-based search engines and would have been aware of ongoing academic and commercial efforts to improve search relevance, including the nascent fields of information filtering and user-based recommendation systems.

Prior Art Combination Rendering the Claims Obvious

The core inventive concept of US Patent 6,314,420—combining content-based filtering with collaborative, user-feedback-based filtering—was a predictable solution to a well-understood problem. The claims are rendered obvious by the combination of at least two key prior art references that were before the Federal Circuit:

1. Wittenberg (U.S. Patent No. 5,754,939): Filed in 1995, this patent teaches a system for the "selective dissemination of documents" based on a user's query. Crucially, Wittenberg discloses a persistent, long-term query that continuously filters a stream of incoming documents to find relevant ones. This system directly teaches the "wire" concept described in independent claims 1 and 9 of the '420 patent. Wittenberg's filtering is primarily content-based, using keywords from the query to match against documents.

2. GroupLens ("GroupLens: An Open Architecture for Collaborative Filtering of Netnews," Resnick et al., 1994): This influential academic paper, published two years before the '420 patent's priority date, explicitly describes a system that helps users find relevant articles in Usenet newsgroups. Its method is purely collaborative filtering. GroupLens collects ratings from users (e.g., on a 1-5 scale) and uses those ratings to predict how other users will rate articles. This directly teaches the "feedback system" that provides "feedback data from other users" to rank or filter information, as claimed in the '420 patent.

Motivation to Combine

A PHOSITA in 1996 would have been motivated to combine the teachings of Wittenberg and GroupLens for the clear and predictable purpose of improving the quality and relevance of search results.

• Known Problem: Purely content-based systems like Wittenberg suffered from a well-known flaw: they were susceptible to "keyword spamming" and could not discern the actual quality or relevance of a document beyond a simple lexical match. The need to improve search relevance was the primary challenge for information retrieval experts at the time.
• Known Solution: Collaborative filtering, as taught by GroupLens, was a known solution to this exact problem. It leveraged the collective judgment of a community of users to identify high-quality content, a technique that was understood to be more robust than simple keyword matching.
• Predictable Result: Combining Wittenberg's persistent query mechanism with GroupLens's collaborative rating system was an obvious step. A skilled artisan would have recognized that one could first use Wittenberg's content-based approach to generate a candidate set of documents (the "wire") and then apply the collaborative filtering method from GroupLens to rank that set based on user feedback. The result—a list of not just keyword-relevant but also user-endorsed documents—was the predictable and desired outcome of such a combination.

Mapping to Independent Claim 1

The combination of Wittenberg and GroupLens teaches every element of independent claim 1:

• "A search engine system...": Both references describe components of such systems.
• "...a content-based filtering system for receiving informons from a network on a continuing basis and for filtering the informons for relevancy to a wire...query...": This is the core teaching of Wittenberg's persistent query system.
• "...a feedback system for providing feedback data from other users.": This is the core teaching of the GroupLens system.
• "...the filtering system combines pertaining feedback data from the feedback system with content profile data in determining the relevancy of the informons...": This is the obvious combination. The motivation was to use the known technique from GroupLens (collaborative filtering) to improve upon the known system of Wittenberg (content-based filtering).
• "...a control system for controlling the operation of the filtering system to filter for one of a wire response and a demand response...": Providing both a persistent search ("wire," from Wittenberg) and an immediate search ("demand," a standard feature of any contemporary search engine) is an obvious design choice, not an inventive step. It merely offers the user two known modes of operation.

In conclusion, the '420 patent claims a combination of known elements (a content-based filter with persistent queries and a collaborative filter using user ratings) to achieve a predictable result (improved search relevance). As determined by the Federal Circuit, this combination would have been obvious to a person of ordinary skill in the art in 1996.

Term, Continuation, and Family Analysis for US Patent 6,314,420

Date of Analysis: May 11, 2026

This analysis details the patent term, application history, and related family members for U.S. Patent 6,314,420 ("the '420 patent").

