System and method for the simplified and statistically rigorous destination selection with a user interface

Abstract

A computer-implemented system and method for destination selection is disclosed, enabling users to make informed, data-driven travel decisions through an interactive user interface. The invention processes preference data—collected from sources such as surveys, expert input, and web data, to identify and define statistically distinct experience components and their sub- components using dimensionality reduction techniques. Ordinal measures and weights are calculated for each component, reflecting their significance in differentiating destinations. The system generates customisable visual representations, graphical, textual, or combined, allowing users to explore, adjust, and compare destinations in real-time based on personalised preferences. Visualisations include multi-dimensional plots, ranked component displays, spider charts, and comparative analyses across one or more destinations. Interactive features permit live weighting adjustments and highlight destination strengths, weaknesses, or unique selling propositions. The system ensures synchronised textual summaries and iterative refinement based on user feedback, supporting intuitive and statistically robust destination decision-making through integrated data analysis and visual exploration tools.

Description

SYSTEM AND METHOD FOR A SIMPLIFIED AND STATISTICALLYRIGOROUS DESTINATION SELECTION WITH A USER INTERFACEFIELD OF INVENTION

[0001] The present invention pertains to the field of tourism, specifically to a system and method for facilitating simplified and statistically rigorous destination selection for travellers, via a user interface and mechanism.BACKGROUND OF INVENTION

[0002] In tourism, selecting an intended destination involves navigating a complex array of broadly defined and notional factors or dimensions of perceived experience (hereinafter referred to as “experience components” or “components”), such as accessibility, affordability, service levels and amenities, safety, and more. Each of these components is further detailed by a subset of sub-components or descriptors, which adds layers of complexity to the decision-making process.

[0003] The intricacies of the tourist experience are viewed from various perspectives, including post-experience analysis, immediacy, and business and attraction viewpoints. For instance, African safari travel, a distinct type of tourism offering, encompasses numerous known and hypothesised components. The component of 'Authenticity' may include descriptors such as remoteness, an emphasis on ecotourism, designation as a nature reserve or protected area, and community involvement, amongst others. Similarly, 'Iconic wildlife encounters' may include Big Five sightings, sightings of notablePOL2_0003African animals like giraffes, zebras, and hippos, as well as exposure to other rare or unusual biodiversity.

[0004] Choosing a destination from numerous components and subcomponents can be complex and overwhelming, primarily because experience components, their measurements, and the underlying preference data lack uniformity and comparability. Travellers find it challenging to consistently assess and compare the various attributes, making like-for-like comparisons difficult and impeding informed, satisfying decisions.

[0005] Addressing this complexity requires a system and method capable of efficiently processing, structuring, and presenting such multidimensional preference data. Users need real-time, interactive visualisations that enable comparisons across multiple destinations, adjustment of experience component weightings, and presentation of both graphical and textual representations synchronised across devices. Conventional approaches often struggle with handling the dimensionality and interactivity efficiently, or fail to dynamically synchronise multiple representations, resulting in delays, inconsistencies, non-intuitive user experiences, mismatched expectations, and ultimately unsatisfactory outcomes.

[0006] The present invention addresses, at least partially, the issues above.SUMMARY OF THE INVENTION

[0007] The invention addresses these challenges by providing a system and method that simplifies the process in a statistically rigorous way. It allows for easy visual navigation through a computerised user interface - whetherPOL2_0003graphical, textual, or a combination thereof - enabling a would-be tourist or user to make quick yet rigorous destination selections with the reassurance of their decision-making process and supported by available data.

[0008] Hereinafter, "experience component" refers to a distinct dimension or factor of perceived experience related to a destination or a location (“location”) derived from preference data collected. It acts as a broad category in statistical analysis for grouping and evaluating key aspects of a travel destination, thereby assisting travellers in comparing and selecting destinations based on their preferences or tastes.

[0009] Hereinafter, “descriptors” and “sub-components” are used interchangeably, meaning metadata of sub-factors or specific attributes that contribute to an experience component, representing the finer details or individual elements that collectively shape the broader experience component.

