Abstract: One embodiment of the present disclosure is a method for automatically acquiring and assessing travel data. The method includes acquiring travel data from a plurality of content sources using a plurality of artificial intelligence (AI) agents, generating, using the plurality of AI agents, a plurality of output travel data items from the acquired travel data, generating a plurality of confidence scores for the plurality of output travel data items, each of the plurality of confidence scores for a different respective output travel data item, and each of the plurality of confidence scores generated using a source credibility associated with a reliability of the content source from which the travel data was acquired for the output travel data item, and utilizing the plurality of confidence scores to determine an action to perform with respect to one or more of the plurality of output travel data items.

Abstract: Various examples, systems, and methods are disclosed relating to processing, classifying, and grouping images. A first computing system can cause an encoder model to generate a plurality of scenes corresponding with a plurality of images. The first computing system further can cause a detection model to generate a plurality of similarity metrics of a plurality of image pairs of a plurality of spaces of the plurality of images corresponding with at least one scene. The first computing system further can determine a plurality of image subsets of the plurality of spaces of the plurality of images corresponding with the at least one scene, the plurality of image subsets are determined based at least on a grouping of the plurality of images according to the plurality of similarity metrics. The first computing system further can provide the plurality of image subsets of the plurality of images.

Abstract: A computing system includes a processing circuit having a processor coupled to a memory device. The processing circuit performs operations including receiving, during a search session, a search query comprising configurable parameters; providing, during the search session, an array of visual outputs that meet criteria defined by the parameters; receiving, from a user device, during the search session, a selection of a visual output from the array; extracting, using a machine learning model and based on a pixel composition of the visual output, a feature; identifying, using the machine learning model, one or more second visual outputs related to travel properties that share the feature; replacing a default image associated with at least one travel property with an image representing the feature; and providing, to the user device, during the search session, a second array comprising the one or more second visual outputs including the replaced image.

Abstract: Systems and methods for clustering and organizing geographical locations into regions of interest (ROI) within a hierarchical graph. The ROI generation system may generate a graph containing geographical entities and the relationships between each geographical entity. Each geographical entity can be represented as a node, and the relationships between geographical entities may be represented as edges between nodes. Each edge may represent the relationship between the two geographical entities weighted based on an occurrence of both geographical entities appearing as search items within a user session. In addition, the ROI generation system may generate multiple levels within a graph corresponding to various resolutions of geographical entities. The ROI generation system may cluster geographical entities within the hierarchical graph into non-overlapping regions of interest, or clusters. Insights and metrics may be inferred from the hierarchical graph and presented to the user or third parties.

Abstract: A system includes at least one processing circuit including at least one memory and one or more processors configured to: identify, via at least one machine learning model, at least one excluded parameter of a non-bounded query relating to a trip; identify, via the at least one machine learning model, a set of travel results that match the query and the excluded parameter by: analyzing, based on search data from one or more users, at least one search result distribution corresponding to at least one parameter associated with at least one trip of the one or more users and relating to the at least one excluded parameter; and identifying the set of travel results based on a value regarding the at least one parameter satisfying a presentation threshold for the at least one search result distribution; and present one or more travel results of the set of travel results.

Abstract: Systems and methods for generating content summaries are provided. A provider computing system includes a first machine learning model configured to: retrieve one or more elements associated with an entity and retrieve a plurality of content items associated with the entity, each content item including a reference to at least one of the one or more elements; a second machine learning model configured to determine, for each reference to at least one of the one or more elements in each content item of the plurality of content items, a sentiment of the reference; a third machine learning model configured to generate, for each reference to the at least one of the one or more elements, a first summary of the at least one of the one or more elements; and a fourth machine learning model configured to: generate a second summary, including the first summary.

Abstract: One embodiment of the present disclosure is a method for automatically acquiring and assessing travel data. The method includes acquiring travel data from a plurality of content sources using a plurality of AI agents, generating, using the AI agents, a plurality of output travel data items from the acquired travel data and a plurality of confidence scores for the output travel data items, generating a plurality of final confidence scores for the plurality of output travel data items, the plurality of final confidence scores generated based the confidence scores, source credibility scores and AI agent credibility scores, automatically determining an action to perform on one or more of the plurality of output travel data items using the final confidence scores of the one or more output travel data items, and automatically performing the action.

Abstract: One embodiment of the present disclosure is a method for automatically acquiring and assessing travel data. The method includes acquiring travel data from a plurality of content sources using a plurality of AI agents, generating, using the AI agents, a plurality of output travel data items from the acquired travel data and a plurality of confidence scores for the output travel data items, generating a plurality of final confidence scores for the plurality of output travel data items, the plurality of final confidence scores generated based the confidence scores, source credibility scores and AI agent credibility scores, automatically determining an action to perform on one or more of the plurality of output travel data items using the final confidence scores of the one or more output travel data items, and automatically performing the action.

Abstract: Secure authentication and delayed transaction processing for booking management systems is provided. Third-party services partner with booking management systems to aggregate and list offerings of the third-party services in a digestible display on a one-stop platform. A booking management system can manage the authentication of payment card information on behalf of any number of such third-party services. The booking management system can maintain and process authentication information associated with traveler payment cards, and provide virtual payment information to the third-party services for payment following chargeable events. The third-party services may later initiate a transactions using the virtual payment information, without being required to perform authentication processing on the traveler payment card information maintained by the booking management system.

