IP Library › Granted Patent US 12,461,922
Granted Patent B1
US 12,461,922 · App. 18/796,950 · Granted Nov 4, 2025

Platform for semantic search and dynamic reclassification

Inventors: Brian M. Sager (Menlo Park, CA); William Lee Kimberlin (Menlo Park, CA)
Assignee: Reveal Networks, Inc.
G06F16/24573G06F16/248G06F16/906G06F40/205G06F40/30
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Quick Facts
Patent No.
US 12,461,922
App. No.
18/796,950
Granted
Nov 4, 2025
Kind
B1
Abstract

A platform receives an input document from a user device and automatically determines a semantic signature for the input document based on a probabilistic distribution of rare words within the input document. The platform automatically scrapes at least one Internet database for additional documents and webpages, determining semantic signatures for each document or webpage. Based on similarity of semantic signatures, the platform automatically constructs and displays a graphical network of documents, wherein each document is represented as a node and similarity of semantic signatures is used to determine the locations of edges between nodes. The graph automatically groups nodes by communities and selects nodes in different communities to promote serendipity of results.

Claims (42)

1 . A platform for identifying relevant documents, comprising:

a server platform, including a processor and a memory, operable to communicate with at least one user device;

wherein the server platform receives at least one input document from the at least one user device to initiate a search;

wherein the server platform automatically determines a semantic signature for the at least one input document;

wherein the server platform automatically parses a plurality of documents to identify semantic signatures for each of the plurality of documents, and returns a list of documents having semantic signatures substantially similar to the semantic signature of the at least one input document;

wherein the server platform graphically displays the list of documents on the at least one user device;

wherein the server platform applies at least one meta-tag to each of the at least one input documents and/or each of the plurality of documents;

wherein the at least one meta-tag is based on comparison of the semantic signature of the tagged document with at least one contextual signature identified for at least one technical field;

wherein based on the list of documents, the server platform automatically generates a temporal provenance of the semantic signature, and wherein the temporal provenance of the semantic signature is a time distribution of when documents substantially similar to the at least one input document were published and/or written; and

wherein the server platform generates a trustworthiness score for the plurality of documents based on a semantic graph density for the plurality of documents and/or intrinsic trustworthiness ratings for a source or a type of source of each of the plurality of documents.

2 . The system of claim 1 , wherein the server platform retrieves at least one of the plurality of documents using a web crawler.

3 . The system of claim 1 , wherein the server platform automatically transmits a warning to the at least one user device if the trustworthiness score is beneath a minimal trustworthiness threshold.

4 . The system of claim 1 , where the semantic signature is determined based on a probabilistic distribution of words in the at least one input document.

5 . The system of claim 1 , wherein based on the list of documents, the server platform automatically generates a spatial provenance of the semantic signature, and wherein the spatial provenance of the semantic signature includes one or more sites on which substantially similar documents have been published.

6 . The system of claim 1 , wherein the at least one input document includes a plurality of input documents and wherein the server platform is operable to generate an aggregate semantic signature for the plurality of input documents.

7 . The system of claim 1 , wherein the server platform automatically indicates at least one serendipitous result, wherein the at least one serendipitous result includes at least one document not within one or more communities associated with the at least one input document.

8 . The system of claim 1 , wherein the server platform graphically displays the list of documents on the at least one user device in the form of a graph, wherein each document is represented by a node and edges are constructed based on similarity of the semantic signatures of connected documents being greater than a preset threshold of similarity.

9 . The system of claim 1 , wherein the server platform receives a selection to exclude one or more types of documents from the plurality of documents.

10 . A method for identifying relevant documents, comprising:

a server platform including a processor and a memory receiving at least one input document from at least one user device to initiate a search;

the server platform automatically determining a semantic signature for the at least one input document;

the server platform automatically parsing a plurality of documents to identify semantic signatures for each of the plurality of documents, and returning a list of documents having semantic signatures substantially similar to the semantic signature of the at least one input document;

the server platform graphically displaying the list of documents on the at least one user device;

the server platform applying at least one meta-tag to each of the at least one input document and/or each of the plurality of documents;

the at least one meta-tag being based on comparison of the semantic signature of the tagged document with at least one contextual signature identified for at least one technical field;

wherein based on the list of documents, the server platform automatically generates a temporal provenance of the semantic signature, and wherein the temporal provenance of the semantic signature is a time distribution of when documents substantially similar to the at least one input document were published and/or written; and

the server platform generating a trustworthiness score for the plurality of documents based on a semantic graph density for the plurality of documents and/or intrinsic trustworthiness ratings for a source or a type of source of each of the plurality of documents.

11 . The method of claim 10 , further comprising the server platform retrieving at least one of the plurality of documents using a web crawler.

12 . The method of claim 10 , further comprising the server platform automatically transmitting a warning to the at least one user device if the trustworthiness score is beneath a minimal trustworthiness threshold.

13 . The method of claim 10 , where the semantic signature is determined based on a probabilistic distribution of words in the at least one input document.

14 . The method of claim 10 , wherein the server platform graphically displaying the list of documents on the at least one user device includes displaying the list of documents in the form of a graph, wherein each document is represented by a node and edges are constructed based on similarity of the semantic signatures of connected documents being greater than a preset threshold of similarity.

15 . A platform for identifying relevant documents, comprising:

a server platform, including a processor and a memory, in network communication with at least one user device;

wherein the server platform receives at least one input document from the at least one user device to initiate a search;

wherein the server platform automatically determines a semantic signature for the at least one input document;

wherein the server platform automatically parses a plurality of documents to identify semantic signatures for each of the plurality of documents, and returns a list of documents having semantic signatures substantially similar to the semantic signature of the at least one input document;

wherein the server platform graphically displays the list of documents on the at least one user device;

wherein the server platform generates a trustworthiness score for the plurality of documents based on a semantic graph density for the plurality of documents and/or intrinsic trustworthiness ratings for a source or a type of source of each of the plurality of documents; and

wherein based on the list of documents, the server platform automatically generates a temporal provenance of the semantic signature, and wherein the temporal provenance of the semantic signature is a time distribution of when documents substantially similar to the at least one input document were published and/or written.

16 . The platform of claim 15 , wherein the semantic signature is determined based on a probabilistic distribution of words in the at least one input document.

17 . The platform of claim 15 , wherein the server platform retrieves at least one of the plurality of documents using a web crawler.

18 . The platform of claim 15 , wherein the server platform graphically displays the list of documents on the at least one user device, including displaying the list of documents in the form of a graph, wherein each document is represented by a node and edges are constructed based on similarity of the semantic signatures of connected documents being greater than a preset threshold of similarity.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 13, 2024
From: KIMBERLIN, WILLIAM LEE
To: REVEAL NETWORKS, INC.
Reel/Frame 068265/0878 →
Continuity (13)
Continuation 18157431 · Jan 20, 2023
Continuation 17849385 · Jun 24, 2022
Continuation In Part 15663460 · Jul 28, 2017
Continuation In Part 15589882 · May 8, 2017
Continuation In Part 15589838 · May 8, 2017
Continuation In Part 15148967 · May 6, 2016
Continuation In Part 14811718 · Jul 28, 2015
Continuation In Part 14105174 · Dec 12, 2013
Continuation In Part 14059460 · Oct 22, 2013
Continuation In Part 13900676 · May 23, 2013
Provisional Application 62368159 · Jul 28, 2016
Provisional Application 62333078 · May 6, 2016
Provisional Application 62333092 · May 6, 2016
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