Description:TECHNICAL FIELD
[001] The present invention relates to persona generation, and more particularly, the present invention relates to a system and a method for automated persona generation.
BACKGROUND ART
[002] Personas are currently created primarily by qualitative methods. The persona generation involve interviewing or surveying users, prospects and/or customers. While such methods provide depth of insights such as motivations and challenges/pain points, they are neither easily scalable to millions of data points nor amenable to frequent updates. As a result, persona related tools today are primarily limited to templates or visualization tools that rely on inputs from the user surveys/interviews. Accordingly, improvements to the automatic creation of user personas are desired. Further, the personas can be utilized in wide range of areas. One of such area utilizing personas is software development and testing.
[003] During software development and quality testing, identification and documentation of user requirements may have errors of negligence due to imperfect understanding of how users interact with software. A test plan is created and executed for different software, and for each released version of a given software. Hence, the testing is a costly and time-consuming process. Moreover, testing is often biased in reflecting ideal workflows rather than all possible user workflows.
[004] Accordingly, there exists a need for a system and a method for automated persona generation which can be utilized in many areas such as automated user-centric testing.
OBJECT OF THE INVENTION
[005] An object of the present invention is to develop a system for automated persona generation.
[006] Another object of the present invention is to provide a method of automated persona generation based user-centric testing.
SUMMARY OF THE INVENTION
[007] The present invention provides a system and a method for automated persona generation. The system comprising an application crawler, a persona generating module, a database, and a machine learning model.
[008] The application crawler is configured to crawl through the plurality of applications interacted by a user, gathers interaction data including possible pathways by interacting with elements of the plurality of application. The application crawler comprising an analysis module, an interaction engine, a data collection module, a user interaction handler, and a data export module. The persona generating module generates a persona based on the applicable paths and inputs received from the application crawler. The generated personas are stored in the database. The machine learning model serves as an integration hub for the application crawler and the persona generating module, providing OCR capabilities and generative data. The generated personas then can be retrieved for simulating real-world testing, design studies, feature coverage, and any applicable area. Additionally, the generated persona can be further trained by running the application crawler with the given persona, allowing the persona to adapt to new applications.
BRIEF DESCRIPTION OF THE DRAWINGS
[009] The embodiments can be better understood with reference to the following drawings and description. The components in the figures are not necessarily to scale, the emphasis instead being placed upon illustrating the principles of the embodiments. Moreover, the figures, like reference numerals designate corresponding parts throughout the different views.
[0010] Reference will be made to embodiments of the invention, examples of which may be illustrated in the accompanying figures. These figures are intended to be illustrative, not limiting. Although the invention is generally described in the context of these embodiments, it should be understood that it is not intended to limit the scope of the invention to these particular embodiments.
[0011] The objects and advantages of the present invention will become apparent when the disclosure is read in conjunction with the following figures, wherein
[0012] Figure 1 illustrates a flow chart of the method of automated persona generation, in accordance with the present invention;
[0013] Figure 2 illustrates a flow chart of the working of the application crawler, in accordance with the present invention; and
[0014] Figure 3 illustrate a working flow chart of the system of automated persona generation, in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION
[0015] The embodiments herein provide a system and a method for automated persona generation, configured to generate persona mimicking a person’s role based on real-world characteristics of the user and the applications they use.
[0016] Throughout this application, with respect to all reasonable derivatives of such terms, and unless otherwise specified (and/or unless the particular context clearly dictates otherwise), each usage of:
“a” or “an” is meant to read as “at least one”,
“the” is meant to be read as “the at least one.”
[0017] References in the specification to “one embodiment” or “an embodiment” mean that a particular feature, structure, characteristic, or function described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
[0018] Hereinafter, embodiments will be described in detail. For clarity of the description, known constructions and functions will be omitted.
[0019] Parts of the description may be presented in terms of operations performed by at least one processor, electrical/electronic circuit, a computer system, using terms such as data, state, link, fault, packet, and the like, consistent with the manner commonly employed by those skilled in the art to convey the substance of their work to others skilled in the art. As is well understood by those skilled in the art, these quantities take the form of data stored/transferred in the form of non-transitory, computer-readable electrical, magnetic, or optical signals capable of being stored, transferred, combined, and otherwise manipulated through mechanical and electrical components of the computer system; and the term computer system includes general purpose as well as special purpose data processing machines, switches, and the like, that are standalone, adjunct or embedded. For instance, some embodiments may be implemented by a processing system that executes program instructions so as to cause the processing system to perform operations involved in one or more of the methods described herein. The program instructions may be computer-readable code, such as compiled or non-compiled program logic and/or machine code, stored in a data storage that takes the form of a non-transitory computer-readable medium, such as a magnetic, optical, and/or flash data storage medium.
[0020] The present invention is illustrated with reference to the accompanying drawings, throughout which reference numbers indicate corresponding parts in the various figures. These reference numbers are shown in brackets in the following description.
[0021] In one of the exemplary embodiments of the present invention, the system (100) is configured for generating persona based on activities of a user in a plurality of applications. The system (100) is configured on a computing device. In an exemplary embodiment, the plurality of applications is configured on a computing device of a user. In an exemplary embodiment, the computing device is a laptop, a mobile phone, a smart phone, a personal computer, a tablet, and the like.
