Identifying gaps in search results

A recommendation engine that identifies gaps in search results generated in response to search queries sent to a search engine that identifies applications implicated by the search queries, the recommendation engine comprising:

• a storage device storing a query record datastore, the query record datastore storing a plurality of query records, each query record including query data and query log data, wherein the query data indicates instances where a search query was processed by the search engine and the query log data indicates one or more sets of search results provided in response to the search query by the search engine, each set of search results including application identifiers respectively indicating applications that were represented in the set of search results in response to the search query;
• a processing device that executes computer executable instructions, the instructions, when executed by the processing device, causing the processing device to:
• identify a target query record from the query record datastore corresponding to a target search query;
• determine a target query recommendation score of the target search query based on the target query record;
• determine whether the target query recommendation score is below a threshold;
• and
• when the target query recommendation score is below the threshold, recommend the target search query to a target organization,
• wherein recommending the target search query includes:
• including a query identifier of the target search query in a set of recommended search queries;
• for each search query in the set of recommended search queries, performing entity recognition on the search query to identify zero or more potential entity types associated with the search query;
• determining a category corresponding to the target search query based on the entity recognition;
• and
• generating, by the processing device, a report that indicates the category of the target search query, and
• wherein determining the category based on the entity recognition includes:
• generating a matrix based on the entity recognition, the matrix having a first dimension indicating the search queries in the set of recommended search queries and a second dimension indicating possible entity types, wherein elements of the matrix indicate whether a particular search query implicates a particular entity type;
• and
• for each entity type in the matrix:
• determining whether to recommend the entity type based on a number of populated elements in the matrix;
• and
• identifying the entity type as a recommended category based on the determining whether to recommend the entity type.