Patent Term and Expiration

• Priority Date: The patent's term is calculated from its earliest claimed priority date. As a continuation-in-part, the '420 patent claims priority to U.S. Application No. 08/627,436, which was filed on April 4, 1996.
• Statutory Term: The standard term for a U.S. patent is 20 years from the earliest effective filing date.
• Patent Term Adjustment (PTA) / Extension (PTE): A review of the USPTO's public records for this patent indicates that no Patent Term Adjustments or Extensions were granted. The application was filed before the effective date (May 29, 2000) of the American Inventors Protection Act of 1999, which established the modern PTA system.
• Calculated Expiration Date: Based on the April 4, 1996, priority date and a 20-year term, the patent expired on April 4, 2016. This is consistent with the "Expired - Lifetime" legal status listed in public databases.

Continuation and Divisional History

The '420 patent is part of a chain of related applications filed by the same inventors.

• Parent Application:

  • The '420 patent, filed as application 09/204,149 on December 3, 1998, is a Continuation-in-Part of application 08/627,436.
  • Application 08/627,436 was filed on April 4, 1996, and issued as U.S. Patent 5,867,799 ("Distributed, collaborative/content-based information filtering system") on February 2, 1999. This parent patent discloses the foundational "wire" or continuous filtering system.

• Child Application (Continuation):

  • A continuation of the application for the '420 patent was filed on October 22, 2001, under application number 10/045,198.
  • This continuation application subsequently issued as U.S. Patent 6,775,664 ("Collaborative/adaptive search engine") on August 10, 2004. This patent shares the same title as the '420 patent and was also asserted in the I/P Engine, Inc. v. AOL, Inc., et al. litigation.

Patent Family Summary

The known U.S. patent family for US 6,314,420 consists of three issued patents originating from the initial 1996 application.

Patent Number	Application Number	Filing Date	Issue Date	Relationship to '420 Patent	Title
5,867,799	08/627,436	April 4, 1996	February 2, 1999	Parent Application	Distributed, collaborative/content-based information filtering system
6,314,420	09/204,149	Dec. 3, 1998	Nov. 6, 2001	Subject Patent (Continuation-in-Part of '799 application)	Collaborative/adaptive search engine
6,775,664	10/045,198	October 22, 2001	August 10, 2004	Continuation of '420 application	Collaborative/adaptive search engine

There are no known foreign counterparts or divisional applications associated with this patent family. The inventive activity appears to be confined to the United States.

Defensive Disclosure: Derivative Embodiments of Collaborative and Adaptive Search

Publication Date: May 11, 2026
Reference Patent: US 6,314,420 B1 ("Collaborative/adaptive search engine")
Objective: This document discloses a plurality of derivative implementations, applications, and enhancements of the core concepts described in US Patent 6,314,420. The purpose of this disclosure is to establish prior art against future patent claims on incremental variations of dual-mode (demand/continuous) search systems and those integrating collaborative and content-based filtering.

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Derivatives Based on Independent Claim 1: A System for Filtering and Responding to Queries

1. Material & Component Substitution

• Derivative 1.1: In-Memory Graph Database for Collaborative Filtering

  • Enabling Description: The filtering system is implemented using an in-memory graph database (e.g., Neo4j, RedisGraph) instead of a traditional relational database. User profiles, "informons" (information entities), and feedback events (ratings, views, shares) are modeled as nodes and edges. The "wire" query leverages graph traversal algorithms (e.g., PageRank, k-nearest neighbors) to determine relationships between users and content in real-time. This component substitution allows for significantly faster collaborative filtering by treating user similarity and content relevance as direct relationships within the graph, rather than requiring complex table joins. The "demand" search component queries a separate, document-oriented search index (e.g., Elasticsearch), but its results can be re-ranked using a fast, single-depth traversal from the user's node in the graph database.