Abstract: A system includes at least one processing circuit including at least one memory and one or more processors configured to: obtain, via a user interface, a non-bounded query relating to a travel trip, the non-bounded query excluding at least one parameter associated with the travel trip; identify, via a first machine learning model, the at least one excluded parameter based on the non-bounded query; identify, via a second machine learning model and from among a first set of travel results that match the non-bounded query and the excluded parameter, a second set of the travel results that meet a presentation threshold of customer popularity based on at least one of a location selected by one or more users or a time selected by the one or more users; and present, via the user interface, one or more travel results of the second set, and the presentation threshold.

Abstract: A computing system includes a processing circuit having at least one processor coupled to at least one memory device. The processing circuit performs operations including receiving, from a user device during a search session, a first visual output from a first array of visual outputs comprising a first set of configurable parameters; extracting, using a machine learning model, at least one feature of the first visual output based on a characteristic of the first visual output; identifying, using the machine learning model, one or more second visual outputs that share the at least one feature of the first visual output based on a characteristic of each of the one or more second visual outputs; generating a second array of visual outputs comprising the one or more second visual outputs; and displaying, via a user interface of the user device and during the search session, the second array of visual outputs.

Abstract: A computing system for automated fraud risk reduction for travel-related transactions, the computing system including at least one processing circuit including at least one processor and at least one memory, the at least one memory storing instructions therein that, when executed by the at least one processor, cause the at least one processor to: receive data corresponding to a first travel-related transaction, process, using a first machine learning model, the data to automatically generate an output data set comprising a plurality of characteristics relating to the first travel-related transaction, the first machine learning model configured to generate the output data set by identifying the plurality of characteristics to include responsive to determining the plurality of characteristics are potentially relevant to a determination of whether the first travel-related transaction is fraudulent, and provide the generated output data set for use in analyzing whether the first travel-related transaction is frau

Abstract: One embodiment relates to a method for searching for travel items. The method includes obtaining interaction data indicating a set of interactions of a first user across a plurality of platforms. The method includes generating a dynamic user profile indicating a plurality of travel preferences for the first user. The method includes generating search suggestions for the first user based on the dynamic user profile, the search suggestions specific to the first user and generated based at least in part on characteristics of the dynamic user profile. The search suggestions include at least one of suggested search queries or suggested filters. The method includes receiving a selection from the first user of a first search suggestion. The method includes identifying a first plurality of travel items using the selected first search suggestion. The method includes providing, to the first user, the first plurality of travel items.

Abstract: One embodiment relates to a method for dynamic user preference assessment. The method includes receiving a dynamic user profile indicating a plurality of travel preferences for a user. The method includes providing, to the user, a first indication of a first set of one or more of the plurality of travel preferences indicated by the dynamic user profile at a first time. The method includes obtaining interaction data indicating interactions of the user across a plurality of platforms. The method includes processing the interaction data to infer changes to the plurality of travel preferences indicated by the dynamic user profile. The method includes updating the dynamic user profile to include the changes to the plurality of travel preferences.

Abstract: One embodiment relates to a method for travel comparison. The method includes obtaining, by one or more processing circuits, interaction data indicating a set of interactions of a first user across a plurality of platforms. The method includes generating a dynamic user profile indicating a plurality of travel preferences for the first user using the interaction data. The method includes providing, to the first user, a first set of travel search results based on the dynamic user profile. The method includes generating a comparison among two or more travel items included in the first set of travel search results, where the comparison relates to one or more features of the two or more travel items, and where generating the comparison includes selecting the one or more features based at least in part on one or more characteristics of the dynamic user profile.

Abstract: Systems and methods of recommending insights to optimize an experience. In some implementations, a request is received to optimize an experience based on a display option of a plurality of display options, one or more filters, and/or one or more metrics. Based on the request, the systems and methods can access (e.g., from a sampled data set) metric data associated with each of the display options. Metric data corresponding to each display options can be compared to generate insights based on each comparison. The systems and methods can determine whether an insight corresponds to a positive improvement and rank the insights based on preconfigured criteria. In addition, insights can be implemented automatically and/or recommended to a user in order to optimize the experience (e.g., based on the one or more metrics).

Abstract: A computing system includes at least one processing circuit having at least one processor and at least one memory device. The processing circuit performs operations including: providing a chat interface to allow a plurality of travelers to initiate a chat session in which the plurality of travelers collaborate to plan a trip; receiving, via the chat session, input from the plurality of travelers related to the trip; and automatically interacting, via a chatbot, with the plurality of travelers within the chat session to plan the trip by: processing, using a machine learning model, a content of the chat session to generate one or more recommendations for the trip, wherein processing the content of the chat session includes generating the one or more recommendations using the input from the plurality of travelers; and providing the generated one or more recommendations to the plurality of travelers within the chat session.

Abstract: Aspects of the present disclosure enable a storage manager to provide access to storage systems of varying types, such as database storage systems or indexed data storage systems, to a data source and allow for use of reserved storage capacity of the storage systems. The storage manager may provide access to storage systems under the control of different cloud storage providers. The storage manager may provide for temporary data storage in a reserved portion of a storage system when processing capacity of a data processing system is exceeded. The storage manager may provide for temporary storage of query results retrieved from a database system in a reserved portion of a data store. The storage manager may provide for temporary storage of data used for data enrichment in a reserved portion of a data store.