[0010] Hereinafter, “preference data” refers to raw, uncollated information collected from various sources containing ordinal measures of descriptors, which can then be organised and aggregated into broader experience components to identify patterns and tailor destination recommendations.

[0011] “Devices” as used herein refer to all hardware components through which a user interacts with the computerised system deploying the method of the invention, and include input devices such as keyboards, touchscreens, microphones, and cameras, as well as network communication interfaces that enable data exchange over wired or wireless networks.POL2_0003

[0012] The invention provides a method, implemented by a computerised system comprising processing means, memory configured with executable software and a database, to enable a user to select a location, which includes the following steps:(a) defining experience components (and sub-components) from collected preference data relating to the location using statistical algorithms executed by the processing means;(b) grouping the collected preference data into one or more experience components through computational modules executed by the processing means;(c) calculating an ordinal measure for each experience component based on the preference data using software executed by the processing means;(d) assigning a weight to each experience component using software executed by the processing means; and(e) representing the experience components in a visual representation that highlights the strengths or weaknesses of the location, generated by software executed by the processing means and presented via devices.

[0013] The preference data relating to the location may be collected via verification visits, website information, expert advice, public surveys, or otherPOL2_0003relevant sources, and may be input to the system through devices, network interfaces, or automated data feeds.

[0014] The preference data pertains to a specific destination and captures various aspects of the experience there, and may include elements like restaurants, fine dining, hikes, water activities, or accommodations such as hotels and safari lodges, which are then stored in structured formats within the database.

[0015] The method further includes, after step (e), permitting the user to customise the visual representation of the experience components through devices, wherein software executed by the processing facilitates such customisation, enabling real-time interactive adjustment of experience components weightings, with responsive updates to the visual representations generated dynamically by the processing means.

[0016] In step (a), the experience components are defined and distilled using dimension reduction statistical methods executed as optimised software routines on the processing means, such as principal component analysis, singular-value decomposition, or factor rotation, which reduce data dimensionality and isolate independent, orthogonal factors to enable this identification and definition of experience components.

[0017] In this step, reducing data dimensionality and isolating independent, orthogonal factors ensures that the experience components have minimal correlation or overlap, meaning they are discrete and independent (uncorrelated).POL2_0003

[0018] The method includes an additional step, after step (a), of assigning a meaningful label to each experience component performed automatically or semi-automatically by software employing statistical interpretation or grouping techniques on the descriptor data.

[0019] In step (c), an ordinal measure is calculated for each experience component based on the preference data and all associated descriptors, with software executed by the processing means mapping the experience components and their descriptors to the preference data, thereby associating each destination with an average ordination across the experience components.

[0020] In step (d), weight is assigned by analysing the experience components to determine which experience components are most important to the overall variance in the preference data, using software executed by the processing means that applies statistical metrics and ranking algorithms.

[0021] The weight may reflect the component’s contribution to the overall variation in the collected preference data across all destinations, thereby prioritising components that most significantly differentiate destinations; the weights may subsequently be adjusted interactively by the user to reflect individual traveller preferences.

[0022] By assigning weights, more significant experience components can be distinguished from less significant ones, allowing exclusion of less meaningful components from the visual representation to improve clarity and user focus.POL2_0003

[0023] In step (e), the visual representation may be static or interactive, with interactive forms implemented as computer-executable instructions executed by the processing means that respond to user input events on devices, updating the representation dynamically.

[0024] The interactive form of the visual representation may be configured to enable the user to adjust the weighting (significance) of the experience components in real-time, omit experience components or sub-components, or amend contributions of sub-components, with updates rendered by the processing means via devices.

[0025] In step (e), the visual representation can be configured to enable the user to compare a destination or location with similar or competing destinations or locations.

[0026] The visual representation may be graphical, textual, or a combination thereof.