  • graph TD
        A[User Query] --> B{Query Processor};
        B -- Demand Query --> C[Elasticsearch Index];
        B -- Wire Query --> D[In-Memory Graph DB];
        D -- Traversal & Ranking --> E[Ranked Wire Results];
        C --> F[Initial Demand Results];
        F -- User Node ID --> D;
        D -- Collaborative Re-ranking --> G[Re-ranked Demand Results];
        E --> H[User];
        G --> H;
    

• Derivative 1.2: Serverless Function Architecture

  • Enabling Description: The entire system is decomposed into a set of serverless functions (e.g., AWS Lambda, Google Cloud Functions). The "query processor" is a function triggered by an API Gateway endpoint. It determines the query type and invokes either a "demand-search" function or a "wire-update" function. The "wire" is not a continuously running process but a stateful entry in a key-value store (e.g., DynamoDB) that tracks user interest. A separate, time-triggered function periodically crawls for new informons, processes them, and asynchronously updates the result lists for all active "wires" by comparing informon content against stored wire profiles. This substitution of monolithic services with ephemeral functions reduces operational overhead and allows for massive, independent scaling of the demand and wire-processing components.

  • sequenceDiagram
        participant User
        participant APIGateway as API Gateway
        participant QueryProcessor [λ Query Processor]
        participant DemandSearch [λ Demand Search]
        participant WireStore [DynamoDB Wire Table]
        participant Crawler [λ Crawler]
    
        User->>APIGateway: POST /query
        APIGateway->>QueryProcessor: Invoke
        QueryProcessor->>WireStore: Check for existing wire
        alt Wire Exists
            QueryProcessor->>WireStore: Read latest results
            WireStore-->>User: Return cached wire results
        else Demand Search
            QueryProcessor->>DemandSearch: Invoke
            DemandSearch-->>User: Return immediate results
        end
        Note right of Crawler: Triggered every 5 mins
        Crawler->>WireStore: Update all active wires with new informons
    

2. Operational Parameter Expansion

• Derivative 1.3: Planetary-Scale Redundant File System Search

  • Enabling Description: The system is applied to a globally distributed, redundant file system (e.g., IPFS). "Informons" are immutable, content-addressed data blocks. A "wire" query acts as a persistent subscription to a Merkle-DAG, receiving updates as new versions are published. The "demand" search uses a distributed hash table (DHT) for fast lookups of known content identifiers (CIDs). Collaborative feedback is collected from peer nodes that have replicated the data, and feedback is cryptographically signed by each user's keypair. The system operates at an extreme scale, managing petabytes of data across thousands of untrusted nodes, with latency-tolerant "wire" updates propagated through a gossip protocol.

  • flowchart TD
        subgraph UserNode1
            A[User Query] --> B{Query Processor}
            B --> C[Demand Search via DHT]
            B --> D[Subscribe to Wire via GossipSub]
        end
        subgraph UserNode2
            F[User Feedback] --> G{Sign Feedback}
            G --> H[Publish to DHT]
        end
        subgraph Network
            I((IPFS Network))
            C -- CID Lookup --> I
            D -- Pub/Sub Channel --> I
            H -- Put Record --> I
        end
        I -- New Informon Blocks --> D
    

• Derivative 1.4: Real-Time RF Spectrum Analysis

  • Enabling Description: The system operates on high-frequency radio signal data. "Informons" are discrete signal patterns (e.g., a specific modulation type, frequency hopping sequence) captured by a distributed network of software-defined radios (SDRs). A "demand" search queries a historical database of categorized signals. A "wire" constitutes a continuous monitoring task for a specific signal signature in a noisy RF band. Collaborative filtering is performed by combining confidence scores from multiple SDR nodes that detect a similar signal pattern. The system functions at extreme frequencies (GHz range) and requires real-time processing to distinguish between known, unknown, and adversarial signals.

