IP Library Granted Patent US 12,265,587
Granted Patent B2
US 12,265,587 · App. 17/133,764 · Granted Apr 1, 2025

Systems and method for investigating relationships among entities

Inventors: Emily Brooks Pavlini (Boston, MA); Jason Rastrick Briggs (Boston, MA); Max Kleiman-Weiner (Cambridge, MA); John Randolph Frank (Cambridge, MA); Tyler Balensiefer (Cambridge, MA); Cogan Dwayne Culver (Satfford, VA); Kevin John Doyle (Somerville, MA); Thomas Michael DuBois (Columbia, MD); Keith Michael Gabryelski (Brookline, MA); Andrew Richard Gallant (Marlborough, MA); Andrew Wilson Haskell (Manchester-by-the-Sea, MA); Abdi-Hakin Dirie (Cambridge, MA); David Johnson (Somerville, MA); Geoffrey Ira Milstein (Merrimac, MA); Daniel Adam Roberts (Cambridge, MA); Aaron Michael Taylor (Cambridge, MA); Henry Forrest Leanna Wallace (Cambridge, MA); Logan Eli Zoellner (Columbia, MD)
Assignee: Salesforce, Inc.
G06F16/9538G06F16/9024G06F16/93
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,265,587
App. No.
17/133,764
Granted
Apr 1, 2025
Kind
B2
Abstract

Connections among two different entities are identified by processing a collection of documents to identify one or more documents that contain co-occurring mentions of each of the two different entities. This relationship may be graphically displayed in a user interface with an icon or the like for each of the two entities, along with a graphical link interconnecting the entities. The graphical link can be an active element of the user interface that responds to user interactions by providing access to evidence within the collection of documents that substantiates the connection between the two entities. In one aspect, a search input form field in a user interface may be used to explicitly request documents that substantiate a relationship between two entities. In another aspect, a user may ground entity mentions by explicitly selecting documents that mention an entity of interest.

Claims (47)

1. A non-transitory machine-readable storage medium that provides instructions that, if executed by a processor, are configurable to cause the processor to perform operations comprising:

receiving a keyword search from a user via a search input form field of a user interface for a search engine;

applying a coreference algorithm to the keyword search to predict an entity intended by the user and characterized by one or more entity-related groups of mentions;

presenting a first search result to the user in the user interface, the first search result including a first plurality of entity tags and a plurality of documents from a collection of documents, each one of the plurality of documents containing a mention located by the search engine in at least one of the one or more entity-related groups of mentions, and each one of the first plurality of entity tags corresponding to at least one of the mentions;

receiving a first selection from the user of a first entity tag for a first entity characterized by a first entity-related group of mentions from the first plurality of entity tags, the first selection indicative of a user confirmation that the keyword search was intended to reference the first entity;

adding the first entity tag to the search input form field;

applying a relevance algorithm to identify a text comprising an evidence passage within a second plurality of documents, the evidence passage providing evidence indicating an existence or nature of a relationship between the first entity and one or more other entities characterized by one or more other entity-related groups of mentions, the relevance algorithm predicting that the text provides evidence of a relationship between the first entity and the one or more other entities;

presenting a second plurality of entity tags, each corresponding to one of the one or more other entities in the user interface;

receiving a second selection from the user of a second entity tag from the second plurality of entity tags; and

presenting a second search result including one or more of the second plurality of documents that substantiate a relationship between the first entity and a second entity based on the evidence passage.

2. The computer program product of claim 1 further comprising code that performs the step of displaying the relationship graphically in the user interface as a first icon for the first entity, a second icon for the second entity, and a connector visually coupling the first icon to the second icon.

3. The computer program product of claim 1 further comprising code that performs the step of displaying the relationship within the search input form field as the first entity tag coupled to the second entity tag by a relationship operator.

4. The computer program product of claim 3 wherein the relationship operator includes a “<>” symbol.

5. The computer program product of claim 1 wherein the collection of documents includes documents hosted locally on a user device where the keyword search is received.

6. The computer program product of claim 1 wherein the collection of documents includes documents distributed on a wide area network.

7. The computer program product of claim 1 wherein the plurality of documents includes documents hosted on a remote cloud storage facility.

8. The computer program product of claim 1 wherein presenting the second search result includes graphically presenting a plurality of entity tags each connected to the first entity by an edge in a graph.

