Abstract: One of more unique products can be selected for advertisement over a digital marketing channel. The selection is based on the calculation of a base impression budget, calculated per product per day, which calculation considers information related to a product, including supply and demand at the market level, characteristics of the property, and popularity of the listing. A real-time, or current, impression budget is calculated to determine whether a particular product should be recommended to a user. Every time the product is advertised to a user, a user intent value is calculated, indicating the user's likelihood of purchasing the product within a given period of time, along with the user intent of every user to which the product has been advertised. The user intent calculation may consider information specific to the user, such as the user's activity history and profile. These user intent values are subtracted from the base impression budget to obtain a real-time impression budget.

Abstract: A base query having a plurality of base query terms is obtained. A plurality of problem log files are accessed. Words, contained in a corpus vocabulary, are extracted from the plurality of problem log files. Based on the words extracted from the plurality of problem log files, a first expanded query is generated from the base query. The corpus is queried, via a query engine and a corpus index, with a second expanded query related to the first expanded query.

Abstract: Systems and methods are provided for receiving a plurality of images corresponding to a listing in an online marketplace, generating a scene type for each image of the plurality of images, and grouping each image into a scene type group of a set of predefined scene types. Each group of images are input into a respective machine learning model specific to the scene type of the group of images to generate a visual score for each image in each group of images, and an attractiveness score is generated for the listing in the online marketplace based on the visual scores for each image in each group of images.

Abstract: Scheduling events with multiple invitees includes: identifying a plurality of invitees for an event in a calendar system having at least one processor; searching an availability associated with each of the invitees to determine a number of periods of availability in the calendar system, at least some of the invitees being available during each period of availability; creating a separate instance of the event in the calendar system for each identified period of availability; and for each invitee available during at least one of the periods of availability, assigning the invitee to one said instance of the event for which that invitee is available with the calendar system.

Abstract: Systems and methods are provided for extracting a plurality of features for a listing from a datastore comprising a plurality of listings and a plurality of features for each of the plurality of listings, determining a cluster of similar listings to the listing and generating a set of cluster features for the cluster of similar listings, analyzing the set of cluster features for the cluster of similar listings based on a booking price, using a first trained machine learning model to determine a cluster-level probability of booking the listing on the given date, analyzing the plurality of features for the listing using the booking price, using a second trained machine learning model to determine a listing-level probability of booking the listing on the given date, and generating a final probability of booking by combining the cluster-level probability of booking and the listing-level probability of booking.

Abstract: A cost-focused determination of whether to deliver an electronic advertisement or notice to a particular user can be made through a cumulative consideration of the predicted return on investment over each of a plurality of electronic channels. A plurality of channel-specific budget values are calculated for the user, one for each channel, each setting an upper spending limit for advertisement to the user over that channel based on the user's information and their activity on the channel. A global budget is calculated for the user using a weighted aggregation of the channel-specific values, information about the user and their activity with the advertiser, and consideration of “overlap” effects of advertising to the same user on several channels. When managing whether to deliver an advertisement over a channel, if the channel-specific value is lower than the global budget, the advertisement is delivered, and the global budget is decreased by a complementary amount.

Abstract: A system for identifying and reporting traffic events is presented. Position and motion data from two or more vehicles are uploaded to a data center. The system identifies an accident between first and second vehicles by correlating the motion and position information of the first vehicle with the motion and position information of the second vehicle.

Abstract: Embodiments of the present invention address deficiencies of the art in respect to social bookmarking and provide a method, system and computer program product for aggregating scoring of tagged content across social bookmarking systems. In an embodiment of the invention, a method for aggregating scoring of tagged content across social bookmarking systems can be provided. The method can include combining tag scores for a tag in content across multiple different social bookmarking systems into a single aggregate tag score and applying the single aggregate tag score to the tag in the content. In this regard, combining tag scores for a tag in content across multiple different social bookmarking systems into a single aggregate tag score can include computing either a simple or a weighted average of the tag scores for the tag to produce the single aggregate score.

Abstract: Text including at least a first term can be presented on a display. An enterprise glossary can be queried to identify at least a first curation parameter assigned to the first term. A first score can be determined for the first term based, at least in part, on the first curation parameter assigned to the first term. The first score can be assigned to a first data value. The first data value can be presented on the display.

