DETAILED ACTION
Claims 1-20 are pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 3/13/2025 is being considered by the examiner.
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 1-9 and 11-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Chen (US 2024/0403313 A1).
With regards to Claim 1, Chen teaches a computer-implemented method comprising: obtaining, by at least one computing device, data (i.e., At operation 305, the user provides a dataset, Paragraph 79; Figure 3) and an intent of an entity relating to the data (i.e., At operation 315, the user selects a query from the set of queries, Paragraph 83; Figure 3; Intent is equivalent to the queries, user’s request to understand the data); automatically generating, by the at least one computing device, a set of analysis paths for the entity based, at least on the data and the intent, the automatically generating using an artificial intelligence application executing on the at least one computing device, the artificial intelligence application including one or more models trained to generate the set of analysis paths, the set of analysis paths including one or more analysis paths (i.e., Figures 3-6; Paragraph 21; data analysis model; analysis thread and data visualization); creating, using the at least one computing device, a visualization of the sent of analysis paths (i.e., At operation 325, the system displays the answer to the query and the additional data visualization, Paragraph 87; According to some embodiments, data analysis interface 235 displays a data visualization in a first region of data analysis interface 235. In some examples, data analysis interface 235 displays an analysis thread visualization in a second region of data analysis interface 235, where the analysis thread visualization depicts an analysis thread graph including a first node corresponding to the data visualization and an edge corresponding to an analysis path between the first node and a second node, Paragraph 52); and displaying, using the at least one computing device, the visualization of the set of analysis paths (Figure 7)
With regards to Claim 2, Chen teaches receiving, based on interaction of the entity with the visualization of the set of analysis paths, interaction signals of the visualization; and automatically revising the visualization based on the interaction signals to further define the set of analysis paths (i.e., As an example shown in FIG. 6, two branches corresponding to diverging exploration on the Weight and Acceleration are presented. By hovering over third node 650 and fourth node 655, a small version of the corresponding visualization appears or pops up as a tooltip…, Paragraph 105; Selecting these questions to insert new cells into the notebook containing stacked bar charts where the color encodes the new data attribute (Origin or Cylinders). The data analysis model updates analysis thread visualization 635 to show the newly diverging analysis trajectories…, Paragraph 106; Figure 6)
With regards to Claim 3, Chen teaches wherein the interactions include one or more actions selected from a group of actions comprising comparing, exploring and regenerating at least one analysis path of the set of analysis paths (i.e., Selecting these questions to insert new cells into the notebook containing stacked bar charts where the color encodes the new data attribute (Origin or Cylinders). The data analysis model updates analysis thread visualization 635 to show the newly diverging analysis trajectories…, Paragraph 106; Figure 6)
With regards to Claim 4, Chen teaches wherein the exploring includes performing at least one action selected from a set of actions comprising viewing additional exogeneous information relating to the data and retrieved form exogeneous sources, displaying additional details relating to at least one analysis path of the set of analysis paths, and requesting further information based on information extracted from the data based on the intent (i.e., In some examples, data analysis interface 235 displays a set of queries in a third region of data analysis interface 235. In some examples, data analysis interface 235 receives user input selecting the query corresponding to the second node. Data analysis interface 235 displays an additional data visualization corresponding to the second node based on the user input, Paragraph 53; Paragraph 55)
With regards to Claim 5, Chen teaches wherein the visualization is a computer-generated node-link diagram in which the one or more analysis paths are represented as nodes in the computer-generated node-link diagram (i.e., Data analysis apparatus 110 displays, via the data analysis interface, an analysis thread visualization in a second region of the data analysis interface. The analysis thread visualization depicts an analysis thread graph including a first node (e.g., node “A”) corresponding to the data visualization and an edge corresponding to an analysis path between the first node and a second node (node “B”). In some examples, the analysis thread graph is a tree including a set of nodes. If two or more nodes are located on a same level of the analysis thread graph and the two or more nodes share a same parent node, the two or more nodes may be referred to as sibling nodes, Paragraph 36)
With regards to Claim 6, Chen teaches wherein the automatically generating the set of analysis paths includes: extracting, using the artificial intelligence application, information from the data based on the intent; and using the information in the automatically generating the set of analysis paths (i.e., In some embodiments, the data analysis model generates a set of next-step questions, via next-step recommendation heuristic, based on the dataset and the initial visualization. The data analysis apparatus runs heuristic algorithms that combine insight-based recommendation (i.e., starting from a visualization reflecting a specific data insight, searching for logically-related insights, and recommending them in the form of a follow-up question) and attribute-based recommendation (i.e., introducing insightful data attributes that are not fully explored) to guide data exploration. A user interacts with insight-related questions. After receiving user input (e.g., a user selects a query from candidate queries), the data analysis model generates text information (e.g., answer to the question) and an additional data visualization (e.g., a bar chart depicting the answer), Paragraph 21; Paragraph 23)