[0027] In a first graphical representation, two or three experience components may be selected to define a 2- or 3-dimensional Cartesian space, respectively, within which various locations within a destination can be plotted for comparison, rendered using computer graphics software executed on the processing means.

[0028] In a second graphical representation, the experience components can be displayed from most to least significant or vice versa, with interactive capabilities implemented by software executed on the processing means that allows users to reorder, adjust, or modify components via devices.POL2_0003

[0029] The second graphical representation may be interactive, allowing the user to adjust the weighting of, or omit, experience components, thereby altering the relative importance of the experience components according to current preference or taste, with the processing means recalculating and rendering updated representations.

[0030] In a third graphical representation, multiple destinations can be compared based on one or more selected experience components, with data aggregation and rendering managed by the processing means.

[0031] A fourth graphical representation may compare multiple destinations based on a single experience component.

[0032] In the fourth graphical representation, one or more additional experience components may be introduced to compare the multiple destinations.

[0033] A single destination may be analysed across multiple experience components in a fifth graphical representation.

[0034] In the fifth graphical representation, one or more additional destinations may be introduced and compared against each other across the multiple experience components.

[0035] In a sixth graphical representation, users can drill down into a selected experience component to examine the underlying sub-components and their relative contributions, for comparison purposes, with interactive adjustment facilitated via devices and processed in real-time by the processing means.POL2_0003

[0036] The sixth graphical representation may support user interaction to adjust or remove weighting of the sub-components, with the processing means updating the graphical representation responsively.

[0037] The most or least advisable destinations or locations may be displayed in a seventh graphical representation based on user preferences or interactive feedback, reflecting adjustments to experience components and subcomponents processed and ranked by software executed by the processing means.

[0038] In an eighth graphical representation, the average experience components are displayed and mapped onto the destination or location most closely aligning with those averages.

[0039] A ninth graphical representation displays a location or destination's unique selling proposition, calculated as the difference between the location's or destination's experience components and the average experience components, using software executed by the processing means.

[0040] The interactive features of the graphical representations mentioned above may help users make informed decisions by customising the importance of experience components to align with their preferences, with such interactions facilitated through user interface devices and processed by software executed on the processing means, with data stored and retrieved from memory.

[0041] Preferably, the graphical representations may be displayed using a polygonal radar or spider chart, implemented as computer-generated graphicsPOL2_0003rendered on user interface devices, generated by software executed on the processing means, with the graphical data stored and retrieved from memory..

[0042] The method may include the additional step of redesigning or refining the experience components, their weightings, or the resultant strength or weakness of the destination or location, based on feedback from the user reflecting the user’s current preference or taste, during interaction with the graphical representation rendered on devices, with such refinements processed iteratively by software executed on the processing means and stored in memory.

[0043] The method may include the additional steps of automatically generating, by software executed on the processing means, a textual representation of experience component data corresponding to a graphical representation rendered on devices, and synchronising the textual representation with the graphical representation in real time to maintain consistent mirroring of information, with both representations stored in memory.

