DETAILED ACTION
This action is responsive to the application filed 4/17/2024.
Claims 1-18 are pending.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 14, 15, 17 and 18 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor regards as the invention.
Claims 14 and 15 recite dependence from Claim 12, however they appear to be intended to depend from Claim 13. Similarly, Claims 17 and 18 are intended to depend from Claim 16, but recite dependence from Claim 15. As a result, the claims lack antecedent basis; appropriate correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-18 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Sobhy Deraz, U.S. PGPUB No. 2024/0303441 (“Deraz”).
With regard to Claim 1, Deraz teaches a content generation system for generating a content, comprising:
at least one user interface, at least one memory, at least one processor configured to execute at least one program stored in said at least one memory and connected to said at least one memory ([0110]), wherein said at least one program is programmed to be executed by said at least one processor to:
(A) utilize both a Large Language Model (LLM) that operates using communicative human language information entered through said at least one user interface, and a visualization software programmed to output visual information using text information ([0040] describes a spreadsheet program accessible through a user interface, where the operational environment also includes a LLM service),
(B) acquire first communicative human language information to be included in the content by the LLM using at least a part of the communicative human language information entered through said at least one user interface ([0094] describes that user inputs are submitted to the LLM making queries regarding the spreadsheet data; [0095] describes that the LLM acquires at least a sample of the spreadsheet data as well as column and row headers),
(C) acquire second communicative human language information by the LLM for selecting the visualization software that is configured to generate the visual information to be included in the content, based on at least a part of the communicative human language information entered through said at least one user interface, and select the visualization software based on the acquired second communicative human language information ([0094]-[0095] describe that user-entered natural language inputs cause the LLM to determine which tool is suited for answering the query; the LLM also determines a type of analysis to be carried out using the tool),
(D) acquire the visual information to be included in the content by operating the selected visualization software using the text information, which is based on an output of the LLM in correspondence to the communicative human language information entered through said at least one user interface ([0094]-[0096] describes that the response to the user inputs involve submitting inputs to a next node to carry out the selected analysis, using the selected tool to produce visual information in the form of the specified analysis, such as a table, or forecasting, or what if analysis. [0081] describes various other things a LLM can be tasked with generating, such as designing tables and data visualization),
(E) generate the content including at least a part of the first communicative human language information, or a modification thereof, acquired from (B), and at least a part of the visual information, or a modification thereof, acquired from (D) ([0096] describes that the LLM passes the task to the next node to execute the analysis. [0090] describes a scenario where a table is created using the spreadsheet data and column names), and
(F) output the generated content through said at least one user interface ([0053]-[0054] describe that outputs can be displayed as suggestions for adding to an existing or new workbook, including created scenarios and tables. [0089] further describes outputs including routines for creating charts and tables).
With regard to Claim 2, Deraz teaches that the visualization software is selected by the content generation system, not by a user. [0095] describes that the LLM classifies a user’s input in order to determine which supporting tool or service to query to provide the proper response.
With regard to Claim 3, Deraz teaches that the content generation system is configured so as not to be embedded in any specific visualization software and not to be associated only with any specific visualization software. [0040] describes that the application service and LLM service operate by hosting a productivity application. The productivity application can be a spreadsheet application, however the environment is not limited to a specific software or exclusively associated therewith; the spreadsheet environment may operate in the context of another application such as a presentation or word processing application.
With regard to Claim 4, Deraz teaches that the visualization software is data visualization software or includes a visual-based model. [0040] describes that the software includes a spreadsheet application, where [0089] describes creation of visualizations such as tables and charts. [0095] describes additional available tools for additional modeling and visualization options.
With regard to Claim 5, Deraz teaches that the at least one program is programmed to be executed by the at least one processor such that: in the step (C), if the second communicative human language information acquired by the LLM includes information indicating a name of the visualization software, then the visualization software is selected based on that name, or a web search is performed using the second communicative human language information acquired by the LLM, and then the visualization software is selected based on information acquired from the web search. [0095] describes that a user input is converted into a request template, which specifies a specific type of analysis that is then used to select the particular tool or service, using the specific name.
With regard to Claim 6, Deraz teaches that the communicative human language information entered through said at least one user interface includes subject matter of the content, and the content is generated to promote a user’s understanding or provide detailed explanations or descriptions about the subject matter included in the communicative human language information entered through said at least one user interface. [0095] describes that the various types of content analysis available respond to particular queries. Fig. 7B shows that user inputs request information on particular subjects such as customer preferences, business growth, discounts, etc.
