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公开(公告)号：US10822761B1
公开(公告)日：2020-11-03
申请号：US16516147
申请日：2019-07-18
Applicant: Airbnb, Inc.
Inventor： Nicole Voyen
Abstract: A foundation structure is made up of a screw that is vertically adjustable into a pile to a desired height, a ball joint connected to the screw, and load bearing components that can be adjusted on the ball joint in 3-dimensional space with respect to the position of the pile. The load bearing components include at least two plates that, between them, define a hollow slot into which an anchor bolt can be held in place vertically while still having allowance for lateral motion. A load bearing plate at the top of the structure can be laterally translated based on movement of the anchor bolt. The load bearing plate is removably couplable to the floor of a building. The structure allows for vertical, lateral, and angular adjustment, providing tolerance for foundation misalignments due to inconsistencies inherent to topography and/or offset between an intended and an actual point of installation.
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公开(公告)号：US20200312021A1
公开(公告)日：2020-10-01
申请号：US16369852
申请日：2019-03-29
Applicant: Airbnb, Inc.
Inventor： Wren Dougherty , David Whitten McGavern , John William Scalo , Damjan Stankovic , Alexander Thomas Brehm
Abstract: Systems and methods are provided for receiving image data via a camera of a computing device, the image data comprising a plurality of image frames; displaying a 3D reconstruction of the image data on a graphical user interface (GUI) displayed on a computing device as the image data is received and the 3D reconstruction of the image data is generated; detecting at least one object corresponding to one or more of a plurality of predefined object types in the image data; determining dimensions of the at least one object in 3D space based on the 3D reconstruction of the image data; and displaying in the GUI the at least one detected object.
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43.发明申请公开(公告)号：US20200090116A1
公开(公告)日：2020-03-19
申请号：US16688569
申请日：2019-11-19
Applicant: Airbnb, Inc.
Inventor： Spencer de Mars , Yangli Hector Yee , Peng Ye , Fenglin Liao , Li Zhang , Kim Pham , Julian Qian , Benjamin Yolken
Abstract: 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.
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公开(公告)号：US20200081988A1
公开(公告)日：2020-03-12
申请号：US16124095
申请日：2018-09-06
Applicant: Airbnb, Inc.
Inventor： Shijing Yao , Yizheng Liao
Abstract: A computer implemented method for incorporating multiple objectives in a ranked list of search results includes receiving a search query from a client device, accessing a set of stored listings for goods or services and probabilities of serving the listings, defining a serving vector as a probability distribution over the set of listings, providing a serving vector as input to a multi-objective function, decomposing the multi-objective function into one or more objective functions, generating a ranked list of the listings based at least in part on the serving vector that maximizes the decomposed multi-objective function, and providing the listings to the client device according to the order of the ranked list. Each objective function addresses a different goal in an overall diversity optimization.
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公开(公告)号：US20190311044A1
公开(公告)日：2019-10-10
申请号：US15949834
申请日：2018-04-10
Applicant: AIRBNB, Inc.
Inventor： Tao Xu , Haibin Cheng , Malay Haldar , Brendan Marshall Collins
Abstract: An online reservation system is configured to receive requests from a guest for searching property listings and to return property listings that satisfy the search criteria of the requests. The online reservation system uses a machine learning system to rank the property listings returned by the search. The machine learning system uses objective functions to determine parameters for each property listing and assign a ranking based on the parameters. A first objective function generates a parameter indicating an extent to which a property listing matches preferences of the guest, and is based on data about the guest's interactions with the reservation system. A second objective function generates another parameter indicating an extent to which the search request matches the preferences of the host associate with the property listing, and is based on data about the host's responses to reservation requests.
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Patent Agency Ranking
公开(公告)号：US10430730B2
公开(公告)日：2019-10-01
申请号：US14800369
申请日：2015-07-15
Applicant: Airbnb, Inc.
Inventor： Lu Cheng , Surabhi Gupta , Frank Lin
Abstract: Listings and reviews of listings can be processed to identify descriptive attributes for locations associated with the listings. To do this, a corpus of words is generated for various locations based on listings in the locations and reviews of those listings. An expected frequency, and per-location frequency for each word is determined. These numbers are in turn used to determine a number of high frequency listing locations, and a number of below expected frequency listing locations for each word. Based on a comparison of the number of high frequency listing locations and the number of below expected frequency listing locations of a word with an attribute reference number, the word can be identified either as an attribute that is likely descriptive of the location, or not.
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公开(公告)号：USD859432S1
公开(公告)日：2019-09-10
申请号：US29642495
申请日：2018-03-29
Applicant: Airbnb, Inc.
Designer： Daniel Spitzer-Cohn , Emre Ozdemir , Josh Leong , Fabio Resende , Alexandre Matthias Schleifer , Nathaniel Abbott
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公开(公告)号：US10360220B1
公开(公告)日：2019-07-23
申请号：US14968750
申请日：2015-12-14
Applicant: Airbnb, Inc.
Inventor： Alok Gupta
IPC: G06F16/2457 , G06N5/04 , G06N20/00 , G06F16/2455
Abstract: A behavior detection module constructs a random forest classifier (RFC) that takes into account asymmetric misclassification costs between a set of classification labels. The classification label estimate is determined based on classification estimates from the plurality of decision trees. Each parent node of a decision tree is associated with a condition of an attribute that splits a parent node into two child nodes by maximizing an improvement function based on a training database. The improvement function is based on an asymmetric impurity function that biases the decision tree to decrease the error for a label with high misclassification cost over the other, at the cost of increasing the error of the other label with a lower misclassification cost.
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公开(公告)号：US20190138529A1
公开(公告)日：2019-05-09
申请号：US16235551
申请日：2018-12-28
Applicant: Airbnb, Inc.
Inventor： Spencer de Mars , Kim Pham , Maxim Charkov
IPC: G06F16/2457 , G06F16/248 , G06Q50/14 , G06Q30/02 , G06Q10/02
Abstract: 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.
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公开(公告)号：US20190132333A1
公开(公告)日：2019-05-02
申请号：US16218069
申请日：2018-12-12
Applicant: Airbnb, Inc.
Inventor： Stephen Kirkham , Michael Lewis
CPC classification number: H04L63/126 , G06F21/31 , G06F21/316
Abstract: Methods and systems for verifying the identity and trustworthiness of a user of an online system are disclosed. In one embodiment, the method comprises receiving online and offline identity information for a user and comparing them to a user profile information provided by the user. Furthermore, the user's online activity in a third party online system and the user's offline activity are received. Based on the online activity and the offline activity a trustworthiness score may be calculated.
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