9. A method comprising:

receiving a keyword search from a user in a search input form field of a user interface for a search engine;

predicting one or more entities intended by the user;

presenting a first search result to the user in the user interface, the first search result including a first plurality of entity tags and a plurality of documents, each one of the plurality of documents containing a mention located by the search engine of at least one of the one or more entities, and each one of the first plurality of entity tags corresponding to at least one of the mentions;

receiving a first selection from the user of a first entity tag for a first entity from the first plurality of entity tags, the first selection indicative of a user confirmation that the keyword search was intended to reference the first entity;

adding the first entity tag to the search input form field;

identifying a text comprising an evidence passage within a second plurality of documents, the evidence passage providing evidence indicating an existence or nature of a relationship between the first entity and one or more other entities;

presenting a second plurality of entity tags for the one or more other entities in the user interface;

receiving a second selection from the user of a second entity tag for a second entity from the second plurality of entity tags; and

presenting a second search result including one or more of the second plurality of documents that substantiate a relationship between the first entity and the second entity based on the evidence text.

10. The method of claim 9 further comprising displaying the relationship graphically in the user interface as a first icon for the first entity, a second icon for the second entity, and a connector visually coupling the first icon to the second icon.

11. The method of claim 9 further comprising displaying the relationship within the search input form field as the first entity tag coupled to the second entity tag by a relationship operator.

12. The method of claim 11 wherein the relationship operator includes a “<>” symbol.

13. The method of claim 9 wherein predicting one or more entities intended by the user in the keyword search includes applying a coreference algorithm to the keyword search to predict one or more entities intended by the user.

14. The method of claim 9 wherein identifying text in the plurality of documents that provides evidence of a relationship between the first entity and one or more other entities includes applying a relevance algorithm to identify text in the plurality of documents that provides evidence of a relationship between the first entity and one or more other entities, the relevance algorithm predicting that the text provides evidence of a relationship between the first entity and the one or more other entities.

15. The method of claim 9 wherein the plurality of documents includes documents obtained from a collection of documents hosted locally on a user device where the keyword search is received.

16. The method of claim 9 wherein the plurality of documents includes documents obtained from a collection of documents distributed on a wide area network.

17. The method of claim 9 wherein the plurality of documents includes documents obtained from a collection of documents hosted on a remote cloud storage facility.

18. The method of claim 9 further comprising storing a relation description characterizing a relationship between the first entity and the second entity for further use by the user within the user interface.

19. The method of claim 9 further comprising graphically displaying a first icon for the first entity, a second icon for the second entity, and a connector visually coupling the first icon to the second icon to illustrate the relationship, wherein the connector includes a user interface element providing access by a user to evidence of the relationship within the second plurality of documents.

20. A system comprising:

a search engine;

a data network;

a computing device coupled to the search engine through the data network, the computing device including a processor, a memory, and a display, the memory storing code executable by the processor to perform the steps of receiving a keyword search from a user in a search input form field of a user interface, predicting one or more entities intended by the user; presenting a first search result to the user in the user interface, the first search result including a first plurality of entity tags and a plurality of documents, each one of the plurality of documents containing a mention located by the search engine of at least one of the one or more entities, and each one of the first plurality of entity tags corresponding to at least one of the mentions; receiving a first selection from the user of a first entity tag for a first entity from the first plurality of entity tags, the first selection indicative of a user confirmation that the keyword search was intended to reference the first entity; adding the first entity tag to the search input form field; identifying a text comprising an evidence passage within a second plurality of documents, the evidence passage providing evidence indicating an existence or nature of a relationship between the first entity and one or more other entities; presenting a second plurality of entity tags for the one or more other entities in the user interface; receiving a second selection from the user of a second entity tag for a second entity from the second plurality of entity tags; and presenting a second search result including one or more of the second plurality of documents that substantiate a relationship between the first entity and the second entity based on the evidence text.

