Expedia, Inc.

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.

Systems and methods for providing improved graphical user interfaces are disclosed. A method includes: receiving experience information associated with an experience; evaluating the experience information based on contextual information associated with the experience; determining a priority of the experience information based on the evaluation; retrieving a digital object template from a limited number of digital object templates based on the determined priority of the experience information; populating the retrieved digital object template with corresponding experience information to generate a contextual digital interface object; and providing the contextual digital interface object on a graphical user interface of a user device, the contextual digital interface object comprising a selectable feature based on the corresponding experience information.

Systems and methods are described for providing personalized travel experiences to a user. In some implementations, a user query related to a request to generate travel recommendations is obtained. The systems and methods can access the user data store to obtain user profile data. Based at least in part of the user profile data, the systems and methods can utilize a case-specific user analysis model to determine the user's specific travel preferences. Based at least in part on the user's specific travel preferences and query, the systems and methods can generate a prompt to input to an LLM. The LLM can output personalized travel recommendations based at least in part on the input prompt to provide to the user.

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.

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.

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.

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.

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).

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.

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.