  • stateDiagram-v2
        [*] --> Idle
        Idle --> DemandSearch: onQuery(type=demand)
        DemandSearch --> Idle: return results
        Idle --> WireMonitoring: onQuery(type=wire, signature)
        WireMonitoring --> SignalDetected: onSignatureMatch
        SignalDetected --> Correlating: aggregate feedback from peer nodes
        Correlating --> ResultPublished: onQuorum
        ResultPublished --> WireMonitoring
        WireMonitoring --> Idle: onCancel
    

3. Cross-Domain Application

• Derivative 1.5: Genomic Data Analysis

  • Enabling Description: In bioinformatics, a "demand" search allows a researcher to find known gene sequences or protein structures in a large genomic database (e.g., NCBI BLAST). A "wire" is a persistent query that continuously scans newly sequenced genomes for a specific, novel genetic marker or mutation. Collaborative feedback is sourced from annotations and experimental results submitted by other researchers. If multiple independent labs associate a specific "wire" result (a newly found gene sequence) with a similar biological function, the system increases the relevance ranking of that result for all subscribers to that "wire."

  • classDiagram
    class GenomicSearchSystem {
        +processQuery(query: UserQuery)
    }
    class QueryProcessor {
        -db: GenomicDatabase
        -wireStore: ActiveWires
        +routeQuery(query)
    }
    class DemandSearch {
        +findSequence(sequence: string)
    }
    class WireFilter {
        +scanNewGenomes(genome: GenomeData)
    }
    class CollaborativeFeedback {
        +updateRanking(markerId, annotation)
    }
    GenomicSearchSystem *-- QueryProcessor
    QueryProcessor --> DemandSearch
    QueryProcessor --> WireFilter
    WireFilter o-- CollaborativeFeedback
    

• Derivative 1.6: Automated Legal E-Discovery

  • Enabling Description: In the legal field, a "demand" search is used by an attorney to find specific documents containing keywords relevant to a case from a large corpus of evidence. A "wire" is set up to continuously monitor incoming documents (e.g., new emails, scanned records) for privilege, confidentiality, or relevance to a specific legal argument. The collaborative feedback mechanism is implemented through a team of paralegals reviewing documents. When multiple reviewers independently tag a document found by a "wire" as "highly relevant," the system automatically prioritizes similar, unreviewed documents for the entire legal team.

  • flowchart LR
        A[Document Ingestion] --> B[Content Indexing];
        C[Attorney Query] --> D{Query Processor};
        D -- Demand --> B;
        D -- Create Wire --> E[Wire Profile Store];
        B -- Matched by Wire --> F[Review Queue];
        G[Paralegal Review] --> H{Relevance Feedback};
        H -- High Relevance --> I[Collaborative Filter];
        I -- Boost Priority --> F;
    

4. Integration with Emerging Tech

• Derivative 1.7: AI-Driven Predictive Wire Creation

  • Enabling Description: The system integrates a machine learning model (e.g., a recurrent neural network or transformer) that analyzes the sequence of a user's "demand" queries. If the model predicts a high probability that the user's information need is long-term (e.g., queries about "Model XYZ phone specs" followed by "Model XYZ phone reviews"), it proactively suggests creating a "wire" for that topic. The collaborative feedback data is used as a training signal for the model; wires that are accepted and receive positive user engagement reinforce the prediction pathways that led to their creation.

  • sequenceDiagram
        participant User
        participant SearchSystem
        participant PredictionModel as AI Model
    
        User->>SearchSystem: Demand Query 1
        SearchSystem->>PredictionModel: Log Query 1
        User->>SearchSystem: Demand Query 2
        SearchSystem->>PredictionModel: Log Query 2
        PredictionModel->>SearchSystem: Predict Long-Term Interest: Topic "T"
        SearchSystem->>User: Suggest creating a 'wire' for Topic "T"?
        User->>SearchSystem: Accept
    

• Derivative 1.8: Blockchain-Verified Collaborative Feedback

  • Enabling Description: The feedback system is integrated with a public blockchain. When a user submits a rating or review for an "informon," a hash of the feedback is recorded on the blockchain in a transaction signed by the user's private key. This creates an immutable, tamper-proof audit trail of all collaborative data. The filtering system prioritizes feedback from users with a long-standing, consistent history on the chain, effectively creating a reputation system. This prevents Sybil attacks where an adversary creates numerous fake accounts to manipulate search rankings, as each identity would need to expend resources (i.e., "gas fees") to submit feedback.

