Search request processing

1 . A method for processing search requests at a search platform, the search platform being arranged to access a cache with a number of incomplete search results, wherein each incomplete search result comprises at least one first data field, the method comprising:

in response to receiving a search request with at least one search parameter from a client, determining, using the cache, one or more of the incomplete search results with first data fields that correspond to the at least one search parameter;

for each determined incomplete search result, generating at least one second data field using a machine learning model, wherein the at least one second data field corresponds to the at least one search parameter and the at least one first data field of each determined incomplete search result, wherein generating the at least one second data field comprises:

traversing a hierarchical tree with multiple branches;

utilizing the machine learning model to predict a subset of the branches of the hierarchical tree for traversing;

skipping traversing the hierarchical tree when the predicted subset of the branches has been traversed;

assembling a number of completed search results on the basis of the determined incomplete search results and the generated at least one second data field; and

returning at least one of the completed search results to the client.

2 . The method of claim 1 , wherein the search request indicates at least two search parameters, wherein at least one first search parameter relates to at least one first data field and at least one second search parameter relates to the at least one second data field, wherein the method comprises:

determining the one or more of the incomplete search results with first data fields that correspond to the at least one first search parameter;

for each determined incomplete search result, generating the at least one second data field using the machine learning model, wherein the at least one second data field corresponds to the at least one second search parameter and the at least one first data field of each determined incomplete search result.

3 . The method of claim 1 , wherein the machine learning model comprises at least one of deep neural network, a gradient boosting tree model, and a generative artificial intelligence model.

4 . The method of claim 1 , comprising

skipping traversing the hierarchical tree prior to completing traversing the predicted subset of the branches in response to a further side-condition being fulfilled.

5 . The method of claim 1 , further comprising:

receiving, from the client, a previous search request preceding the search request;

generating, using at least an original data source, one or more complete previous search results including at least one first data field and at least one second data field corresponding to one or more search parameters in the previous search request;

returning at least one of the generated one or more complete previous search results to the client;

wherein the search request from the client requests an update of at least one of the returned one or more complete previous search results, the update requiring an update of at least one second data field and wherein generating at least one second data field using the machine learning model constitutes the update of the at least one second data field.

6 . A search platform configured to perform the method of claim 1 .

7 . A non-transitory computer readable medium storing computer program instructions which, when executed at a computer, implements the method of claim 1 .

8 . The method of claim 4 , wherein the search request indicates at least two search parameters, wherein at least one first search parameter relates to at least one first data field and at least one second search parameter relates to the at least one second data field, wherein the method comprises:

determining the one or more of the incomplete search results with first data fields that correspond to the at least one first search parameter;

for each determined incomplete search result, generating the at least one second data field using the machine learning model, wherein the at least one second data field corresponds to the at least one second search parameter and the at least one first data field of each determined incomplete search result.

9 . The method of claim 4 , wherein the machine learning model comprises at least one of deep neural network, a gradient boosting tree model, and a generative artificial intelligence model.

10 . The method of claim 4 , further comprising

receiving, from the client, a previous search request preceding the search request;

generating, using at least an original data source, one or more complete previous search results including at least one first data field and at least one second data field corresponding to one or more search parameters in the previous search request;

returning at least one of the generated one or more complete previous search results to the client;

wherein the search request from the client requests an update of at least one of the returned one or more complete previous search results, the update requiring an update of at least one second data field and wherein generating at least one second data field using the machine learning model constitutes the update of the at least one second data field.

11 . A search platform configured to perform the method of claim 4 .

12 . A non-transitory computer readable medium storing computer program instructions which, when executed at a computer, implements the method of claim 4 .