21. A non-transitory machine-readable storage medium that provides instructions that, if executed by a processor, are configurable to cause the processor to perform operations comprising:

displaying a user interface for a search engine, the user interface including a search input form field;

receiving a user input to the search input form field;

parsing the user input to identify a first text string identifying a first entity, a second text string identifying a second entity, and an operator between the first text string and the second text string specifying to the search engine a request to search for evidence of a relationship between the first entity and the second entity;

in response to the operator, searching for one or more documents in a collection of documents that contain mentions that a coreference algorithm predicts are mentions that an author intended to refer to the first entity and other mentions that a coreference algorithm predicts are mentions that the author intended to refer to the second entity, and that provide a text comprising an evidence passage that a relevance algorithm predicts provides evidence of a relationship between the first entity and the second entity, the evidence passage providing evidence indicating an existence or nature of a relationship between the first entity and the second entity; and

presenting a plurality of the one or more documents in the user interface that substantiates a relationship between the first entity and the second entity based on the evidence text.

Assignments (3)
CHANGE OF NAME Recorded Dec 19, 2024
From: SALESFORCE.COM, INC.
To: SALESFORCE, INC.
Reel/Frame 069730/0641 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 8, 2021
From: DIFFEO, INC.
To: SALESFORCE.COM, INC.
Reel/Frame 054854/0298 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 8, 2021
From: PAVLINI, EMILY BROOKS; BRIGGS, JASON RASTRICK; KLEIMAN-WEINER, MAX; FRANK, JOHN RANDOLPH; BALENSIEFER, TYLER; CULVER, COGAN DWAYNE; DOYLE, KEVIN JOHN; DUBOIS, THOMAS MICHAEL; GABRYELSKI, KEITH MICHAEL; GALLANT, ANDREW RICHARD; HASKELL, ANDREW WILSON; DIRIE, ABDI-HAKIN; JOHNSON, DAVID; MILSTEIN, GEOFFREY IRA; ROBERTS, DANIEL ADAM; TAYLOR, AARON MICHAEL; WALLACE, HENRY FORREST LEANNA; ZOELLNER, LOGAN ELI
To: DIFFEO, INC.
Reel/Frame 054928/0109 →
Continuity (5)
Continuation PCTUS2019039051 · Jun 25, 2019
Provisional Application 62832085 · Apr 10, 2019
Provisional Application 62794177 · Jan 18, 2019
Provisional Application 62689737 · Jun 25, 2018
Related Publication 20210149980A1 · May 20, 2021
References Cited (171)
US 5659732A · Kirsch · 1997 [cited by applicant]
US 5673369A · Kim · 1997 [cited by applicant]
US 5748954A · Mauldin · 1998 [cited by applicant]
US 5764906A · Edelstein et al. · 1998 [cited by applicant]
US 5836771A · Ho et al. · 1998 [cited by applicant]
US 5873107A · Borovoy et al. · 1999 [cited by applicant]
US 5884302A · Ho · 1999 [cited by applicant]
US 5924090A · Krellenstein · 1999 [cited by applicant]
US 5934910A · Ho et al. · 1999 [cited by applicant]
US 6112203A · Bharat et al. · 2000 [cited by applicant]
US 6138113A · Dean et al. · 2000 [cited by applicant]
US 7401057B2 · Eder et al. · 2008 [cited by applicant]
US 7962500B2 · Van Zwol et al. · 2011 [cited by applicant]
US 8122019B2 · Sjogreen et al. · 2012 [cited by applicant]
US 8402029B2 · Valdes-Perez et al. · 2013 [cited by applicant]
US 8429173B1 · Rosenberg et al. · 2013 [cited by applicant]
US 8533223B2 · Houghton et al. · 2013 [cited by applicant]
US 8543649B2 · Gilmour et al. · 2013 [cited by applicant]
US 8577911B1 · Stepinski et al. · 2013 [cited by applicant]
US 8635197B2 · Chaturvedi et al. · 2014 [cited by applicant]