[0044] According to a second aspect of the invention, there is provided a computerised system configured to enable a user to select a location, comprising: a processing means; a database configured to store preference data relating to the location;POL2_0003a memory device containing instructions which, when executed by the processing means, cause the processing means to: define experience components from collected preference data relating to the location and stored in the database; group the collected preference data into one or more experience components; calculate an ordinal measure for each experience component based on the preference data; assign a weight to each experience component to rank and prioritise each component; and represent the experience components in a visual representation that highlights the strengths or weaknesses of the location to the user via devices.BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The invention is further described by way of an example with reference to the accompanying drawings in which:Figure 1 illustrates a graphical representation, rendered on a user device, of two experience components, selected to define a 2-dimensional Cartesian space, where various locations (lodges in this example) within a destination are plotted for comparison;POL2_0003Figure 2 shows the graphical representation of Figure 1, which includes a frontier line;Figure 3 shows a graphical representation, rendered on a user device, of three experience components, selected to define a 3-dimensional Cartesian space, where various locations (lodges in this example) within a destination are plotted for comparison, and which includes a frontier boundary;Figure 4 is a bar chart, displayed on a user device, of experience components from most significant to least significant;Figure 5 is the bar chart of Figure 4, demonstrating its interactive capabilities that allow users to adjust the weighting of experience components or remove experience components;Figure 6 shows a spider chart, rendered on a user device, that compares multiple destinations based on a single experience component.Figure 7 shows a spider chart that compares multiple destinations across multiple experience components;Figure 8 illustrates a spider chart analysing a single destination across multiple experience components;Figure 9 shows a spider chart analysing multiple destinations across multiple experience components;Figure 10 shows a spider chart analysing a single destination across underlying sub-components that make up a selected experience component;POL2_0003Figure 11 illustrates the chart of Figure 10, displayed on a user device, and demonstrating the interactive capabilities of this display that allow users to adjust the sub-component weighting or remove experience sub-components;Figure 12 illustrates a display of the most or least advisable destinations or locations based on user preferences or interactive feedback;Figure 13 illustrates a spider chart showing the average experience components of a specific destination and identifying the destination that most closely matches these averages;Figure 14 illustrates a spider chart showing a location’s unique selling proposition compared to the average in Figure 13;Figure 15 illustrates a display of a textual representation of experience component data and a corresponding graphical representation, rendered on a user device;Figure 16 shows a screen, rendered on a user device, through which the user may interact with the system to redesign or refine the experience components, their weightings, or the resultant strength or weakness of the corresponding location;Figure 17 schematically illustrates a computerised system that implements the method of the invention and that generates the graphical representations depicted in Figures 1 to 16 for display on a user's device;Figure 18 provides a schematic of the server at the core of this system, which is configured to generate these graphical representations;POL2_0003Figure 19 shows a schematic overview of the system for Figure 15, showing the flow of data through processes and data outputs; andFigure 20 presents a flow diagram detailing the steps involved in the method of the invention;DESCRIPTION OF PREFERRED EMBODIMENTS

[0046] Figure 17 illustrates a system 10 configured to support a method of the invention, which enables a user to select a location at the destination. In this example, the location would be suitable for providing an African photo safari.

[0047] Central to the system, and with particular reference to Figure 18, is a physical or virtual server 12. The server includes a processing means 14 with method-enabling software 16.1 running on the processing means, the software including, without limitation, algorithm engines, statistical algorithms, computational modules, data ingestion and pre-processing modules, visualisation modules, and interface or application programming interface (API) layers to support interaction with user devices. A database 18 communicates with the processing means to store and retrieve preference data, descriptors, experience components, and processed outputs.

[0048] By way of example, system 10 includes a first device, 20, owned by a first user (e.g., the first person), and a second device, 22, owned by a second user. These users are searching for suitable destinations, such as Kenya, Tanzania, Zambia, Zimbabwe, and South Africa, or locations like lodges, hotels, and tented camps within a destination, for an African photo safari.POL2_0003Typically, the first and second devices (20, 22) will be a cell phone or a laptop, the features of which will have similar designations in the following description.

[0049] Each of these devices comprises a processor 24 and application software (App) 16 executed on the processor, the application software being configured to enable communication with the server 12 and its processing means 14, thereby facilitating execution of the method of the invention on the device.

[0050] Regarding Figure 18, the processing means 14, configured to execute the functionalities of the system and the method of the invention, includes at least one processor 24 (CPU) in communication via a respective bus with a mass memory 30 and a storage drive 32 on which the database 18 is stored.

[0051] The mass memory 30 comprises ROM, which stores firmware, and RAM components. The memory further includes data storage 36, an operating system 38, and executable software modules. In cooperation with the processing means, the software configures the system to carry out the operations and method steps described herein.

[0052] Communicating with the processing means 14, and without limiting the generality of the foregoing or restricting the scope of the invention, the server may further include one or more peripherals such as: a power supply 42, one or more network interfaces or transceivers 44, an audio interface 46, a display 48, a keypad or virtual keypad 50, and one or more input / outputPOL2_0003interfaces 52. The display 48 may be any suitable type of display, for example, LCD or LED, and may further incorporate a touch-sensitive screen.

