Airbnb has filed a patent for a method of sorting search results based on user preferences. The patent describes a system that uses machine learning algorithms to analyze user interactions with search results and detect common relationships. This information is then used to compute a user interest characteristic for subsequent search results, which are presented to the user in an ordered list based on their preferences. GlobalData’s report on Airbnb gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Airbnb, AI for workflow management was a key innovation area identified from patents. Airbnb's grant share as of June 2023 was 1%. Grant share is based on the ratio of number of grants to total number of patents.

Sorting search results based on user interest characteristics

Source: United States Patent and Trademark Office (USPTO). Credit: Airbnb Inc

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By GlobalData

A recently filed patent (Publication Number: US20230185813A1) describes a method for sorting search results based on user interactions and preferences. The method involves two phases: an initial phase and an implementation phase.

During the initial phase, the method receives multiple search requests from a user and associates them with the user. For each search request, a set of search results is provided on a user interface. These search results have attribute types that indicate a common relationship between them. The method collects search interaction data, including attribute parameter data and user interaction data, which reflect the user's interest and interactions with the search results. A machine learning algorithm is then trained to analyze this data and recognize common relationships.

In the implementation phase, the method receives a subsequent search request from the user. It identifies a set of subsequent search results and computes a user interest characteristic for each result based on the similarity between the attribute preference data detected during the initial phase and the attribute parameters of the subsequent search results. The method then sorts the subsequent search results based on the user interest characteristic and transmits an ordered list of the results to the user.

The patent also includes additional claims. Claim 2 states that the user interaction data indicating user interest includes information about the number of times the user has interacted with a search result and the duration of time spent viewing and interacting with it. Claim 3 adds that the user interaction data may also include the number of requests for additional information and the number of transactions initiated by the user related to the search result. Finally, claim 4 specifies that if the subsequent search request includes a user-specified sorting parameter, the method will sort the results first based on the user-specified parameter and then by the user interest characteristic.

Overall, this patent describes a method that utilizes machine learning to analyze user interactions and preferences with search results, allowing for personalized sorting and presentation of subsequent search results.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.