US 8751505B2 · Yogev et al. · 2014 [cited by applicant]
US 8949204B2 · Chaturvedi et al. · 2015 [cited by applicant]
US 9047278B1 · Mann et al. · 2015 [cited by applicant]
US 9081814B1 · Carroll et al. · 2015 [cited by applicant]
US 9135329B1 · Gupta · 2015 [cited by examiner]
US 9275132B2 · Roberts et al. · 2016 [cited by applicant]
US 10474708B2 · Roberts et al. · 2019 [cited by applicant]
US 10839021B2 · Kleiman-Weiner et al. · 2020 [cited by applicant]
US 11294970B1 · Bousquet · 2022 [cited by examiner]
US 11393141B1 · Hsu · 2022 [cited by examiner]
US 11755541B2 · Gerphagnon · 2023 [cited by examiner]
US 20030126136A1 · Omoigui · 2003 [cited by applicant]
US 20030177112A1 · Gardner · 2003 [cited by applicant]
US 20030187844A1 · Li et al. · 2003 [cited by applicant]
US 20060116994A1 · Jonker · 2006 [cited by examiner]
US 20070067285A1 · Blume et al. · 2007 [cited by applicant]
US 20070130126A1 · Lucovsky et al. · 2007 [cited by applicant]
US 20070198948A1 · Toriyama et al. · 2007 [cited by applicant]
US 20070203693A1 · Estes · 2007 [cited by applicant]
US 20070208719A1 · Tran · 2007 [cited by applicant]
US 20070214114A1 · Liu et al. · 2007 [cited by applicant]
US 20080104103A1 · Adams et al. · 2008 [cited by applicant]
US 20080222105A1 · Matheny et al. · 2008 [cited by applicant]
US 20090019031A1 · Krovitz et al. · 2009 [cited by applicant]
US 20090144609A1 · Liang · 2009 [cited by applicant]
US 20090198678A1 · Conrad · 2009 [cited by applicant]
US 20090240744A1 · Thomson et al. · 2009 [cited by applicant]
US 20090290813A1 · He · 2009 [cited by applicant]
US 20090297050A1 · Li et al. · 2009 [cited by applicant]
US 20090326919A1 · Bean · 2009 [cited by applicant]
US 20110029559A1 · Kikuchi et al. · 2011 [cited by applicant]
US 20110085739A1 · Zhang et al. · 2011 [cited by applicant]
US 20110313990A1 · Valdes-Perez et al. · 2011 [cited by applicant]
US 20120036125A1 · Al-Kofahi et al. · 2012 [cited by applicant]
US 20120158633A1 · Eder · 2012 [cited by applicant]
US 20120192055A1 · Antebi et al. · 2012 [cited by applicant]
US 20120215727A1 · Malik · 2012 [cited by applicant]
US 20130080457A1 · Narayanan et al. · 2013 [cited by applicant]
US 20130138661A1 · Lu et al. · 2013 [cited by applicant]
US 20130138669A1 · Lu et al. · 2013 [cited by applicant]
US 20130191376A1 · Zhiyanov · 2013 [cited by examiner]
US 20130346396A1 · Stamm et al. · 2013 [cited by applicant]
US 20140040275A1 · Dang · 2014 [cited by examiner]
US 20140129535A1 · Riley et al. · 2014 [cited by applicant]
US 20140173426A1 · Huang et al. · 2014 [cited by applicant]
US 20150324454A1 · Roberts et al. · 2015 [cited by applicant]
US 20160012336A1 · Franceschini et al. · 2016 [cited by applicant]
US 20160147871A1 · Kalyanpur · 2016 [cited by applicant]
US 20160378855A1 · Roberts et al. · 2016 [cited by applicant]
US 20170017708A1 · Fuchs · 2017 [cited by applicant]
US 20170017716A1 · Joshi · 2017 [cited by applicant]
US 20180189708A1 · Senapaty · 2018 [cited by applicant]
US 20180349511A1 · Kleiman-weiner et al. · 2018 [cited by applicant]
US 20180349517A1 · Kleiman-weiner et al. · 2018 [cited by applicant]
US 20200320111A1 · Roberts et al. · 2020 [cited by applicant]
CN 1965314 · 2007 [cited by applicant]
CN 101427208 · 2009 [cited by applicant]
CN 101470747 · 2009 [cited by applicant]
CN 101796508 · 2010 [cited by applicant]
CN 103229168A · 2013 [cited by applicant]
CN 105183770 · 2015 [cited by applicant]
CN 105893481 · 2016 [cited by applicant]
CN 106021229 · 2016 [cited by applicant]
JP H09218881 · 1997 [cited by applicant]
JP 2005251157 · 2005 [cited by applicant]
JP 2008250623 · 2008 [cited by applicant]
JP 2012150677 · 2012 [cited by applicant]