[0053] The network interface or transceiver 44 has circuitry designed to enable communication between server 10 and devices (20, 22). It is intended to support various communication protocols, such as, but not limited to, GSM, TCP / IP, SMS, GPRS, WAP, UWB, IEEE 802.16, Wi-Fi, Zigbee, or any other wireless communication protocol.

[0054] The devices (20, 22) incorporate counterparts to the hardware components mentioned previously. For simplicity, these components are not described in detail here. It is noted, however, that the corresponding software is referred to as App 16. The touch-sensitive screen of the devices displays visual representations as outputs 58 received from the processing means when deploying the method of the invention, which users can interact with via the touch-sensitive interface, as will be explained in more detail below.

[0055] After downloading the App 16 onto their respective device (20, 22), users may be prompted to subscribe to the service, which is delivered by the system 10, employing the method of the invention. Users can enter personal information and preferences by navigating through screens. This information is then uploaded and stored in the database. Once stored, users can log in with their settings, and their choices will influence the customisation and presentation of the graphical representations described below, providing a personalised and interactive experience.POL2_0003

[0056] The method-enabling software 16.1 and the corresponding App 16.2 consist of computer-executable instructions. When executed on server 12 or a device (20, 22), respectively, this software facilitates the transmission, reception, and processing of communication messages in the form of data packets transmitted using any suitable protocol between the server and the devices. These messages collectively enable the functionality of Apps, allowing them to synchronise data, fetch updates, and provide an interactive communication channel between the user and the system.

[0057] The method of the invention can be implemented via the respective CPU 24 or memory 30. The method steps described below can be partially implemented via hardware logic in the CPUs and partially using instructions stored in memory. Thus, the disclosure is not limited to a specific hardware or software configuration.

[0058] Database 18 contains preference data 60 relating to a destination for an African photo safari, including detailed information about various locations within the destination, sourced from guests, industry experts, travel agencies, or other relevant entities. The preference data includes descriptors such as wildlife viewing opportunities, accommodations, local attractions, and other aspects contributing to the safari experience, each associated with an ordinal measure of relative importance.

[0059] The database further stores feedback data 60.1 from users collected during interactions with the system, enabling dynamic adjustment of experience component weightings and iterative refinement of visual andPOL2_0003textual representations, so that comparisons and recommendations continuously reflect current user preferences, as described below.

[0060] This preference data can be gathered from a variety of sources, including verification visits 60.2, website information 60.3, expert review 60.4, or guest surveys 60.5, which may be input to the system through devices, network interfaces, or automated data feeds and processed via the API..

[0061] By way of example, the preference data stored in database 18 may be organised in tabular form, such as a relational database table, where each record contains a destination or location identifier, an associated descriptor, and an ordinal score. For example:Destination / Location OrdinalQDateDescriptor ID Score (1-5)ourceCollectedBig FiveLODGE_A 5 Guest 2025-03-12 Sightings SurveyLODGE_A Remoteness 4 Expert 2025-03-14GuestLODGE_B Service Quality 3 2025-03-11 SurveySustainable4TourLODGE_B 2025-03-10Architecture Operator GuestLODGE_C Fine Dining 2 2025-03-08 SurveyTABLE 1

[0062] Regarding Figure 20, the method of the invention enables a user to select a destination or a location at the destination, in this case, an African photo safari destination or location, by collecting preference data relating to the destination or the location 62; defining experience components and sub- comonents from the preference data 64; organising the collected preferencePOL2_0003data according to the defined experience components 66; calculating an ordinal measure for each experience component based on the preference data 68; assigning a weight to each experience component to rank and prioritise each component’s relative importance to a traveller’s experience 70; and representing the experience components in a visual representation 58 that highlights the strengths or weaknesses of the destination or the location.