  • graph TD
        A[User rates Informon] --> B{Create Feedback Payload};
        B --> C[Sign Payload with User's Private Key];
        C --> D[Submit as Blockchain Transaction];
        D --> E((Blockchain Ledger));
        F[Filter System] --> G{Read Feedback from Ledger};
        G --> H[Verify Transaction Signature];
        H --> I[Apply Weighted Feedback to Wire];
    

5. The "Inverse" or Failure Mode

• Derivative 1.9: Graceful Degradation under Load
  • Enabling Description: The system is designed to operate in a "graceful degradation" mode. A central load balancer monitors the query queue length and the processing latency of the collaborative/content-based filter for the "wire" services. If latency exceeds a predefined threshold (e.g., 500ms), the query processor is automatically reconfigured to treat all incoming queries as "demand" searches. It bypasses the "wire" system entirely and serves results directly from the static content index. During this mode, collaborative feedback is still collected but is queued for batch processing once the system load returns to normal. This ensures high availability for basic search functionality at the expense of the more resource-intensive continuous and personalized features.

  • stateDiagram-v2
        state "Normal Operation" as Normal {
            state "Process as Wire" as Wire
            state "Process as Demand" as Demand
        }
        state "Degraded Mode" as Degraded
    
        [*] --> Normal
        Normal --> Degraded: on HighLatency
        Degraded --> Normal: on LowLatency
    
        Normal: onQuery -> checkWire()
        checkWire() --> Wire: if wireExists
        checkWire() --> Demand: else
    
        Degraded: onQuery -> processAsDemand()
    

---

Combination Prior Art Scenarios

• Scenario 1: Combination with Apache Lucene and Kafka

  • Disclosure: A search system is constructed using the open-source Apache Lucene library as the core "demand" search engine. User queries are ingested through an Apache Kafka topic. A "Query Processor" service consumes from this topic. For demand searches, it queries the Lucene index directly. To create a "wire," it stores the query profile and user ID in a database. A separate fleet of "informon processing" services, also consuming from a Kafka topic of newly discovered documents, compares each document against the stored wire profiles. If a match occurs, the result is pushed to a user-specific Kafka topic, which the user's client is subscribed to. Collaborative feedback is collected on yet another Kafka topic and is used by a stream processor (e.g., Kafka Streams) to continuously update a relevance model used by the informon processors. This architecture is an obvious combination of the system in '420 with standard, widely used open-source data processing components.

• Scenario 2: Combination with ActivityPub Federated Social Protocol

  • Disclosure: The system is implemented within a federated social network operating on the W3C ActivityPub standard. An "informon" is any Note or Article object. A "demand" search queries a user's home server for content. A "wire" is implemented by sending a Follow activity to a synthetic Service actor representing the query. This actor, upon discovering new, relevant content from the federated network, pushes it to its followers' inboxes as an Announce activity. Collaborative feedback is derived directly from social signals native to the protocol, such as Like and Announce activities from other users in the federation. A user's filtering is thus improved by the explicit actions of others who follow similar hashtag or topic actors, a direct implementation of the '420 method using a pre-existing, open protocol.

• Scenario 3: Combination with TensorFlow for Collaborative Ranking

  • Disclosure: The collaborative filtering component of the system is implemented using the open-source TensorFlow machine learning framework. User and informon profiles are represented as high-dimensional vectors (embeddings). A deep neural network is trained on historical user feedback data (clicks, ratings) to predict the probability of a user positively engaging with a given informon. The output of this model is the primary signal for ranking results in a "wire" search. The content-based filtering aspect serves as a pre-filtering step to select candidate informons which are then passed to the TensorFlow model for collaborative re-ranking. This represents a straightforward application of a standard, open-source machine learning toolkit to implement the collaborative feedback and relevance determination steps described in claim 1 and claim 9 of the '420 patent.