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 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 user profile. Generating the search suggestions includes determining that a portion of the interaction data is related to an upcoming trip and generating the search suggestions based on the user profile and relating to the upcoming trip. The method includes identifying a first plurality of travel items using a selected first search suggestion. The method includes providing, to the first user, the first plurality of travel items.

Abstract: A system includes one or more processors to: receive data from a plurality of sources, aggregate the received data, detect one or more anomalies in the aggregated data set by analyzing the aggregated data set by applying a filter that identifies data values within the data set that deviate by more than a predefined value from a representative data value of the aggregated data set, isolate the one or more anomalies to a particular time frame within a predefined time period and a predefined geographic region, query a machine learning model by formulating a prompt including the particular time frame and the predefined geographic region, receive at least one basis for the one or more anomalies based on the prompt, validate the at least one basis, and notify a user regarding the at least one basis via a client application associated with the system operating a device of the user.

Abstract: A computing system includes a memory storing instructions that, when executed by a processor, cause the processor to: receive, via a chat session on a first user interface, input related to a trip from a plurality of travelers collaborating to plan the trip; interact, via a chatbot, with the plurality of travelers to plan the trip by: generating one or more recommendations using the input; and providing, via the chatbot, the generated one or more recommendations to the plurality of travelers within the chat session; and generate a second user interface that is separate from the first user interface, the second user interface comprising one or more of: selections related to the trip or recommendations related to the trip, wherein the one or more selections and/or recommendations related to the trip are determined using the interactions of the plurality of travelers within the chat session.

Abstract: Systems and methods for providing improved graphical user interfaces are disclosed.

Abstract: A system can include one or more processors configured to store text strings corresponding to an application feature; obtain, via a network interface, one or more data files each comprising natural language content; execute, using a task agent, one or more large language models using the natural language content to generate an identification of the application feature; retrieve, using the task agent, the one or more text strings; filter, using the task agent, the one or more text strings; execute, using the task agent, the one or more large language models using the filtered one or more text strings, the identification of the application feature, and an identification of the first entity as an input; and transmit a message for presentation at a computing device, the message containing the visual representation of the input.

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: A computing system includes a memory device and a processor structured to: receive, from a user device, a media input; extract, using a machine-learning model, at least one feature of the media input; identify, using the machine-learning model, at least one intent; determine, using the machine-learning model, at least one action policy; generate a user interface comprising the media input, the at least one extracted feature of the media input, and the at least one action policy; provide the user interface to the user device; receive, via an input to the user interface, an indication of a selection of the at least one action policy displayed on the user interface; generate a second user interface comprising a plurality of options associated with the selected at least one action policy; and provide the second user interface to the user device.

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, at least one selected output generated for display via the user device in response to a search query; retrieving information related to the at least one selected output; generating a summary of the at least one selected output based on the retrieved information related to the at least one selected output; and displaying, via a graphical user interface, the summary of the at least one selected output simultaneously with a conversation platform, wherein the conversation platform is configured to enable a conversation between a conversational assistant and a user of the user device relating to the at least one selected output.

Abstract: Systems and methods are described for generating and refining videos in response to receiving agent inputs. Example systems can be configured to obtain, from a client device, a request to generate a set of images (including videos). The systems can be configured to determine, responsive to the request, a first image from among a dataset comprising a plurality of predetermined images using the one or more aspects. In some examples, the system can be configured to provide the first image and a prompt to a machine learning model to cause the machine learning model to generate the set of images as an output. In response to obtaining the set of images from the machine learning model, the systems described can provide the set of images to cause the client device to display at least one image of the set of images.

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: 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.

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.