[0063] The advantage of this method and system is that, while maintaining statistical rigour, it enables users to make informed selections easily by interacting with the visual representation 58. The visualisations are designed to be intuitive and are typically presented as spider or radar plots / charts.

[0064] In step 64, based on the preference data, the statistical dimensionreduction methodology encoded in the computational module of software 16 is executed on the processing means 14 to identify, define, and distil orthogonal (uncorrelated) experience components. Principal component analysis is the most commonly applied algorithm, though related techniques such as singular-value decomposition, factor rotation, or biplots may also be used. Regardless of the chosen algorithm, the objective is to apply rigorous statistical methods to isolate and define the key experience components relevant to tourism offerings, for example, an African photo safari product.

[0065] Using the ordination results from the dimension reduction analysis in steps 64 to 68, each destination is plotted as an individual data point, labelled71.1 , 71.2, ... 71. N in Figure 1. This process assigns a distinct visible position to each destination within the ordination of experience components.POL2_0003

[0066] Although the ordination indicates which experience components are most significant in explaining the variation in preference data, any identified experience components can be selected for graphical display. For instance, if ten experience components are identified from a preference data set of a thousand descriptors, one could graphically depict experience component 1 , such as “Iconic Wildlife Encounters”, versus experience component 2, such as “Authenticity”. This visual representation example 58.1 is illustrated in Figure 1.

[0067] In any graphical representation of experience components mapped to destinations, each destination is positioned within a 2-dimensional {x, y} or 3- dimensional {x, y, z} Cartesian space, as shown in Figure 1 (58.1) and Figure 3 (58.3), respectively. A frontier line 72 (see Figures 2 and 3) can also be included to highlight destinations that maximise or minimise suitability. This frontier line represents a Pareto frontier, which is the set of non-dominated destinations such that no other destination outperforms them simultaneously across the selected experience components. The Pareto frontier effectively identifies destinations offering the best trade-offs and optimal performance in the dimensions considered, aiding users in discerning top-performing destinations within the graphical interface in both 2D (Figure 2; 58.2) and 3D (Figure 3; 58.3) contexts.

[0068] In step 70, each isolated experience component is assigned a relative weight reflecting its importance in explaining the overall variation within the preference data. When principal component analysis is employed, the resulting experience components are, by construction, statisticallyPOL2_0003independent. This analysis is carried out by statistical metrics and ranking algorithms encoded in the software 16 and executed by the processing means 14. For illustration, Table 2 below shows an example output from principal component analysis (PCA) applied to a preference dataset, with corresponding eigenvalues, variance explained, and normalised weights. At the same time, Figure 4 provides a corresponding graphical representation 58.4 of this dataset :TABLE 2

[0069] The eigenvalues indicate the relative importance of each component in explaining variance in the data. These values are normalised by dividing eachPOL2_0003eigenvalue by the sum of all eigenvalues to produce weights that sum to 1 (or 100%). The normalised weights can then be used to rank the experience components and adjust their visual representation accordingly. For instance, “Iconic Wildlife Encounters” with the highest weight (0.35) would be emphasised more prominently in the graphical interface than “Affordability” with the lowest weight (0.08). This approach ensures the weighting reflects the statistical significance of each experience component, enabling a more rigorous and meaningful destination selection process.

[0070] A bar chart of the experience components ordered according to relevance, from most relevant (i.e. explaining the most significant proportion of variance in the underlying preference data) to the least relevant (i.e. presenting the least proportion of variance in the underlying preference data), after assigning a weight according to step 70, is represented graphically 58.4 (Figure 4).