Abstract: Methods and systems for updating a calendar entry for an accommodation listing are disclosed. In one embodiment, the method comprises generating an availability model and an acceptance model for an accommodation listing in an accommodation reservation system and determining based on those models the probability that the accommodation listing would be able to be booked. Furthermore, the result of an accommodation search query can be filtered and/or sorted using the determined probability of booking.

Abstract: An asset merging system generates a merge file containing assets from multiple party systems. The asset merging system receives the assets and determines whether any of the assets has changed versus previously received versions of the assets. If any of the received assets has changed, the asset merging system generates a merge file containing at least the most recent version of the changed assets. The asset merging system then communicates the merge file to a content delivery network (CDN) for serving to users requesting for content that uses the assets in the merge file.

Abstract: GPS devices of vehicles send routes of drivers and automatically generated coordinates of driver positions to a host application for saving on memory remote from the vehicles. Selections of saved routes by drivers and coordinates of driver positions indicating starting and completion of the saved routes are sent to the host application for storing driver trip times corresponding to the saved routes. A driver sends a request for a saved route to the host application. When the host application identifies other saved routes that have start and destination locations within predetermined distances of start and destination locations of the requested saved route, the GPS device of the driver receives at least one of the other save routes from the host application.

Abstract: Disclosed are ways to generate and present recommendations which provide a user with the ability to explore the follow-on consequences of accepting the recommendations. In some aspects, a method includes receiving a first user input including a recommendation topic, presenting, via a display, an exploration structure including a node corresponding to the recommendation topic, receiving data corresponding to the node from a knowledge repository, analyzing the received data to determine at least one follow-on recommendation based on the node, and presenting each determined follow-on recommendation in the exploration structure as a child node of the node corresponding to the recommendation topic.

Abstract: Providing dynamic, interest-based change notifications includes detecting an event for an artifact managed by a collaborative system, determining a user subscribed to the artifact, and, responsive to the event, calculating a score for the event using a processor. The score is user-specific and indicates a level of interest of the user for the event. The score is compared with a threshold score. A change notification of the event is sent to the user responsive to determining that the score exceeds the threshold score.

Abstract: Prioritizing items based on user activity includes determining a user interest based on a current user activity and prioritizing items in a list presented in a display based on the user interest.

Abstract: Systems and methods for providing contextual calendar reminders are provided. A host can receive a calendar reminder notifying the host that a calendar for a property listing maintained by the host may need to be updated. The system can provide the host with a reminder to update the calendar for the property listing based on criteria related to the expected number of times the host will view the calendar within a designated time period and the timing of the host's last interaction with the calendar. If the designated criteria are satisfied, the system can generate a reminder for the host to update the calendar for the property listing. Before sending the reminder to the host, the system confirms that the host did not recently interact with the calendar and if the host did interact with the calendar, the system cancels the sending of the reminder.

Abstract: Systems and methods are provided for generating a base visual score for each candidate image of a plurality of images received by a computing system, based on the scene type of each image. For each candidate image, the computing system multiplies the base visual score by a feature importance weight to generate a first visual score, adds respective scene type bonus points to the first visual score to generate a second visual score, and adds diversity scoring points to the second visual score to generate a final visual score for each candidate image. The computing system ranks the candidate images based on the final visual scores and provides a specified number of the top-ranked candidate images to be displayed on a display of the computing device.

Abstract: Systems and methods are provided for analyzing booking session data to generate a plurality of feature vectors for each booking session of the plurality of booking sessions, and generating training data comprising the plurality of feature vectors for each booking session and at least a first constraint. The systems and methods further providing for calculating a set of weights using the training data, wherein each weight is a lowest weight satisfying the most constraints possible, wherein the set of weights comprises a weight associated with each feature in the plurality of feature vectors, and computing a reservation value for each of a plurality of clients for each of a plurality of listings and for each date of a plurality of dates, based on the set of weights and the plurality of feature vectors.

Abstract: A user expertise classifying method, system, and computer program product, include analyzing an input by a user based on at least one of vocabulary, orthography, and grammar of the user input, processing user background data obtained from a database, and calculating an expertise score of the user based on the analyzed user input and the processed background data.