Abstract: Some aspects relate to technologies for performing item retrieval on a listing platform using clusters of interchangeable parts formed using fitment data. In accordance with some aspects, item data is accessed for each of a plurality of part item listings on a listing platform, where the item data for each part item listing includes fitment data. An item embedding is generated for each part item listing using the item data. The item embeddings are clustered to generate a plurality of clusters, wherein each cluster includes one or more item embeddings. Cluster data is stored for the plurality of clusters. The cluster data for each cluster associates a cluster identifier and an item listing identifier for each item embedding in the cluster. The cluster data can be leveraged to perform item retrieval for the listing platform.

Abstract: Some aspects relate to technologies for performing item retrieval on a listing platform using clusters of interchangeable parts formed using fitment match. In accordance with some aspects, item data is accessed for part item listings on a listing platform, where the item data for each part item listing includes fitment data for each of a number of different fitments. For each part item listing, a fitment hash is generated using fitment data for each fitment of the part item listing. The part item listings are clustered based on overlap of fitment hashes for the part item listings. Cluster data is stored for the part item listing clusters. The cluster data for each part item listing cluster associates a cluster identifier and an item listing identifier for each part item listing in the part item listing cluster. The cluster data can be leveraged to perform item retrieval for the listing platform.

Abstract: Some aspects relate to technologies for performing item retrieval on a listing platform using clusters of interchangeable parts formed using fitment data. In accordance with some aspects, item data is accessed for each of a plurality of part item listings on a listing platform, where the item data for each part item listing includes fitment data. An item embedding is generated for each part item listing using the item data. The item embeddings are clustered to generate a plurality of clusters, wherein each cluster includes one or more item embeddings. Cluster data is stored for the plurality of clusters. The cluster data for each cluster associates a cluster identifier and an item listing identifier for each item embedding in the cluster. The cluster data can be leveraged to perform item retrieval for the listing platform.

Abstract: Some aspects relate to technologies for employing metadata identifiers for part item listings on a listing platform to generate inventory intelligence. In accordance with some aspects, textual analysis of listing data for each of a plurality of part item listings on a listing platform is performed to assign a metadata identifier to each part item listing. The metadata identifier for each part item listing comprises a combination of an inventory segment identifier, a category identifier, and fitment data. For a first metadata identifier, a set of part item listings having the first metadata identifier is identified. Demand data and/or supply data is aggregated for the set of part item listings to provide aggregated data. A user interface with one or more metrics is generated using the aggregated data, and the user interface is communicated over a network to a computing device for presentation.