With regard to Claim 7, Deraz teaches that the communicative human language information entered through said at least one user interface includes subject matter of the content and is a query that consists of a command, a request, or a question, or a combination thereof, and the content is generated to explain or describe the subject matter in accordance with the query. Fig. 7B shows various questions for which content is generated include various subjects related to the data, and questions thereabout. [0096] describes that the LLM generates the responses, which are passed to the proper service for performing the task.
With regard to Claim 8, Deraz teaches that the first communicative human language information in the content has a larger text count than the communicative human language information entered through said at least one user interface. [0089] describes examples where users create a variety of tables and charts using information such as a shopping list. [0090] describes that columns can be added to the existing content as well.
With regard to Claim 9, Deraz teaches that the first communicative human language information and the visual information included in the content are mutually related and are also related to subject matter of the content. [0095]-[0096] describe that the analyses is carried out and the content generated by identifying the type of analysis requested based on the contextual information, including data and headers from the spreadsheet.
With regard to Claim 10, Deraz teaches that the visual information is added to supplement explanations or descriptions made by the communicative human language information in the content. [0095] describes that the various data analyses are of a type to provide additional understanding of the content, such as forecasting or what if analysis. [0092] describes additional use of Insights and other data analysis tools.
With regard to Claim 11, Deraz teaches that the visual information is either an image which is static visual information, or a video which is dynamic visual information, and the image encompasses visualizations, and the video encompasses animations or simulations. [0089] describes that the system can create pivot charts in response to user input.
With regard to Claim 12, Deraz teaches that at least one program is further programmed to be executed by said at least one processor to utilize the visualization software after the visualization software is selected, as the visualization software to be selected is not determined before the start of use of the content generation system. [0095] describes that the tool or service that is to be used to carry out a particular analysis is determined by the LLM in response to the prompt entered by the user, and not before the system has begun to be used.
With regard to Claim 13, Deraz teaches a system for generating a content in response to an input in communicative human language, the system being configured to communicate with:
a user terminal device configured to receive the input in the communicative human language, to thereby generate communicative human language (CHL) information, and output the generated content (Fig. 1, devices 130 entering data into spreadsheets),
a first server configured to provide a Large Language Model (LLM), and a second server configured to provide a plurality of pieces of visualization software (Fig. 1, application service 110 and LLM service 120), the system comprising:
a processor; and a non-transitory storage medium containing program instructions ([0110]), execution of which by the processor causes the system to:
receive the CHL information from the user terminal device; send the CHL information to the first server, to thereby obtain a first output of the LLM, the first output including output content in the communicative human language ([0095]);
resend the CHL information to the first server, to thereby obtain a second output of the LLM, the second output including information designating one of the plurality of pieces of visualization software ([0095]);
further resend the CHL information to the first server, to thereby obtain a third output of the LLM, the third output including text information for the designated one of the plurality of pieces of visualization software ([0095]);
send the text information to the second server, to thereby obtain output content including visual information from the designated one of the plurality of pieces of visualization software ([0095]-[0096]);
generate the content based on both the output content in the communicative human language, and the output content including the visual information ([0095]-[0096]; and
send the generated content to the user terminal device to be outputted thereby ([0090], [0096]).
Claim 16 recites a method carried out by the system of Claim 12, and the claim is similarly rejected.
With regard to Claim 14, Deraz teaches that at least one of the first and second servers include a plurality of server devices that communicate with one another ([0042]-[0043]).
Claim 17 recites a method carried out by the system of Claim 14, and the claim is similarly rejected.
With regard to Claim 15, Deraz teaches that the content generated by the system further includes at least one of a modification of the output content in the communicative human language, and a modification of the output content including the visual information ([0090]).
Claim 18 recites a method carried out by the system of Claim 15, and the claim is similarly rejected.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Kummamuru, et al., U.S. Patent No. 10,896,214 discloses a system and method for AI-based generation of data visualizations.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEITH D BLOOMQUIST whose telephone number is (571)270-7718. The examiner can normally be reached M-F, 8:30-5 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kieu Vu can be reached at 571-272-4057. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KEITH D BLOOMQUIST/Primary Examiner, Art Unit 2171
1/29/2026