With regards to Claim 7, Chen teaches wherein the automatically generating the set of analysis paths further includes: retrieving additional information from one or more exogenous sources; and using the additional information in the automatically generating the set of analysis paths (i.e., As an example shown in FIG. 1, data analysis apparatus 110 receives a dataset from database 120 via e.g., cloud 115. The dataset contains a seed visualization (e.g., from a company dashboard), Paragraph 35; Paragraphs 80, 107, Figure 1)
With regards to Claim 8, Chen teaches wherein at least one of the creating and the displaying is performed using a visualization tool, and wherein the visualization tool facilitates collection and organization of the set of analysis paths (i.e., FIG. 2 shows an example of a data analysis apparatus 200 according to aspects of the present disclosure. The example shown includes data analysis apparatus 200, processor unit 205, memory unit 210, I/O module 215, training component 220, and data analysis model 225. In one embodiment, data analysis model 225 includes graph component 230, data analysis interface 235, query component 240, answer component 245, navigation component 250, and visualization component 255., Paragraph 45; Paragraphs 51-52, 59)
With regards to Claim 9, Chen teaches wherein at least one of the creating and the displaying is performed using a visualization tool, and wherein the visualization tool facilitates storing the set of analysis paths (i.e., According to some embodiments, graph component 230 adds a third node to the analysis thread graph based on the user input. Graph component 230 generates an analysis thread graph including a first node corresponding to a data visualization and an edge corresponding to an analysis path between the first node and a second node, Paragraph 51; According to an embodiment, data analysis model 255 records and stores the data analysis or data exploration history as a linear stream of separate notebook cells., Paragraph 151)
With regards to Claim 11, Chen teaches further comprising generating, by the artificial intelligence application, reasoning for the set of analysis paths, and wherein the displaying the visualization includes displaying the reasoning (i.e., In some cases, the data visualization takes the form of a chart, a graph, or other types of visual representation. For example, if the dataset includes a collection of sales data, the data visualization may be a bar chart showing the sale information for each month. The set of queries are generated based on the data visualization. For example, if the data visualization is a scatter plot showing the relationship between two variables, the data analysis apparatus generates a set of queries that include questions about insights related to the two variables, e.g., the strength of the relationship, reason behind the relationship, Paragraph 82)
With regards to Claim 12, Chen teaches wherein the visualization facilitates viewing by the entity one or more analysis paths already explored and one or more new analysis paths (i.e., In some embodiments, the data analysis model includes an interactive visualization panel (e.g., a visualization tree) to enable convenient analysis history browsing and quick navigation between different analysis threads. This way, users have increased awareness and control of the structure of their data exploration process. For example, a user can visualize notebook cells based on the analysis hierarchy to trace back through the history of the data exploration process and can be re-directed to a target cell containing a data visualization or a list of queries efficiently, Paragraph 22; …The data analysis model updates analysis thread visualization 635 to show the newly diverging analysis trajectories…, Paragraph 106)
The limitations of Claim 13 are rejected in the analysis of Claim 1 above, and the claim is rejected on that basis.
The limitations of Claim 14 are rejected in the analysis of Claim 2 above, and the claim is rejected on that basis.
The limitations of Claim 15 are rejected in the analysis of Claim 5 above, and the claim is rejected on that basis.
The limitations of Claim 16 are rejected in the analysis of Claim 6 above, and the claim is rejected on that basis.
The limitations of Claim 17 are rejected in the analysis of Claim 1 above, and the claim is rejected on that basis.
The limitations of Claim 18 are rejected in the analysis of Claim 2 above, and the claim is rejected on that basis.
The limitations of Claim 19 are rejected in the analysis of Claim 5 above, and the claim is rejected on that basis.
The limitations of Claim 20 are rejected in the analysis of Claim 6 above, and the claim is rejected on that basis.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Chen (US 2024/0403313 A1) in view of Nguyen (US 2025/0130779 A1).
With regards 10, Chen teaches the above disclosed subject matter. However, Chen does not explicitly disclose wherein at least one of the creating and displaying is performed using a visualization tool, and wherein the visualization tool provides a chat interaction to the entity to provide an interface with the visualization tool through natural language processing. Nguyen does teach wherein at least one of the creating and displaying is performed using a visualization tool, and wherein the visualization tool provides a chat interaction to the entity to provide an interface with the visualization tool through natural language processing (i.e., the user input may pertain to a dataset in a data file, and the user may input a filename or directory path of the file for upload. For example, a user working on a document of a word processing application may wish to generate a visualization relating to data in a spreadsheet file to include in the document. The user can enter a natural language input in a chat pane of the word processing application which relates to data in the spreadsheet file to generate a visualization to include in the document, Paragraph 22) in order to provide an iterative process of visualization generation (Paragraph 4). Therefore, based on Chen in view of Nguyen, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Nguyen with the system of Chen in order to provide an iterative process of visualization generation.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SURAJ M JOSHI whose telephone number is (571)270-7209. The examiner can normally be reached Monday - Friday 8-6 ET.
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/SURAJ M JOSHI/Primary Examiner, Art Unit 2447 July 22, 2026
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