Abstract: Some aspects relate to technologies for generating pivots using a generative model and grouping items into pivot groups using the pivots. Pivots are generated by obtaining item information for items, generating a prompt using the item information, and causing a generative model to use the prompt to generate text for the pivots, including a pivot name and pivot description for each pivot. A pivot embedding is also generated for each pivot. When items are to be returned to a user device (e.g., as recommended items or search result items), item embeddings for the items and the pivot embeddings for the pivots are used to assign each item to a particular pivot to generate pivot groups that each includes a pivot name, a pivot description, and assigned items. User interface information is provided to present at least a portion of the pivot groups on a user device.

Abstract: Some aspects relate to technologies for using synthetic items generated by a generative model to perform item retrieval for a listing platform based on seed item listings. In some examples, a textual indication of a seed item listing from a listing platform is received. Based on the seed item listing, a textual indication of one or more synthetic items generated by a generative model are obtained. The textual indication of each synthetic item can be generated by the generative model at runtime or previously generated by the generative model and retrieved at runtime using one or more caching techniques. A search is performed on an item listings data store for the listing platform based on the textual indication of the one or more synthetic items to identify one or more item listings. An indication of the one or more item listings is provided for presentation as item listing recommendations.

Abstract: A wave spectrum calculation method based on GNSS wave measuring buoy is provided, which includes: placing GNSS drift buoys in the sea, collecting buoy position data; then obtaining three-dimensional velocity data of ocean waves; performing high pass filtering on velocity data of a sliding window to remove noise signals and trend terms, retaining wave motion data; calculating a cross spectrum and wave direction spectrum. The present disclosure solves limitations of traditional GNSS measurement methods applied to ocean buoy wave measurement, such as limited observation distance, high cost, tedious measurement and average calculation accuracy, and a need for correction services. The measurement accuracy is high and no additional correction services are required, which is more suitable for wave measurement, the wave spectrum algorithm in this method can adapt to more complex observation environments and incorporate results of a velocity measurement algorithm into a matched wave spectrum algorithm.

Abstract: Some aspects relate to technologies for generating pivots using a generative model and grouping items into pivot groups using the pivots. Pivots are generated by obtaining item information for items, generating a prompt using the item information, and causing a generative model to use the prompt to generate text for the pivots, including a pivot name and pivot description for each pivot. A pivot embedding is also generated for each pivot. When items are to be returned to a user device (e.g., as recommended items or search result items), item embeddings for the items and the pivot embeddings for the pivots are used to assign each item to a particular pivot to generate pivot groups that each includes a pivot name, a pivot description, and assigned items. User interface information is provided to present at least a portion of the pivot groups on a user device.

Abstract: A wave spectrum calculation method based on GNSS wave measuring buoy is provided, which includes: placing GNSS drift buoys in the sea, collecting buoy position data; then obtaining three-dimensional velocity data of ocean waves; performing high pass filtering on velocity data of a sliding window to remove noise signals and trend terms, retaining wave motion data; calculating a cross spectrum and wave direction spectrum. The present disclosure solves limitations of traditional GNSS measurement methods applied to ocean buoy wave measurement, such as limited observation distance, high cost, tedious measurement and average calculation accuracy, and a need for correction services. The measurement accuracy is high and no additional correction services are required, which is more suitable for wave measurement, the wave spectrum algorithm in this method can adapt to more complex observation environments and incorporate results of a velocity measurement algorithm into a matched wave spectrum algorithm.