Airbnb, Inc.

Spencer De Mars

Maxim Charkov

Kim Pham

Bar Ifrach

Li Zhang

Yangli Hector Yee

Peng Ye

Benjamin Henry Yolken

Fenglin Liao

Julian Qian

Tao Xu

A computer implemented system and method for selecting and notifying operators of the option to enable a record activation feature for a short interval of time for the records they offer in a selected geographic area. Enabling record activation for a record indicates that the record may be booked without the operator's to manual approval of the transaction. Before selecting and notifying operators, a demand for database requests is predicted. Operators that are most likely to offer their record for record activation are identified. A quality score is determined for each identified record based on the likelihood that the record will get booked once the operator has programmatically enabled record activation. The records needed to fulfill the demand for database requests are selected based on their quality score and the operators of the selected records are notified of the option to enable record activation.

Automated database record activation using predictive modeling of database access

This disclosure includes systems for regression-tree-modified feature vector machine learning models for utilization prediction in time-expiring inventory. An online computing system receives a feature vector for a listing and inputs the feature vector and modified feature vectors into a demand function to generate demand estimates. The system inputs the demand estimates into a likelihood model to generate a set of request likelihoods, each request likelihood representing a likelihood that the time-expiring inventory will receive a transaction request at each of a set of test price and test times to expiration. The system further trains a regression tree model based on a set of training data comprising each of the request likelihoods from the set and the test price and test time period to expiration used to generate the demand estimate that was used to generate the request likelihood.

Regression-tree compressed feature vector machine for time-expiring inventory utilization prediction

Methods and systems for machine learning assisted search functions for unique accommodations founded in listing booking conversion are disclosed. In one embodiment, an online booking system models the conversion propensity of listings based on statistical relationships between features of previously received accommodation reservation requests and the booking of those reservation requests by guests. In particular, the system classifies reservation requests based on several features&#x2014;a reservation request either possesses a feature or does not possess a feature. The conversion propensity of a listing for a particular request feature is modeled based on the relationship between the reservation requests that possess the feature and the reservation requests that are booked by a guest.

Unique accommodation search improvement founded in listing booking conversion

Methods and systems for determining the preferences of hosts offering accommodations are disclosed. In one embodiment, an online booking system models the preferences of hosts based on statistical relationships between features of previously received accommodation reservation requests and the acceptance of those reservation requests by the hosts. In particular, the system classifies reservation requests based on several features&#x2014;a reservation request either possesses a feature or does not possess a feature. The preference of a host for a particular request feature is modeled based on the relationship between the reservation requests that possess the feature and the reservation requests that are accepted by the host.

Determining host preferences for accommodation listings

A computer implemented system and method for selecting and notifying operators of the option to enable a record activation feature for a short interval of time for the records they offer in a selected geographic area. Enabling record activation for a record indicates that the record may be booked by a user without first requesting the operator to manually approve the transaction request and waiting for the operator's approval of the request. Before selecting and notifying operators, a demand for database requests is predicted. Operators that are most likely to offer their record for record activation are identified. A quality score is determined for each identified record based on the likelihood that the record will get booked once the operator has programmatically enabled record activation. The records needed to fulfill the demand for database requests are selected based on their quality score and the operators of the selected records are notified of the option to enable record activation.

Growing community of inventors

San Francisco, CA, United States of America

Spencer De Mars