JP 2019066979A · 2019 [cited by applicant]
WO WO2002054292 · 2002 [cited by applicant]
WO WO2003005235 · 2003 [cited by applicant]
WO WO2005111868 · 2006 [cited by applicant]
WO WO2006031741 · 2006 [cited by applicant]
WO WO2006035196 · 2006 [cited by applicant]
WO WO2012109083 · 2012 [cited by applicant]
WO WO2015175548 · 2015 [cited by applicant]
WO 2017138057A1 · 2017 [cited by applicant]
Extended European Search Report for Application No. 19825458.3, dated Feb. 18, 2022, 14 pages. [cited by applicant]
Japanese Office Action issued in App. No. JP2020572428, dated Aug. 1, 2023, 5 pages. [cited by applicant]
Archagon, “Data Laced with History: Causal Trees & Operational CRDTs”, http://archagon.net/blog/2018/03/24/data-laced-with-history/ Mar. 24, 2018 , 65 pages. [cited by applicant]
Grishchenko, Victor , “Deep Hypertext with Embedded Revision Control Implemented in Regular Expressions”, Grishchenko, Victor S . . . “Deep hypertext with embedded revision control implemented in regular expressions.” I… [cited by applicant]
Winkler, Rolfe , “Getting More than Just Words in a Google Search Result”, The Wall Street Journal Aug. 19, 14 , 1 Page. [cited by applicant]
“Help: Infobox”, Wikipedia—https://en.wikipedia.org/wiki/help:infobox Mar. 5, 2015 , 6 Pages. [cited by applicant]
“Greasemonkey”, Wikipedia—http://en.wikipedia.org/wiki/greasemonkey Mar. 28, 2005 , 5 Pages. [cited by applicant]
Musto, et al., “Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data”, 2016 , 9 pages. [cited by applicant]
Marie, Nicolas , “Linked data based exploratory search”, 2015 , 295 pages. [cited by applicant]
Fellner, et al., “Adaptive Semantics Visualization”, 2014 , 360 pages. [cited by applicant]
Chekima, et al., “Document Recommender Agent Based on Hybrid Approach”, 2014 , 6 pages. [cited by applicant]
KBA, “TREC KBA 2014: Accelerate & Create”, TREC Knowledge Base Acceleration; KBA a TREC evaulation 2014 , 1 Page. [cited by applicant]
KBA, “TREC KBA 2014: Overview”, TREC Knowledge Base Acceleration; KBA a TREC evaulation 2014 , 3 Pages. [cited by applicant]
KBA, “TREC KBA 2014: Streaming Slot Filling”, TREC Knowledge Base Acceleration; KBA a TREC evaluation 2014 , 3 Pages. [cited by applicant]
KBA, “TREC KBA 2014: Technical Details”, TREC Knowledge Base Acceleration 2014 , 2 Pages. [cited by applicant]
KBA, “TREC KBA 2014: Vital Filtering”, TREC Knowledge Base Acceleration; KBA a TREC evaulation 2014 , 4 pages. [cited by applicant]
Cordier, Amelie et al., “Trace-Based Reasoning—Modeling Interaction Traces for Reasoning on Experiences”, 2013 , 6 pages. [cited by applicant]
Morais, et al., “A Multi-Agent Recommender System”, 2012 , 10 pages. [cited by applicant]
“VisualEditor”, MediaWiki.org—https://www.mediawiki.org/wiki/visualeditor May 15, 2011, 4 pages. [cited by applicant]
Popov, et al., “Connecting the Dots: A Multi-pivot Approach to Data Exploration”, 2011 , 16 pages. [cited by applicant]
Nesic, et al., “Semantic Document Architecture for Desktop Data Integration and Management”, 2010 , 228 pages. [cited by applicant]
Nesic, et al., “Semantic Document Model to Enhance Data and Knowledge Interoperability”, 2010 , 26 pages. [cited by applicant]
Kboubi, et al., “Semantic Visualization and Navigation in Textual Corpus”, 2010, 11 pages. [cited by applicant]
Eck, Adam et al., “Intelligent User Interfaces with Adaptive Knowledge Assistants”, 2009 , 20 pages. [cited by applicant]
Nesic, et al., “Extending MS Office for sharing Document Content Units”, 2008 , 4 pages. [cited by applicant]
Marivate, Vukosi N. et al., “An Intelligent Multi-Agent Recommender System for Human Capacity Building”, 2007 , 6 pages. [cited by applicant]