[0071] A graphical mechanism allows users to modify experience components by omitting, reordering, or adjusting the relative importance of any component. Users can increase the significance by dragging the column up on the touch screen 48 of their device (20, 22) or decrease it by dragging the column down. This interaction can be visualised using various graph types; for illustration, a bar chart is used (Figure 5; 58.5). The hand icon 74 represents the interactive feature that enables users to adjust the height of the bars corresponding to each experience component.POL2_0003

[0072] The system provides users with an interactive graphical interface (Figure 5; 58.5) that allows them to adjust the relative relevance of experience components to reflect personal preferences or tastes. Using mechanisms such as dragging columns up or down on a touchscreen display 48, users can increase, decrease, omit, or reorder components, with changes visualised in formats such as bar charts. These manual adjustments complement the statistically derived weights and are captured as feedback data 60.1 (see Figure 19), which is stored in the database 18 and reintegrated into the system to refine statistical outputs and visualisations. This feedback loop ensures that recommendations and comparisons remain dynamically aligned with evolving user priorities.

[0073] In another alternative to representing the experience components in a visual representation 58.6, a mechanism is provided in the form of a computerised data-mapping and visualisation module within the graphical user interface. This module retrieves destination profiles from database 18 and aligns them with the statistically derived or user-adjusted experience component 76. Each destination (71.1 to 71.5) is mapped to a common scale of component values, thereby enabling direct side-by-side comparison.

[0074] Depending on user selection, and without limiting the scope of the invention, the graphical interface may render the comparison using charts (such as bar graphs), radar plots (such as the polygonal radar charts of Figures 6 to 9), bubble plots, Glyph plots, Sankey plots, or comparative matrices. This allows destinations to be evaluated against a single component, for example, “Authenticity” as shown in Figure 6, or acrossPOL2_0003multiple components, for example, “Authenticity,” “Iconic Encounters,” and “Service and Guiding”, as illustrated in Figure 7 (58.7) and respectively designated 76.1 , 76.2 and 76.3.

[0075] The mapping and rendering operations are managed by the computational module of software 16, executed on the processing means 14, ensuring statistical consistency while providing intuitive, interactive usability.

[0076] Conversely, the method provides a mechanism to map multiple experience components (76.1 to 76.11) to a single destination 71 or to various destinations (71.1, 71.2) in a computerised graphical user interface. See Figures 8 (58.8) and 9 (58.9), respectively.

[0077] In an alternative embodiment, the method provides a mechanism within the computerised graphical user interface to explore a single destination 71 with respect to an individual experience component, such as “Eco-friendly.” The interface further enables examination of the subcomponents (designated 80.1 to 80.9) that constitute the selected experience component, together with their respective weightings. An example of this graphical representation (58.10) is illustrated in Figure 10.

[0078] Figure 11 (58.11) illustrates a graphical representation configured to enable users to interactively adjust the relative contributions of the underlying sub-components (80.1 to 80.9) within a selected experience component. Users may first identify the experience component most relevant to them (as shown in Figure 5) and then customise the weighting of its sub-components inPOL2_0003accordance with their contemporaneous preferences, rather than relying solely on the statistically derived or average significance values.

[0079] The system 10 further allows the user to emphasise specific subcomponents or descriptors within an experience component by selectively including or excluding them. Through the graphical interface, individual descriptors can be adjusted interactively — pushed outward (as shown in dotted lines) to increase their relative weighting, or pulled inward (as shown in dotted lines) to reduce their weighting, including to zero if excluded entirely (see Figure 11). In the illustrated graphical representation 58.11, user 74 is modifying the relative importance of the sub-components “Eco-friendly Activities” and “Sustainable Architecture-Water Conservation” in accordance with personal preference.

[0080] Figure 12 (58.12) illustrates a mechanism of the invention in which destinations are displayed, in a computerised graphical user interface, as a ranked list or similar format ordered from most to least recommended (or vice versa). This ranking is generated by the processing means 14 executing the software 16, based on preference data distilled into experience components, including any custom isations made by the user. The selected experience components are then mapped against destinations retrieved from the database 18.

[0081] The system 10 further provides a mechanism to calculate and display the average value of each experience component across the dataset. From these values, an “average preference destination” 82 is derived andPOL2_0003presented graphically, as illustrated in Figure 13 (58.13), thereby providing a benchmark profile for comparative analysis.