[0022] The system (100) comprising an application crawler (11), a persona generating module (12), a database (13), and a machine learning model (14).
[0023] The application crawler (11) is configured to crawl through the plurality of applications interacted by a user. The application crawler (11) identifies possible pathways by interacting with elements of the plurality of application. The application crawler (11) further requests data points from the user to facilitate progress within the application. Furthermore, the application crawler (11) gathers interaction data from the plurality of application. More particularly, the application crawler (11) comprising an analysis module, an interaction engine, a data collection module, a user interaction handler, and a data export module.
[0024] The analysis module examines the structure and a plurality of elements of the plurality of applications interacted by the user and maps the user flows therein. In an exemplary embodiment, the elements of the plurality of applications examined by the analysis module includes a plurality of buttons, a plurality of input fields, a plurality of dropdown menus, and other UI components. The plurality of applications provides different user interfaces (UI) to the user to interact with the applications. The interaction engine is configured to simulate the user interactions with user interface (UI) of the plurality of application. Additionally, the interaction engine populates forms and input fields with appropriate data to progress through different application states. The interaction engine further navigates between different sections and levels of the application. The analysis module and the interaction engine gather interaction data. The interaction data are then fed the data collection module. In an exemplary embodiment, the interaction data includes simulated user actions, system responses, error scenarios, and error handling mechanisms.
[0025] The user interaction handler requests the user input for human assistance in complex decision points. Further, the user interaction handler processes the input received from the user and provides it to the data collection module. The data export module exports data gathered by the data collection module.
[0026] In an exemplary embodiment, the data exported by the data export module includes path data of user journeys through the plurality of applications, a catalog of the data required at various points in the application, and a plurality of user behavior patterns.
[0027] The persona generating module (12) generates a persona based on the applicable paths and inputs received from the application crawler (11). The generated personas are stored in the database (13). The generated personas then can be retrieved for simulating real-world testing, design studies, feature coverage, and any applicable area. Additionally, the generated persona can be further trained by running the application crawler (11) with the given persona, allowing the persona to adapt to new applications.
[0028] The machine learning model (14) serves as an integration hub for the application crawler (11) and the persona generating module (12), providing OCR capabilities and generative data. The machine learning model (14) configured to enable the application crawler (11) and the persona generating module (12) to comprehensively understand the plurality of applications and provide the necessary inputs to progress to a next task.
[0029] In another embodiment of the present invention, the method for automated persona generation is configured to generate persona mimicking a person’s role based on real-world characteristics of the user and the applications they use.
[0030] The method for automated persona generation comprising a plurality of steps as disclosed below for generating personas. In a first step, the application crawler (11) crawls (101) through a plurality of applications interacted by a user. In an exemplary embodiment, in this step, the system runs the application under test and starts collecting data about the system while navigating through the site. By crawling, the application crawler (11) understands the structure, categories input, builds navigation paths and outputs of the said paths. The application crawler (11) may use any information available to it for generation of such pathways.
[0031] The application crawler (11) gathers the raw interaction data from the plurality of applications, and provides (102) this raw interaction data to the machine learning model (14) for processing thereof. The machine learning model (14) processes the raw interaction data and sends the processed interaction data to the application crawler (11). The application crawler (11) provides (103) this processed interaction data to the persona generating module (12) to build multiple personas for the given application under test. In an exemplary embodiment, the interaction data includes structure and a plurality of elements of the plurality of applications.
[0032] In an exemplary embodiment, at times the persona generating module (12) may decide that the processed data might not be enough to generate the required persona. During this time the persona generating module (12) requests (104) the machine learning model (14) to generate more static data for the various inputs required to satisfy the persona. On request, the machine learning model (14) provides a plurality of additional insights to the persona generating module (12). The personal generating module (12) generates a persona of the user interacting the plurality of applications. The generated persona is then stored (105) in the database (13). In an exemplary embodiment, the plurality of insights includes application interaction patterns of user, potential user preferences, and static data for the various user inputs.
[0033] The method further receives new interaction data of the plurality of applications, time by time or on request (106), by the persona generating module (12) from the application crawler (11). Based on this additional data received from the application crawler (11), the persona generating module (12) updates (107) and trains the generated persona. This is useful when certain personas of an application are already created and changes in the application under test are to be applied to the existing datasets.
[0034] Further, the generated persona is utilized by the application crawler (11) to automate (108) flows or test paths in the application assuming the persona as the user.
[0035] Additionally, the generated persona is utilized for crawling (109) through a plurality of applications to collect a plurality of required inputs and pathways for the usage of the system. In an exemplary embodiment, crawling with a persona differs from a crawl without a persona because the persona decides which inputs are required for the usage of the system and provides inputs based on the data typically given by that persona. However, non-persona-based crawl is not built with the output functionality (i.e. testing) in mind and serves only to scan the system for all of its inputs and pathways.