Sauermann, et al., “Overview and Outlook on the Semantic Desktop”, 2005 , 18 pages. [cited by applicant]
Chen, James R. et al., “A Distributed Multi-Agent System for Collaborative Information Management and Sharing”, 2000 , 7 pages. [cited by applicant]
“Recommender System”, Wikipedia—https://en.wikipedia.org/wiki/recommender_systems May 2, 2015 , 13 Pages. [cited by applicant]
“Wikipedia: User Scripts”, Wikipedia—http://en.wikipedia.org/wiki/wikipedia:user_scripts May 2, 2015 , 26 Pages. [cited by applicant]
Fakultat, et al., “A Semantics-based User Interface Model for Content Annotation, Authoring and Exploration”, 1984 , 202 pages. [cited by applicant]
Shapiro, Marc et al., “A comprehensive study of Convergent and Commutative Replicated Data Types”, Inria—Centre Paris-Rocquencourt; INRIA. Jan. 13, 2011 , 51 Pages. [cited by applicant]
“Office Assistant”, Wikipedia—https://en.wikipedia.org/wiki/office_assistant May 11, 2015 , 6 Pages. [cited by applicant]
Spiewak, Daniel , “Understanding and Applying Operational Transformation”, http://www.codecommit.com/blog/java/understanding-and-applying-operational-transformation. Understanding and Applying Operational Transformation… [cited by applicant]
Githubgist, “A Bluffers Guide to CRDTs in Riak”, https://gist.github.com/russelldb/f92f44bdfb619e089a4d , 10 Pages Total. [cited by applicant]
Preguica, Nuno et al., “A commutative replicated data type for cooperative editing”, A commutative replicateddata type for cooperative editing. 29th IEEE International Conference on Distributed Computing Systems (ICDCS … [cited by applicant]
“U.S. Appl. No. 15/055,984 Final Office Action mailed Apr. 4, 2019”, 17 pages. [cited by applicant]
“U.S. Appl. No. 15/055,984 Non-Final Office Action mailed Jul. 9, 2018”, 18 pages. [cited by applicant]
“U.S. Appl. No. 15/055,984 Notice of Allowance mailed Oct. 2, 2019”, 13 pages. [cited by applicant]
“U.S. Appl. No. 16/001,874 Final Office Action mailed May 1, 2019”, 10 pages. [cited by applicant]
“U.S. Appl. No. 16/001,874 Non-Final Office Action mailed Sep. 18, 2019”, 30 pages. [cited by applicant]
“U.S. Appl. No. 16/001,874 Non-Final Office Action mailed Sep. 28, 2018”, 42 pages. [cited by applicant]
“U.S. Appl. No. 16/001,874 Notice of Allowance mailed Oct. 7, 2020”, 7 pages. [cited by applicant]
“U.S. Appl. No. 16/001,884 Notice of Allowance mailed Dec. 28, 2020”, 8 pages. [cited by applicant]
WIPO, “Application No. PCT/US19/39051 International Preliminary Report on Patentability mailed Jan. 7, 2021”, 13 pages. [cited by applicant]
“U.S. Appl. No. 14/710,342, Non-Final Office Action mailed Jun. 16, 2015”, 19 pages. [cited by applicant]
“U.S. Appl. No. 14/710,342, Final Office Action mailed Nov. 10, 2015”, 20 pages. [cited by applicant]
“U.S. Appl. No. 14/710,342, Notice of Allowance mailed Jan. 15, 2016”, 17 pages. [cited by applicant]
“U.S. Appl. No. 16/001,874 Notice of Allowance mailed Jun. 22, 2020”, 15 pages. [cited by applicant]
“U.S. Appl. No. 16/001,884 Non-Final Office Action mailed May 15, 2020”, 23 pages. [cited by applicant]
CNIPA, “CN Application No. 201580037649.3 First Office Action mailed Aug. 2, 2019”, English and Chinese Translations , 19 pages. [cited by applicant]
Shapiro, Marc , “Conflict-free Replicated Data Types”, Marc Shapiro, Nuno Pregui ca, Carlos Baquero, Marek Zawirski. Conflict-free Replicated Data Types. [Research Report] RR-7687, INRIA. 2011, pp. 18. , 22 Pages Total. [cited by applicant]
Fraser, Neil , “Differential Synchronization”, Differential Synchronization by Neil Fraser, Jan. 2009. Google. , 8 Pages Total. [cited by applicant]
EPO, “EP Application Serial No. 15792362.4 Communication Pursuant to Article 94(3) mailed Sep. 24, 2018”, 8 pages. [cited by applicant]