[0082] Building on this, the method enables comparison between any individual destination and the average preference destination. This graphical representation (Figure 14; 58.14) highlights the unique selling proposition 84 of the selected destination by contrasting its experience components against the benchmark profile, either across all components or only those where the differences are most significant.

[0083] Figure 15 (58.15) illustrates an alternative visualisation of the experience component data. A textual representation 86 is synchronised with a graphical representation 88 rendered on the user device (20, 22). Both representations are generated by software 16 executed on the processing means 14 and stored in the database 18. User inputs via text prompts, processed by the software and optionally interpreted through a chatbot or large language model trained on the preference data, dynamically update experience component values and weightings. These updates are propagated to both representations in real time, ensuring synchronisation and reflecting the user’s current preferences.

[0084] Finally, with reference to Figure 16, the system 10 provides an alternative interactive representation 58.16 in which the experience components (76.1 to 76.3 and 76.8 to 76.10) are displayed linearly down the page. Each component is associated with a slider bar 90, with ten ordinal positions indicating relative importance. By default, the sliders may be presetPOL2_0003to a median value, such as 5, allowing the user to adjust each component upward toward “10” or downward toward “1” according to their personal preference. Adjustments made via these sliders are processed by the software, executed on the processing means, dynamically updating the corresponding visual and textual representations, and storing the feedback data in the database to refine subsequent recommendations.

[0085] In each case, the graphical user interface running on the user device (20, 22) and rendered on the display 48 acts as the point of interaction, supported by the processing means 14 and database 18. This integration allows users not only to view rankings and comparisons but also to emphasise particular destinations, spotlight unique selling propositions, or refine selections for specific travel themes, such as an African photographic safari, a European hotel stay, or an island adventure. The captured adjustments and interactions are stored as feedback data 60.1, enabling the system to refine subsequent recommendations continuously.POL2_0003

Claims

CLAIMS1. A method, implemented by a computerised system comprising processing means, memory configured with executable software and a database, to enable a user to select a location, which includes the following steps:(a) defining experience components and sub-components from collected preference data relating to the location using statistical algorithms executed by the processing means;(b) grouping the collected preference data into one or more experience components through computational modules executed by the processing means;(c) calculating an ordinal measure for each experience component based on the preference data using software executed by the processing means;(d) assigning a weight to each experience component using software executed by the processing means; and(e) representing the experience components in a visual representation that highlights the strengths or weaknesses of the location, generated by software executed by the processing means and presented via devices.

2. A method according to claim 1 which includes an additional step, after step (e), of permitting the user to customise the visual representation of the experience components through devices.POL2_00033. A method according to claim 1 or 2 wherein, in step (a), the experience components are defined using dimension reduction statistical protocols executed by the software on the processing means.

4. A method according to any one of claims 1 to 3 which includes an additional step, after step (a), of assigning a label to each experience component performed by the software on the processing means.

5. A method according to any one of claims 1 to 4 wherein, in step (c), the ordinal measure for each experience component is calculated by mapping the experience components to the preference data, thereby assigning each destination an average ordination across the experience components.

6. A method according to any one of claims 1 to 5 wherein, in step (d), the weight is assigned to each experience component by analysing the experience components to identify those that contribute most significantly to the overall variance in the preference data.

7. A method according to any one of claims 1 to 6 wherein, in step (e), the visual representation is in a static or an interactive form, and wherein the interactive form is executable to receive user input from devices and update the visual representation in response thereto.8 A method according to claim 7, wherein the interactive form, when executed, enables the user to adjust the weighting assigned to the experience components, omit experience components or sub-components, or amend contributions of sub-components.POL2_00039. A method according to claim 7 or 8 wherein the visual representation is graphical, textual, or a combination thereof.

10. A method according to claim 9, wherein the visual representation comprises both a textual representation and a corresponding graphical representation, the textual and graphical representations being synchronised, and wherein user input provided via text prompts updates the graphical representation, and user input provided via the graphical representation updates the textual representation.POL2_0003

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