ADVANTAGES OF THE INVENTION
1. The present invention facilitates persona generation using user activity in a plurality of application.
2. The present invention facilitates automated updating of the generated personas time to time by utilizing additional insights.
3. The generated personas can be utilized in many fields for mimicking a person’s role based on real-world characteristics of the user and the applications they use.

[0029] The foregoing descriptions of specific embodiments of the present invention have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the present invention to the precise forms disclosed, and obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the present invention and its practical application, to thereby enable others skilled in the art to best utilize the present invention and various embodiments with various modifications as are suited to the particular use contemplated. It is understood that various omission and substitutions of equivalents are contemplated as circumstance may suggest or render expedient, but such are intended to cover the application or implementation without departing from the scope of the present invention.
, Claims:We claim:
1. A system (100) for automated persona generation, the system (100) being configured on a computing device, the system (100) comprising:
an application crawler (11) configured to crawl through a plurality of applications, interacted by a user, to identify possible pathways by interacting with elements and submitting inputs;
a persona generating module (12) configured to generate a persona based on the applicable paths and inputs received from the application crawler (11);
a database (13) configured for storing generated persona; and
a machine learning model (14) configured to enable the application crawler (11) and the persona generating module (12) to comprehensively understand the plurality of applications and provide the necessary inputs to progress to a next task.

2. The system (100) as claimed in claim 1, wherein the application crawler (11) comprising
an analysis module configured to examine structure and a plurality of elements of the plurality of applications interacted by the user and to map user flows therein;
an interaction engine configured to simulate the user interactions with user interface (UI) of the plurality of applications, to populate forms and input fields with appropriate data to progress through different application states, and to navigate between different sections and levels of the application;
a data collection module configured to gather every simulated user actions, system responses, error scenarios, and error handling mechanisms;
a user interaction handler configured to request user input for human assistance in complex decision points and to process input received from the user; and
a data export module configured to export data gathered by the data collection module.

3. The system (100) as claimed in claim 1, wherein the elements of the plurality of applications examined by the analysis module includes a plurality of buttons, a plurality of input fields, a plurality of dropdown menus, and other UI components.

4. The system (100) as claimed in claim 1, wherein the data exported by the data export module includes path data of user journeys through the plurality of applications, a catalog of the data required at various points in the application, and a plurality of user behavior patterns.

5. The system (100) as claimed in claim 1, wherein the application crawler (11) further configured to train the generated persona by allowing adaptation thereof to a new application.

6. The system (100) as claimed in claim 1, wherein the generated persona is utilized by a testing system for software development and testing utilizing persona-based behavior.

7. A method for automated persona generation comprising
crawling (101) through a plurality of applications interacted by a user using an application crawler (11);
gathering an interaction data, by the application crawler (11), from the plurality of applications;
providing the interaction data (102), by the application crawler (11), to a machine learning model (14);
processing the interaction data by the machine learning model (14);
receiving processed interaction data, by the application crawler (11), from the machine learning model (14);
providing processed interaction data (103), by the application crawler (11), to a persona generating module (12);
requesting a plurality of insights (104), by the persona generating module (12), to the machine learning model (14);
providing the plurality of insights, by the machine learning model (14), to the persona generating module (12);
generating persona of the user interacting the plurality of applications by the persona generating module (12); and
storing the generated persona (105) in a database (13).

8. The method as claimed in claim 7, wherein the interaction data includes structure and a plurality of elements of the plurality of applications.

9. The method as claimed in claim 7, wherein the plurality of insights includes application interaction patterns of user, potential user preferences, and static data for the various user inputs.

10. The method as claimed in claim 7, further comprising:
receiving new interaction data of the plurality of applications, time by time or on request (106), by the persona generating module (12) from the application crawler (11);
updating the generated persona (107), by the persona generating module (12), using additional data received from the application crawler (11); and
training the generated persona by the persona generating module (12).

11. The method as claimed in claim 7, wherein the generated persona is utilized by the application crawler (11) to automate flows or test paths (108) in the application assuming the persona as the user.

12. The method as claimed in claim 7, wherein the generated persona is utilized for crawling (109) through a plurality of applications to collect a plurality of required inputs and pathways for the usage of the system.

Dated this on 15th day of January 2025

Prafulla Wange
(Agent for Applicant)
(IN/PA: 2058)