Microsoft Technology Licensing, LLC

Yucan Zhang

Arun Sacheti

Marcelo Medeiros De Barros

Parthasarathy Govindarajen

Achraf Chalabi

Sumit Chatterjee

Sharada Chandrasekaran

Aditya Khandelwal

Xulong Zhang

Arun Kumar Chippada

Aspects of the present disclosure relate to providing a shoppable video corpus by generating a shoppable URL. A URL is extracted from a video corpus, in which the extracted URL may be a long URL or a short URL. Extracted URLs are then combined and normalized. From the normalized URL, noise is removed and quality control is performed. As a result, shoppable URL may be presented at the user's computing device as personal recommendation. The video and metadata of the cleaned URL is also ingested and stored in a database for future reference.

Building shoppable video corpus out of a generic video corpus via video meta data link

A computing system includes a processor and memory storing instructions that, when executed by the processor, cause the processor to perform acts. The acts include receiving a query provided by a user. The acts additionally include determining that the query is related to a comparison between entities. Based upon the determining that the query is related to the comparison between entities, the computing system generates a prompt that is to be input to a generative language model, where the prompt includes:) an instruction for the generative language model to generate a table based upon the query; and) attribute values for entities identified by a search system based upon the query. The acts also include providing the prompt as input to the generative language model, where the generative language model generates a table based upon the prompt, and further where the table includes the attribute values for the entities.

Computer-implemented table construction

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Bothell, WA, United States of America

Yucan Zhang