EPO, “EP Application Serial No. 15792362.4, Extended Search Report mailed Sep. 6, 2017”, 9 pages. [cited by applicant]
U.S. Searching Authority, “International Application Serial No. PCT/US15/30400, Search Report and Written Opinion mailed Aug. 27, 2015”, 9 pages. [cited by applicant]
Weiss, Stephane et al., “Logoot-Undo: Distributed Collaborative Editing System on P2P networks”, Logoot-Undo: Distributed Collaborative Editing System on P2P networks Stéphane Weiss, Pascal Urso, Pascal Molli Nancy-Univ… [cited by applicant]
Ahmend-Nacer, Mehdi et al., “Merging OT and CRDT Algorithms”, Mehdi Ahmed-Nacer, Pascal Urso, Valter Balegas, Nuno Pregui ca. Merging OT and CRDT Algorithms. 1st Workshop on Principles and Practice of Eventual Consisten… [cited by applicant]
Wikipedia, “Operational transformation”, https://en.wikipedia.org/wiki/Operational_transformation#Basics , 10 Pages Total. [cited by applicant]
Sun, Chengzheng et al., “Operational Transformation in Real-Time Group Editors: Issues, Algorithms, and Achievements”, Appeared in Proc. of 1998 ACM Conference on ComputerSupported Cooperative Work, Seattle, USA, Nov. 1… [cited by applicant]
WIPO, “PCT Application No. PCT/US15/30400 International Preliminary Report on Patentability mailed Nov. 24, 2016”, 7 pages. [cited by applicant]
WIPO, “PCT Application No. PCT/US18/36345 International Preliminary Report on Patentability mailed Dec. 19, 2019”, 10 pages. [cited by applicant]
ISA, “PCT Application No. PCT/US18/36345 International Search Report and Written Opinion mailed Aug. 31, 2018”, 11 pages. [cited by applicant]
ISA, “PCT Application No. PCT/US19/39051 International Search Report and Written Opinion mailed Sep. 13, 2019”, 14 pages. [cited by applicant]
Oster, Gerald et al., “Real time group editors without Operational transformation”, G'erald Oster, Pascal Urso, Pascal Molli, Abdessamad Imine. Real time group editors without Operational transformation. [Research Repor… [cited by applicant]
Burckhardt, Sebastian et al., “Replicated Data Types: Specification, Verification, Optimality”, Replicated Data Types: Specification, Verification, Optimality. POPL 2014: 41st ACM SIGPLAN-SIGACT Symposium on Principles … [cited by applicant]
Attiya, Hagit et al., “Specification and Complexity of Collaborative Text Editing”, PODC'16, Jul. 25-28, 2016, Chicago, IL, USA. ISBN 978-1-4503-3964-Mar. 16, 2007. DOI: http://dx.doi.org/10.1145/2933057.2933090 , 10 Pa… [cited by applicant]
Lamport, Leslie , “Time, Clocks, and the Ordering of Events in a Distributed System”, Massachusetts Computer Associates, Inc. Jul. 1978 vol. 21 No. 7 , pp. 558-565. [cited by applicant]
Levien, Raph , “Towards a unified theory of Operational Transformation and CRDT”, Jul. 6, 2016.https://medium.com/@raphlinus/towards-a-unified-theory-of-operational-transformation-and-crdt-70485876f72f , 9 Pages Total. [cited by applicant]
Taylor, Aaron M. et al., “Unpublished U.S. Appl. No. 17/100,697, filed Oct. 20, 2020”, 38 Pages. [cited by applicant]
Pavlini, Emily B. et al., “Unpublished U.S. Appl. No. 17/133,764, filed Dec. 24, 2020”, 93 Pages. [cited by applicant]
Chinese Office Action issued in App. No. CN201980055147, dated Jun. 17, 2024, 9 pages. [cited by applicant]
Chinese Office Action issued in App. No. CN201980055147, dated Feb. 2, 2024, 17 pages. [cited by applicant]
Japanese Office Action (including English translation) issued in App. No. JP2020-572428, dated Jan. 23, 2024, 5 pages. [cited by applicant]
European Patent Officie Communication pursuant to Article 94(3) issued in App. No. EP19825458.3, dated Feb. 15, 2024, 7 pages. [cited by applicant]