IP Library › Granted Patent US 12,126,768
Granted Patent B2
US 12,126,768 · App. 18/304,190 · Granted Oct 22, 2024

System and methods for chatbot and search engine integration

Inventors: Geoff Willshire (Greenslopes, AU); Florian Treml (Klausen-Leopoldsdorf, AT); Christoph Börner (Vienna, AT)
H04M3/493G06F16/22G10L15/22H04M3/24H04M3/4938H04M7/1295G06F16/24
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Quick Facts
Patent No.
US 12,126,768
App. No.
18/304,190
Filed
Apr 20, 2023
Granted
Oct 22, 2024
Kind
B2
Art Unit
2692
USPC
379/88.01
Abstract

A system and method for chatbot and search engine integration comprising chatbot crawler engine configured to detect all possible paths through a conversational flow between a chatbot and a user, and also comprising a chatbot search integration manager configured to receive a processed conversation flow from the chatbot crawler engine, parse the conversation flow to identify keywords and features, and build an indexable data structure which can be integrated into search engines in order to expose the information and data contained within the chatbot's knowledge base. This integration may allow search engine users to be redirected to a website hosting the chatbot when an indexed data structure comprises information relevant to a search engine query.

Claims (41)

1. A system for integrating a chatbot with a search engine, comprising:

a chatbot crawler comprising a first plurality of programming instructions stored in a nontransitory, computer-readable memory of, and operating on a processor of, a computing device, wherein the first plurality of programming instructions, when operating on the processor, cause the computing device to:

connect to an enterprise chatbot and traverse a conversation flow detecting one or more conversation paths;

for each detected conversation path generate a flow chart and a conversation; and

send the flow chart to a chatbot search integration manager; and

the chatbot search integration manager comprising a second plurality of programming instructions stored in the memory of, and operating on the processor of, the computing device, wherein the second plurality of programming instructions, when operating on the processor, cause the computing device to:

extract one or more index keywords from a flow chart received from the chatbot crawler;

store a data structure comprising the index keywords in a database; and

connect to a search engine, wherein the search engine's built in crawler crawls the data structure and assigns a page rank to the data structure.

2. The system of claim 1 , wherein the chatbot integration manager parses the flow chart according to a graph traversal algorithm.

3. The system of claim 1 , wherein the data structure is a static HyperText Markup Language webpage.

4. The system of claim 1 , wherein the assigned page rank is associated with the data structure and stored in the database.

5. The system of claim 1 , further comprising a machine learning algorithm configured to determine an optimal format for the data structure.

6. The system of claim 5 , further comprising a page optimization engine comprising a third plurality of programming instructions stored in the memory of, and operating on the processor of, the computing device, wherein the third plurality of programming instructions, when operating on the processor, cause the computing device to:

receive the data structure;

use the data structure as an input into the machine learning algorithm, wherein the machine learning algorithm outputs an optimized data structure format; and

send the machine learning output to the chatbot search integration manager.

7. The system of claim 6 , wherein the chatbot search integration manager creates a data structure using the received machine learning output as the format for the data structure.

8. The system of claim 5 , wherein the machine learning algorithm is a neural network.

9. The system of claim 5 , wherein the machine learning algorithm is configured by training the algorithm on training data comprising at least static webpages and for each static webpage an associated with page rank.

10. The system of claim 6 , wherein the page optimization engine retrieves the assigned page rank of the data structure and determines if the format is optimal by comparing the page rank to a predetermined threshold value.

11. A method for integrating a chatbot with a search engine, comprising the steps of:

connecting to an enterprise chatbot and traverse a conversation flow detecting one or more conversation paths;

generating a flow chart and a conversation for each detected conversation path;

sending the flow chart to a chatbot search integration manager;

using the chatbot search integration manager:

extracting one or more index keywords from the flow chart received from the chatbot crawler;

storing a data structure comprising the index keywords in a database; and

connecting to a search engine, wherein the search engine's built in crawler crawls the data structure and assigns a page rank to the data structure.

12. The method of claim 11 , wherein the chatbot integration manager parses the flow chart according to a graph traversal algorithm.

13. The method of claim 11 , wherein the data structure is a static HyperText Markup Language webpage.

14. The method of claim 11 , wherein the assigned page rank is associated with the data structure and stored in the database.

15. The method of claim 11 , further comprising a machine learning algorithm configured to determine an optimal format for the data structure.

16. The method of claim 15 , further comprising the steps of:

receiving the data structure;

using the data structure as an input into the machine learning algorithm, wherein the machine learning algorithm outputs an optimized data structure format; and

sending the machine learning output to the chatbot search integration manager.

17. The method of claim 16 , wherein the chatbot search integration manager creates a data structure using the received machine learning output as the format for the data structure.

18. The method of claim 15 , wherein the machine learning algorithm is a neural network.

19. The method of claim 15 , wherein the machine learning algorithm is configured by training the algorithm on training data comprising at least static webpages and for each static webpage an associated with page rank.

20. The method of claim 16 , wherein the page optimization engine further performs the steps of: retrieving the assigned page rank of the data structure and determining if the format is optimal by comparing the page rank to a predetermined threshold value.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 30, 2024
From: WILLSHIRE, GEOFF
To: CYARA SOLUTIONS PTY LTD
Reel/Frame 069079/0560 →
Continuity (9)
Continuation 17943095 · Sep 12, 2022
Continuation In Part 17896024 · Aug 25, 2022
Continuation In Part 16985652 · Aug 5, 2020
Continuation In Part 16379084 · Apr 9, 2019
Continuation 15091556 · Apr 5, 2016
Continuation In Part 14590972 · Jan 6, 2015
Provisional Application 63354616 · Jun 22, 2022
Provisional Application 63354618 · Jun 22, 2022
Related Publication 20230370547A1 · Nov 16, 2023
Cited By (1)
US 12,712,830